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  • Safari, an O'Reilly Media Company.  (194)
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  • 1
    Online Resource
    Online Resource
    [Place of publication not identified] : Pragmatic AI Solutions
    Language: English
    Pages: 1 online resource (1 video file (1 hr., 5 min.)) , sound, color.
    Edition: [First edition].
    DDC: 006.3
    Keywords: Artificial intelligence Study guides Examinations ; Microsoft Azure (Computing platform) Study guides Examinations ; Instructional films ; Nonfiction films ; Internet videos
    Abstract: Microsoft Azure AI Fundamentals (AI-900) Certification Pass the AI Fundamentals certification This early release (ongoing) course will give you everything you need to pass the Azure AI Fundamentals (AI-900) certification. This is the foundational certification for doing Machine Learning and Data Science using Azure and its specialized services. The course will go into every content that is relevant to pass the certification including how to create a study guide and strategy to pass the exam. This course includes and covers all of the author's study notes so that you can use them in addition to your own notes . Course overview This course contains a complete walkthrough over all of the content relevant for the AI-900 certification with a summary and specialized notes after each sections, following the same content that is available as Learning Paths. Aside from the video content, create your own study notes and strategy using the example reference guide Course Content Get Started with AI Get Started with AI Study notes Get Started with Artificial Intelligence on Azure About your instructor Alfredo Deza has over a decade of experience as a Software Engineer doing DevOps, automation, and scalable system architecture. Before getting into technology he participated in the 2004 Olympic Games and was the first-ever World Champion in High Jump representing Peru. He currently works in Developer Relations at Microsoft and is an Adjunct Professor at Duke University. This solid background in technology and teaching, including his experience studying and passing the AI-900 is seen throughout this course, where you will get a first-hand experience with study notes, example repositories, and a solid study strategy. Resources Pytest Master Class Practical MLOps book.
    Note: Online resource; title from title details screen (O'Reilly, viewed January 10, 2023)
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  • 2
    Online Resource
    Online Resource
    [Place of publication not identified] : Pragmatic AI Solutions
    Language: English
    Pages: 1 online resource (1 video file (32 min.)) , sound, color.
    Edition: [First edition].
    DDC: 004.67/82
    Keywords: Windows Azure ; Machine learning ; Artificial intelligence ; Instructional films ; Nonfiction films ; Internet videos
    Abstract: This introductory lesson will walk you through everything you need to know to quickly get started with Azure ML Studio using AutoML. After creating the necessary resources, you'll walk through the steps needed to create a regression job using a dataset. Next you'll create a compute cluster and review the different options available and finally, you'll analyze the results after the best model is selected.
    Note: "Pragmatic AI Labs course.". - Online resource; title from title details screen (O'Reilly, viewed January 23, 2023)
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  • 3
    Online Resource
    Online Resource
    [Place of publication not identified] : Pragmatic AI Solutions
    Language: English
    Pages: 1 online resource (1 video file (3 hr., 24 min.)) , sound, color.
    Edition: [First edition].
    DDC: 005.1
    Keywords: Rust (Computer program language) ; Computer software Development ; Rust (Langage de programmation) ; Instructional films ; Nonfiction films ; Internet videos ; Films de formation ; Films autres que de fiction ; Vidéos sur Internet
    Abstract: Rust For DevOps Learn how to use and apply DevOps principles using Rust This is an early release of the course. In this course, you will learn the basics of DevOps using the Rust programming language. DevOps helps you build, test, and deploy code faster while creating a robust foundation for your projects and teams. First, we will talk about what DevOps is. You will learn things like automation, monitoring, and working together as a team. Then, we will see how to use DevOps ideas in Rust code. You will learn about version control, testing, containers, and deploying Rust programs. Although this course explains the foundations of DevOps and using Rust which is ideal for beginners, experienced Rust developers will find solid advice in how to apply DevOps best practices to existing applications. Learning Objectives The core principles and practices of DevOps How to apply DevOps concepts to build, package, and deploy applications with Rust The basics of containerization and how to leverage containers for DevOps with Rust Course Content This course is divided into 4 weeks with 3 lessons that contain about 6 videos each. Each video is about 5 minutes long and contains a hands-on demonstration of the concepts covered in the lesson. The course is designed to be taken in order, but you can jump to any lesson you want to learn more about. Week 1: Introduction to DevOps Principles Introduction to DevOps Principles DevOps Considerations for Applications Basics of Containerization Week 2: Implementing monitoring and logging strategies Introduction to monitoring and logging strategies Tools and Services for monitoring and logging Logging with Rust About your instructor Alfredo Deza has over a decade of experience as a Software Engineer doing DevOps, automation, and scalable system architecture. Before getting into technology he participated in the 2004 Olympic Games and was the first-ever World Champion in High Jump representing Peru. He currently works in Developer Relations at Microsoft and is an Adjunct Professor at Duke University teaching Machine Learning, Cloud Computing, Data Engineering, Python, and Rust. With Alfredo's guidance, you will gain the knowledge and skills to build robust applications and infrastructure with the Rust programming language and for Rust applications. Resources Rust Bootcamp Deploy Rust on Azure Functions DevOps command-line tools in Python and Rust Switching to Rust from Python First Steps with Rust Learning Path.
    Note: Online resource; title from title details screen (O'Reilly, viewed September 05, 2023)
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  • 4
    Online Resource
    Online Resource
    [Place of publication not identified] : Pragmatic AI Solutions
    Language: English
    Pages: 1 online resource (1 video file (6 hr., 12 min.)) , sound, color.
    Edition: [First edition].
    DDC: 005.13/3
    Keywords: Rust (Computer program language) ; Instructional films ; Nonfiction films ; Internet videos
    Abstract: Rust Bootcamp Course Overview Welcome to our comprehensive Rust programming course! In this immersive learning experience, we will guide you through every aspect of Rust, empowering you to become a proficient developer. This course is ideal for beginners wanting to become proficient in Rust or from existing developers coming from languages like Python or JavaScript that want to learn Rust fundamentals. Get started by setting up your preferred text editor and installing Rust. We'll ensure that you have all the necessary tools to create a productive coding environment. By leveraging the capabilities of Visual Studio Code and enabling the Rust Analyzer, you'll unlock a feature-rich ecosystem that enhances your development workflow. Experience the game-changing potential of GitHub Copilot, an AI-powered assistant. Sign up for GitHub Copilot and witness its transformative impact on your coding experience. We'll guide you through the installation process and show you how to leverage its intelligent suggestions for accelerated programming. Master concepts and fundamentals like control flow, variable assignment, and immutability. Learn the intricacies of loops, conditional statements, and effective error handling techniques. With Rust's borrowing concept at your disposal, you'll develop secure and high-performance code. Build upon your foundation with advanced topics like structs, string manipulation, and working with vectors and enums. We'll explore real-world library development using Cargo, Rust's robust package manager. Effective documentation and debugging techniques will become second nature as you optimize your code. Organize your code effectively with modules, extending functionality and enhancing reusability. Dive into comprehensive testing methodologies to ensure the reliability and correctness of your programs. From writing tests for your code to handling private components, you'll gain expertise in developing robust software projects. Our immersive learning experience includes hands-on examples, interactive exercises, and practical projects. Rust's performance, safety, and expressiveness will be at your fingertips as you embrace its immense potential. Join us on this rewarding journey to unlock the power of Rust programming and propel your career forward. Enroll now and gain the skills, knowledge, and expertise to thrive in the world of Rust. Whether you're a beginner, coding novice, or an experienced developer seeking new horizons, our course is your gateway to writing elegant, reliable, and high-performance code. Embrace the possibilities of Rust and embark on a rewarding programming journey today with one of the most loved programming languages. Learning Objectives Gain a solid understanding of Rust's core concepts, including variable assignment, control flow, and immutability, to write efficient and reliable code. Master the utilization of powerful development tools such as Visual Studio Code and the Rust Analyzer, enhancing productivity and enabling seamless coding experiences. Explore GitHub Copilot and learn how to leverage its AI-driven suggestions to accelerate programming and boost code quality. Develop proficiency in working with advanced Rust features, such as structs, enums, and string manipulation, to build robust and flexible applications. Discover the intricacies of module organization and extend functionality through effective code structuring, promoting code reusability and maintainability. Acquire comprehensive testing skills, including writing tests for code components and handling private code, ensuring the reliability and correctness of Rust programs. Gain hands-on experience in real-world library development using Cargo, Rust's package manager, and become proficient in documenting code and debugging techniques. These compelling learning objectives will guide you through the course, helping you acquire essential skills and knowledge to become a confident Rust developer. Course Content This course is divided into 4 weeks with 3 lessons that contain about 6 videos each. Each video is about 5 minutes long and contains a hands-on demonstration of the concepts covered in the lesson. The course is designed to be taken in order, but you can jump to any lesson you want to learn more about. Week 1: Setting up your development environment Reference GitHub Repository Setting up your text editor Using GitHub Copilot with Rust Introduction to GitHub Codespaces for Rust Week 2: Rust fundamentals Reference GitHub Repository Introduction to Rust Loops and Control flow Function basics Week 3: Structs, Types, and Enums Reference GitHub Repository Using structured data Exploring strings and vectors Working with Enum and Variants Week 4: Applying Rust Reference GitHub Repository Building a real-world library Extending functionality with modules Testing Rust code About your instructor Alfredo Deza has over a decade of experience as a Software Engineer doing DevOps, automation, and scalable system architecture. Before getting into technology he participated in the 2004 Olympic Games and was the first-ever World Champion in High Jump representing Peru. He currently works in Developer Relations at Microsoft and is an Adjunct Professor at Duke University teaching Machine Learning, Cloud Computing, Data Engineering, Python, and Rust. With Alfredo's guidance, you will gain the knowledge and skills to build with the Rust programming language. Resources Deploy Rust on Azure Functions DevOps command-line tools in Python and Rust Switching to Rust from Python First Steps with Rust Learning Path.
    Note: Online resource; title from title details screen (O'Reilly, viewed June 13, 2023)
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  • 5
    Online Resource
    Online Resource
    [Place of publication not identified] : Pragmatic AI Solutions
    Language: English
    Pages: 1 online resource (1 video file (41 min.)) , sound, color.
    Edition: [First edition].
    DDC: 005.13/3
    Keywords: Rust (Computer program language) ; Microsoft Azure (Computing platform) ; Cloud computing ; Cloud computing ; Microsoft Azure (Computing platform) ; Rust (Computer program language) ; Instructional films ; Internet videos ; Nonfiction films ; Instructional films ; Nonfiction films ; Internet videos
    Abstract: Deploy Rust on Azure Functions Learn how to deploy Rust functions to Azure Functions with this comprehensive video course. You will start by creating a simple HTTP-triggered function, and then use GitHub Actions to automate your deployment. Deploying Rust in Azure can be frustrating because there is no first-class support yet for it. You will learn what are some of the caveats and what are some strategies you can use to properly deploy a very basic Rust HTTP API. Course Overview We will start by covering the basics of Azure Functions and Rust, and then dive into more advanced topics such as configuring your function's environment, application settings, and using external crates. By the end of this course, you will have a working knowledge of how to deploy and manage your Rust functions on Azure Functions using automation to quickly re-deploy or update your function. Course Content Introduction to Azure Functions - Learn the basics of Azure Functions and how they work with Rust. Creating Your First Azure Function in Rust - Create a simple HTTP-triggered function in Rust and deploy it to Azure Functions. Configuring Your Function Environment - Learn how to use environment variables to configure your function's behavior. Use GitHub Actions for automation About your instructor Alfredo Deza has over a decade of experience as a Software Engineer doing DevOps, automation, and scalable system architecture. Before getting into technology he participated in the 2004 Olympic Games and was the first-ever World Champion in High Jump representing Peru. He currently works in Developer Relations at Microsoft and is an Adjunct Professor at Duke University. With Alfredo's guidance, you will gain the knowledge and skills needed to deploy and manage your Rust functions on Azure Functions. Resources Deploying containers to Azure Practical MLOps book Automated Azure Resource Cleanup Azure Fundamentals Certification.
    Note: Online resource; title from title details screen (O'Reilly, viewed March 21, 2023)
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  • 6
    Online Resource
    Online Resource
    [Place of publication not identified] : Pragmatic AI Solutions
    Language: English
    Pages: 1 online resource (1 video file (2 hr., 7 min.)) , sound, color.
    Edition: [First edition].
    DDC: 006.3/1
    Keywords: Machine learning ; Instructional films ; Nonfiction films ; Internet videos
    Abstract: Introduction to MLflow for MLOps Learn how to use MLflow for managing the machine learning lifecycle. Track experiments, package models, and deploy to production. In this course you'll learn how to use MLflow - an open source platform for managing the machine learning lifecycle. You'll learn how to: Install MLflow and explore its components like the UI, tracking, and model packaging Log metrics, parameters, and artifacts to track ML experiments Create reproducible ML projects with MLflow for repeatable model training Package models and dependencies for deployment and serving Use model registries to version, stage, and deploy models Deploy models to tools like Azure ML and SageMaker This course includes hands-on exercises, projects, and real-world examples so you can apply your new MLflow skills immediately. Use the reference repository for MLFlow examples and projects: Example MLFlow Projects Learning objectives Install and configure MLflow Use the tracking UI and APIs Log metrics, parameters, tags, and artifacts Create reproducible ML projects Version, stage, and deploy models with registries Deploy models to Azure ML, SageMaker, etc Lesson 1: Introduction to MLflow Lesson Outline Overview of MLflow components Installation and configuration Tracking experiments with UI, Python, R APIs Logging metrics, params, tags, artifacts Lesson 2: MLflow Projects Lesson Outline Motivation for reproducible ML projects Creating project directories Running projects locally or on Git Customizing execution environments Lesson 3: MLflow Models Lesson Outline Packaging models and dependencies Model versioning with registries Staging and promoting model stages Deploying models to services About your instructor Alfredo Deza has over a decade of experience as a Software Engineer doing DevOps, automation, and scalable system architecture. Before getting into technology he participated in the 2004 Olympic Games and was the first-ever World Champion in High Jump representing Peru. He currently works in Developer Relations at Microsoft and is an Adjunct Professor at Duke University teaching Machine Learning, Cloud Computing, Data Engineering, Python, and Rust. With Alfredo's guidance, you will gain the knowledge and skills to work with MLFlow and apply it to MLOps tasks. Resources Pytest Master Class Practical MLOps book.
    Note: "Pragmatic AI Labs course.". - Online resource; title from title details screen (O'Reilly, viewed August 14, 2023)
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  • 7
    Online Resource
    Online Resource
    [Place of publication not identified] : Pragmatic AI Solutions
    Language: English
    Pages: 1 online resource (1 video file (1 hr., 39 min.)) , sound, color.
    Edition: [First edition].
    DDC: 005.13/3
    Keywords: Python (Computer program language) Study guides Examinations ; Application program interfaces (Computer software) Study guides Examinations ; Machine learning Study guides Examinations ; Computer programming Study guides Examinations ; Instructional films ; Nonfiction films ; Internet videos
    Abstract: Hands-on Python for MLOps Build powerful APIs, tools, and scripts with Python Use Python to create APIs and automation scripts for machine learning operations. Learn to leverage APIs, build CLI tools, and develop web services. If you are new to Machine Learning Operations or want to know more about the foundations of Python for MLOps, this course will walk you through the basics. In this course, you'll learn how to use Python for automation, APIs, and building useful command-line interfaces. We'll cover consuming APIs, creating CLI tools, packaging projects, and building web services to expose machine learning models. The course includes hands-on examples and projects so you can apply what you learn right away. By the end of the course, you'll have practical skills to automate workflows and develop interfaces for machine learning. This course includes GitHub repositories you can reference: Python CLI Examples Basic Python CLI Web API with Python and Hugging Face models Learn objectives Consume and use APIs and SDKs in Python Create command-line programs for automation Develop web services and APIs with Python frameworks Package Python projects for distribution Apply skills to build useful interfaces for ML models Lesson 1: Working with APIs in Python Lesson Outline Overview of APIs and SDKs Using the Requests Library Consuming REST APIs Python SDKs like NumPy and SciPy Project: Building a Python script using APIs Lesson 2: Building Command-line Interfaces Lesson Outline Intro to automation with CLI tools Parsing arguments and options Organizing code into modules Python packaging for distribution Project: CLI tool for machine learning Lesson 3: Developing Web APIs Lesson Outline REST API concepts Web frameworks like Flask and FastAPI Building an API with Flask Developing APIs with FastAPI OpenAPI specs and documentation Project: Web API for movie recommendations About your instructor Alfredo Deza has over a decade of experience as a Software Engineer doing DevOps, automation, and scalable system architecture. Before getting into technology he participated in the 2004 Olympic Games and was the first-ever World Champion in High Jump representing Peru. He currently works in Developer Relations at Microsoft and is an Adjunct Professor at Duke University. This solid background in technology and teaching, including his past experience as a Linux system administrator is seen throughout this course, where you will get a first-hand experience with high-level knowledge and practical examples. Resources Pytest Master Class Practical MLOps book.
    Note: Online resource; title from title details screen (O'Reilly, viewed August 14, 2023)
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  • 8
    Online Resource
    Online Resource
    [Place of publication not identified] : Pragmatic AI Solutions
    Language: English
    Pages: 1 online resource (1 video file (3 hr., 27 min.)) , sound, color.
    Edition: [First edition].
    DDC: 005.13/3
    Keywords: Python (Computer program language) ; SQL (Computer program language) ; Computer programming ; Instructional films ; Nonfiction films ; Internet videos
    Abstract: Scripting with Python and SQL for Data Engineering Learn Python data structures, web scraping, SQL, and MySQL from the ground up. Master essential skills for collecting, storing, and working with data. In this hands-on course for beginners, you'll learn how to: Store and manipulate data using Python lists, dictionaries, JSON Write reusable scripts to process data Connect Python to databases like SQLite and MySQL Query, import, and export data with SQL Scrape and parse websites using Beautiful Soup and Scrapy Persist scraped data to databases and files You'll use the following example repositories to practice: Mapping data in Python Python Scripting Scrapping Basics Key topics include: Mapping, iterating, and persisting data structures Creating modules, scripts, and workflows in Python SQL essentials - queries, statements, aggregations Setting up connections from Python to SQLite and MySQL Scraping data locally and at scale with spiders Storing scraped data to optimize pipelines You'll build your data wrangling skills through practical examples and hands-on coding exercises in every lesson. By the end of the course, you'll have experience building end-to-end data engineering scripts. Whether you're a beginner looking to learn Python and SQL, or want to develop robust data engineering skills, this course will get you started. Enroll now and start collecting, storing, and working with data using Python and SQL You'll gain hands-on experience building Python scripts and SQL queries for common data engineering tasks. This course is divided in 4 weeks: Week 1 Working with Data in Python By the end of Week 1 you'll be able to: Apply Python data structures like lists, dicts Extract data from sources like CSV, JSON Load and persist data using JSON Lesson 1: Data Structures in Python Lesson Outline Lists, tuples, dictionaries Working with pandas DataFrames Loading data files like CSV into data structures Lesson 2: Reading and Writing Data Lesson Outline Reading and writing CSV files Serializing Python objects with JSON Parsing and dumping JSON data Lesson 3: Persisting and Loading Data in Python Lesson Outline Loading data from files Saving data from Python to disk Loading and saving data to JSON Week 2 Python Scripting and SQL By the end of Week 2 you'll be able to: Write reusable Python scripts Use SQLite to persist data Query SQLite databases with Python Lesson 1: Python Scripting Techniques Lesson Outline Writing modular, reusable Python scripts Exception handling and logging Python virtual environments Lesson 2: Python with SQLite Lesson Outline Creating SQLite databases from Python Writing tables with SQLAlchemy Querying SQLite from Python with SQLAlchemy Week 3 Learning Objectives By the end of Week 3 you'll be able to: Scrape and collect data from websites Build scalable scraping scripts Persist scraped data to files/databases Lesson 1: Web Scraping with Python Lesson Outline HTML parsing and structure Using Beautiful Soup for scraping Storing scraped data in Python Lesson 2: Scalable Web Scraping Lesson Outline Scraping best practices Scaling scraping with multiprocessing Storing scraped data in databases Week 4 Learning Objectives By the end of Week 4 you'll be able to: Connect to MySQL from Python Execute SQL statements and queries Import and export data from MySQL Lesson 1: Python and MySQL Lesson Outline Installing MySQL and configuration Connecting Python to MySQL Executing queries and statements Lesson 2: Running SQL queries from VSCode Use Visual Studio Code to build SQL queries Execute and review SQL queries from Visual Studio Code Lesson 3: Importing and Exporting Data Lesson Outline Loading and exporting CSV data Best practices for moving data into MySQL Automating data imports with Python About your instructor Alfredo Deza has over a decade of experience as a Software Engineer doing DevOps, automation, and scalable system architecture. Before getting into technology he participated in the 2004 Olympic Games and was the first-ever World Champion in High Jump representing Peru. He currently works in Developer Relations at Microsoft and is an Adjunct Professor at Duke University. This solid background in technology and teaching, including his experience teaching and authoring content about DevOps and MLOps will give you everything you need to get started applying these powerful concepts. Resources Python and Rust CLI Tools Linux For Beginners Hands on Python for MLOps.
    Note: Online resource; title from title details screen (O'Reilly, viewed August 14, 2023)
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  • 9
    Online Resource
    Online Resource
    [Place of publication not identified] : Pragmatic AI Solutions
    Language: English
    Pages: 1 online resource (1 video file (1 hr., 33 min.)) , sound, color.
    Edition: [First edition].
    DDC: 005.4/32
    Keywords: Linux ; Operating systems (Computers) ; Instructional films ; Nonfiction films ; Internet videos
    Abstract: Linux for Beginners A hands on and practical introduction of Linux This early release (ongoing) course will give you a foundational knowledge to quickly get started with Linux. You will learn practical examples packaged in easy-to-follow videos that give you just enough knowledge to use Linux. There is a strong focus on using the terminal exclusively for this course, which is the best way to ensure a wide variety of Linux environments can be used with almost no difference in concepts. The course will not cover deep Linux internals or advanced usage. It will also not go through specialized scenarios that are meant to pass a Linux certification. Learn objectives Use a terminal to navigate the file system Understand different Linux versions and use readily available versions without installing Linux Use a shell with common features Create and edit files using a terminal text editor Manage system processes and services Install and remove packages About your instructor Alfredo Deza has over a decade of experience as a Software Engineer doing DevOps, automation, and scalable system architecture. Before getting into technology he participated in the 2004 Olympic Games and was the first-ever World Champion in High Jump representing Peru. He currently works in Developer Relations at Microsoft and is an Adjunct Professor at Duke University. This solid background in technology and teaching, including his past experience as a Linux system administrator is seen throughout this course, where you will get a first-hand experience with high-level knowledge and practical examples. Resources Pytest Master Class Practical MLOps book.
    Note: Online resource; title from title details screen (O’Reilly, viewed February 7, 2023)
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  • 10
    Online Resource
    Online Resource
    [Place of publication not identified] : Pragmatic AI Solutions
    Language: English
    Pages: 1 online resource (1 video file (2 hr., 49 min.)) , sound, color.
    Edition: [First edition].
    DDC: 005.1
    Keywords: Python (Computer program language) ; Rust (Computer program language) ; Computer software Development ; Instructional films ; Nonfiction films ; Internet videos
    Abstract: DevOps command-line tools in Python and Rust Use both Python and Rust to automate systems engineering tasks In this introductory course, you will learn how to build powerful command-line tools using Python and Rust. You will discover how to set up a development environment, incorporate user input, expand functionality using modules and libraries, and optimize performance for common DevOps and Systems Engineering tasks. Whether you're new to programming or an experienced developer, this course will teach you the fundamentals of building command-line tools using Python and Rust. By the end of the course, you'll have the skills to automate tasks and improve the efficiency of your DevOps and Systems Engineering workflows. This course includes GitHub repositories that you can use as a reference for all the learning content: Python CLI Examples Rust CLI Examples Learn objectives Set up a development environment for building command-line tools. Build basic command-line tools. Expand the functionality of command-line tools using modules and libraries. Create a simple command-line tool using Rust and understand the basic structure of a Rust-based CLI tool. Incorporate user input, such as arguments and options. Learn how to organize code into modules and packages, and work with dependencies and libraries in both Python and Rust. About your instructor Alfredo Deza has over a decade of experience as a Software Engineer doing DevOps, automation, and scalable system architecture. Before getting into technology he participated in the 2004 Olympic Games and was the first-ever World Champion in High Jump representing Peru. He currently works in Developer Relations at Microsoft and is an Adjunct Professor at Duke University. This solid background in technology and teaching, including his past experience as a Linux system administrator is seen throughout this course, where you will get a first-hand experience with high-level knowledge and practical examples. Resources Pytest Master Class Practical MLOps book.
    Note: Online resource; title from title details screen (O'Reilly, viewed April 24, 2023)
    Library Location Call Number Volume/Issue/Year Availability
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  • 11
    Online Resource
    Online Resource
    [Place of publication not identified] : Pragmatic AI Solutions
    Language: English
    Pages: 1 online resource (1 video file (2 hr., 57 min.)) , sound, color.
    Edition: [First edition].
    DDC: 006.3/1
    Keywords: Machine learning Study guides Examinations ; Cloud computing Study guides Examinations ; Instructional films ; Nonfiction films ; Internet videos
    Abstract: Hugging Face for MLOps Learn how to leverage Hugging Face and its powerful machine learning capabilities. Build, train, and deploy your own models using the Hugging Face platform and libraries. In this course you'll get hands-on with Hugging Face and learn how to: Access and use pre-trained models from the Hub Fine-tune models with your own data Build machine learning pipelines with Hugging Face Transformers Add and version your own datasets Containerize and deploy Hugging Face models Automate workflows with GitHub Actions By the end, you'll have practical experience building, training, and deploying Hugging Face models, including production deployment to the Azure cloud. Learning objectives Find and use pre-trained models Fine-tune models for custom tasks Build ML pipelines with Hugging Face libraries Create and version datasets Containerize models for production Automate workflows for MLOps Lesson 1: Getting Started with Hugging Face Lesson Outline Overview of Hugging Face Hub Browsing models and datasets Using Hugging Face repositories Managing spaces and access Lesson 2: Applying Hugging Face Models Lesson Outline Downloading models from the Hub Using models with PyTorch/TensorFlow Leveraging tokenizers and pipelines Performing inference with Hub models Lesson 3: Working with Datasets Lesson Outline Browsing datasets on Hugging Face Uploading and managing datasets Versioning datasets with dataset cards Loading datasets in PyTorch/TensorFlow Lesson 4: Model Serving and Deployment Lesson Outline Containerizing Hugging Face models Creating inference APIs with FastAPI Deploying to cloud services like Azure Automating with GitHub Actions About your instructor Alfredo Deza has over a decade of experience as a Software Engineer doing DevOps, automation, and scalable system architecture. Before getting into technology he participated in the 2004 Olympic Games and was the first-ever World Champion in High Jump representing Peru. He currently works in Developer Relations at Microsoft and is an Adjunct Professor at Duke University. This solid background in technology and teaching, including his experience teaching and authoring content about LOps will give you everything you need to get started applying these powerful concepts. Resources MLOps with Databricks Introduction to MLflow for MLOps Hands-on Python for MLOps.
    Note: "Pragmatic AI Labs course.". - Online resource; title from title details screen (O'Reilly, viewed August 14, 2023)
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  • 12
    Online Resource
    Online Resource
    [Place of publication not identified] : Pragmatic AI Solutions
    Language: English
    Pages: 1 online resource (1 video file (1 hr., 43 min.)) , sound, color.
    Edition: [First edition].
    DDC: 004.67/82
    Keywords: Windows Azure Study guides Examinations ; Database management Study guides Examinations ; Cloud computing Study guides Examinations ; Instructional films ; Nonfiction films ; Internet videos
    Abstract: Microsoft Azure Fundamentals (AZ-900) Certification Pass the Azure fundamentals certification This early release and ongoing course will give you everything you need to pass the Azure Fundamentals (AZ-900) certification. This is the foundational certification for Azure which is essential for working in Microsoft's cloud. The course will go into every content that is relevant to pass the certification including how to create a study guide and strategy to pass the exam. Course overview This course contains a complete walkthrough over all of the content relevant for the AZ-900 certification with a summary and specialized notes after each sections, following the same content that is available as Learning Paths. Aside from the video content, create your own study notes and strategy using the example reference guide This course includes all of the author's study notes so that you can use them in addition to your own notes. Course Content Describe Cloud Concepts Cloud Concepts Study notes Introduction to Azure Fundamentals Discuss Azure concepts Describe code Azure Architectural components About your instructor Alfredo Deza has over a decade of experience as a Software Engineer doing DevOps, automation, and scalable system architecture. Before getting into technology he participated in the 2004 Olympic Games and was the first-ever World Champion in High Jump representing Peru. He currently works in Developer Relations at Microsoft and is an Adjunct Professor at Duke University. This solid background in technology and teaching, including his experience studying and passing the AZ-900 is seen throughout this course, where you will get a first-hand experience with study notes, example repositories, and a solid study strategy. Resources Study notes Quick AZ-900 reference guide Azure Remote Compute for VSCode Automated Azure Resource Cleanup Azure SAMBA file share Learn Azure (AutoML) in one hour Deploying containers to Azure Practical MLOps book.
    Note: Online resource; title from title details screen (O'Reilly, viewed September 13, 2022)
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  • 13
    Online Resource
    Online Resource
    [Place of publication not identified] : Pragmatic AI Solutions
    Language: English
    Pages: 1 online resource (1 video file (8 min.)) , sound, color.
    Edition: [First edition].
    DDC: 006.3/12
    Keywords: Windows Azure ; Cloud computing ; Windows Azure ; Cloud computing ; Instructional films ; Internet videos ; Nonfiction films ; Instructional films ; Nonfiction films ; Internet videos
    Abstract: Azure in GitHub Actions Authenticate to Azure with GitHub Actions If you need to use GitHub Actions and interact with Azure resources, you'll need to authenticate properly. Authenticating is made easy by direct Action support in a workflow, but it requires a Service Principal created in a specific way that produces output that is required to go into a GitHub Secret. Using a sample GitHub repository, the video lesson will cover all the details you need to know to get a working GitHub workflow step to authenticate to Azure and then use the Azure CLI to perform operations. Learning Objectives In this lesson you will learn: Create a GitHub Action workflow to login to Azure Create an Azure Service Principal with enough permissions Add a GitHub Actions Secret from the Service Principal Run the workflow that uses the Azure CLI Useful Resources Sample GitHub Repository GitHub Actions and GitOps in One Hour Run Python in GitHub Actions Azure Service Principal documentation How to install the Azure CLI Free Azure Certification for Students.
    Note: Online resource; title from title details screen (O'Reilly, viewed June 21, 2022)
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  • 14
    Online Resource
    Online Resource
    [Place of publication not identified] : Pragmatic AI Solutions
    Language: English
    Pages: 1 online resource (1 video file (4 hr., 10 min.)) , sound, color.
    Edition: [First edition].
    DDC: 005.13/3
    Keywords: Python (Computer program language) ; Computer programming ; Instructional films ; Nonfiction films ; Internet videos
    Abstract: Python Bootcamp for Data Learn foundational Python with an emphasis for data In this course, you will learn how to work effectively with Python. You will understand how to use variables, create functions, and work with classes. That foundational knowledge will allow you to understand testing and testing techniques to validate your work and then move onto Pandas and Numpy which allows you to work effectively with data sets and other data science tasks. This is valuable for anyone wanting to get a quick introductory course on Python, like a student, programmer new to Python or aspiring data engineer or data scientist. At the end of this course you'll be ready to work with more advanced concepts with Pandas and Numpy with a solid foundation in Python for any other task. All lessons and videos have accompanying GitHub Repositories with example code. Learn Objectives This course has extensive content that covers Python for beginners and then moves onto more complex Python operations including data analysis, exploration, and manipulation with Pandas and NumPy. It will include the following learning objectives: Work with logic in Python, assigning variables and using different data structures Create functions and classes of different types Write, run, and debug tests using Pytest to validate your work Manipulate data with Pandas Create and modify NumPy arrays Index This course is divided into content for 4 weeks, with 3 lessons per week: Week 1: Introduction to Python Reference GitHub Repository Working with variables and types Introduction to Python data structures Adding and extracting data from data structures Week 2: Python functions and Classes Reference GitHub Repository Working with functions Building classes and using methods Modules and advanced usage Week 3: Testing in Python Reference GitHub Repository Introduction to testing Writing useful tests Test failures Week 4: Introduction to Pandas and Numpy Reference GitHub Repository Basic Pandas usage Working with datasets Introduction to NumPy Resources Week 1 GitHub repository: Introduction to Python Week 2 GitHub repository: Python Functions and Classes Week 3 GitHub repository: Testing In Python Week 4 GitHub repository: Introduction to Pandas and Numpy Python dictionaries Learn Module Testing In Python book Minimal Python book Python for Beginners Learn Path Practical MLOps book.
    Note: Online resource; title from title details screen (O'Reilly, viewed July 25, 2022)
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  • 15
    Online Resource
    Online Resource
    [Place of publication not identified] : Pragmatic AI Solutions
    Language: English
    Pages: 1 online resource (1 video file (6 min.)) , sound, color.
    Edition: [First edition].
    DDC: 005.117
    Keywords: Python (Computer program language) ; Application software Development ; Python (Langage de programmation) ; Logiciels d'application ; Développement ; Application software ; Development ; Python (Computer program language) ; Instructional films ; Internet videos ; Nonfiction films ; Instructional films ; Nonfiction films ; Internet videos ; Films de formation ; Films autres que de fiction ; Vidéos sur Internet ; Webcast
    Abstract: What does the Yield keyword do in Python? This video covers the basics so you can understand what yield is, what is a generator, and why is it different than any other iterable in Python A yield keyword makes a function a lazy iterable. Producing values one at a time. The function becomes a generator, so when called, the code will not execute. A generator is a function that uses the yield keyword. This function is an iterable that produces values one at a time, or does a lazy production of values. I'll use a Jupyter Notebook that you can use to follow along with practical examples that will show you what are some of the key differences and when or why you would use the yield keyword. In this video you will learn: What is an iterable and how is it different from using yield? What does yield do to a function? What is a Python generator Potential uses for a Python generator like infinite results Useful Resources GitHub repository with examples Build Python applications from scratch Try Azure for Free Introduction to Azure Databricks.
    Note: Online resource; title from title details screen (O'Reilly, viewed March 21, 2022)
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  • 16
    Online Resource
    Online Resource
    [Place of publication not identified] : Pragmatic AI Solutions
    Language: English
    Pages: 1 online resource (1 video file (19 min.)) , sound, color.
    Edition: [First edition].
    DDC: 005.3
    Keywords: Application software Development ; Cloud computing ; Microsoft Azure (Computing platform) ; Instructional films ; Nonfiction films ; Internet videos
    Abstract: MLOps deployment to Azure Container Apps Take advantage of insta-scaling for live inferencing Learn how to deploy an ML container with FastAPI and deploy it to Azure Container Apps with GitHub Actions. This repository gives you a good starting point with a Dockerfile, GitHub Actions workflow, and Python code that already works for generating text using GPT-2 with HuggingFace Transformers. First, you'll go through an architectural overview of the end-result, then you will go through every configuration item needed to set the automation right between Azure and GitHub Actions and the GitHub Container Registry. Finally, you'll see how to deploy and find a few crucial requirements needed for everything to work, like ingress ports and setting the right amount of RAM and CPU. Learn Objectives In this video lesson, I'll go over the details with an example repository you can use for reference including the following learning objectives: Use GitHub Container Registry to push a built container Use the Azure CLI in a GItHub Action to authenticate to Azure How to generate an Azure Service Principal and a Personal Access Token to authenticate Configure Azure Container Apps to correctly serve a model with enough resources Look at deployment logs to ensure things are working right Resources Example repository Practical MLOps book MLOps Maturity Model Packaging ML models MLOps packaging: HuggingFace and Docker MLOps packaging: HuggingFace and Azure Container Registry.
    Note: Online resource; title from title details screen (O'Reilly, viewed July 12, 2022)
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  • 17
    Online Resource
    Online Resource
    [Place of publication not identified] : Pragmatic AI Solutions
    Language: English
    Pages: 1 online resource (1 video file (15 min.)) , sound, color.
    Edition: [First edition].
    DDC: 005.26/2
    Keywords: Python (Computer program language) ; Computer programming ; Instructional films ; Nonfiction films ; Internet videos
    Abstract: Learn how to run Python scripts on GitHub Actions! This allows you to handle logic that might be a bit more complex, like setting conditional behavior based on results. I'll show you how in this GitHub Actions lesson for beginners so that you can use this in your own repository easily. Example repo in the lesson resources. Although GitHub actions is powerful as-is, it can get complicated when consuming inputs from other sources like an HTTP request providing JSON output. Imagine a scenario where, depending on the JSON output of an HTTP request you have to do an API call. You might be able to do this with a specialized action or workflow, but with Python it might be easier.
    Note: Online resource; title from title details screen (O’Reilly, viewed June 2, 2022)
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  • 18
    Online Resource
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    [Place of publication not identified] : Pragmatic AI Solutions
    Language: English
    Pages: 1 online resource (1 video file (14 min.)) , sound, color.
    Edition: [First edition].
    DDC: 005.1
    Keywords: Computer software Development ; Instructional films ; Nonfiction films ; Internet videos
    Abstract: VSCode development environments Learn different options for programming with VSCode Find out different ways you can use VSCode for development: on the web, with Codespaces or locally with configurable Docker containers This video will cover what makes each one different and when you might want to use one vs. the other. From quick edits on GitHub to a more powerful machine backed by a remote compute using Codespaces, it is all about flexibility! Topics Covered Include: Use quick edits with GitHub.dev that show on your repository Open any repository with VSCode.dev Use Codespaces with a powerful remote compute Configure a local codespace with Devcontainers using Docker Additional Resources Pytest Master Class AWS Solutions Architect Professional Course Github Actions and GitOps in One Hour Video Course Jenkins CI/CD and Github in One Hour Video Course AWS Certified Cloud Practitioner Video Course Advanced Testing with Pytest Video Course AWS Solutions Architect Certification In ONE HOUR Python for DevOps Master Class 2022: CI/CD, Github Actions, Containers, and Microservices MLOPs Foundations: Chapter 2 Walkthrough of Practical MLOps Learn Docker containers in One Hour Video Course Introduction to MLOps Walkthrough AZ-900 (Azure Fundamentals) Quick reference guide.
    Note: Online resource; title from title details screen (O'Reilly, viewed August 9, 2022)
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    Online Resource
    [Place of publication not identified] : Pragmatic AI Solutions
    Language: English
    Pages: 1 online resource (1 video file (16 min.)) , sound, color.
    Edition: [First edition].
    DDC: 006.3/1
    Keywords: Machine learning ; Computer software Development ; Instructional films ; Nonfiction films ; Internet videos
    Abstract: MLOps packaging: HuggingFace and Docker Hub Use automation to package models Learn how to package a HuggingFace GPT2 model using automation with MLOps and pushing the result to Docker Hub. With just a little bit of Python and FastAPI you can have a powerful text generation API that is self-documented! Learn Objectives In this video lesson, I'll go over the details with an example repository you can use for reference including the following learning objectives: Create a FastAPI application with HuggingFace Interact with the model with HTTP from a container using FastAPI Containerize the application using GitHub Actions Create repository secrets to login and push to Docker Hub Resources Example repository Practical MLOps book MLOps Maturity Model Packaging ML models.
    Note: Online resource; title from title details screen (O'Reilly, viewed July 6, 2022)
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  • 20
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    [Place of publication not identified] : Pragmatic AI Solutions
    Language: English
    Pages: 1 online resource (1 video file (1 hr., 7 min.)) , sound, color.
    Edition: [First edition].
    DDC: 005.13/3
    Keywords: Python (Computer program language) ; Web site development ; Python (Computer program language) ; Web site development ; Instructional films ; Internet videos ; Nonfiction films ; Instructional films ; Nonfiction films ; Internet videos
    Abstract: Python Testing for Beginners Over 1 hour of course material with practice code Quickly learn learn how to test in Python Learn the basics of Python testing in this course. From a brief overview of the standard library to using a more modern approach with Pytest, one of the most popular testing libraries in Python. By the end of this week, you should be comfortable working with existing tests, creating new tests, and debugging test failures. All lessons and videos have accompanying GitHub Repositories with example code. Reference GitHub Repository Learning Objectives In this course you will learn to: Understand the basics of testing and its importance Write and run tests with functions and classes Use Pytest for running and creating tests Apply different techniques for debugging including PDB and stopping on failure Use fixtures to simplify tests that make identical assertions Resources Python for beginners course Python Functions and Classes course Python Dictionaries course Pytest Master Class Python Bootcamp for Data Practical MLOps book.
    Note: Online resource; title from title details screen (O'Reilly, viewed August 23, 2022)
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  • 21
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    Online Resource
    [Place of publication not identified] : Pragmatic AI Solutions
    Language: English
    Pages: 1 online resource (1 video file (11 min.)) , sound, color.
    Edition: [First edition].
    DDC: 005.13
    Keywords: Text editors (Computer programs) ; Text editors (Computer programs) ; Instructional films ; Internet videos ; Nonfiction films ; Instructional films ; Nonfiction films ; Internet videos
    Abstract: VSCode for the web Use VSCode directly on the web for editing Git repos Although you can use VSCode locally, using it in the web allows you to avoid having an install and dealing with platform problems. There is no account required and you can directly edit GitHub repositories on the web. In the case of Python, there are a couple of constraints that you must be aware of, like no support to run the terminal and execute a Python program. But syntax and intellisense works great, and we can even make Jupyter Notebooks work with the help of an extension. If you are a beginner and trying out different text editors, or even if you are a seasoned developer, you will find a case to use this feature of VSCode. Learning Objectives In this lesson you will learn: Opening a GitHub repository directly on the web and start editing it Commit and push changes from VSCode on the web to GitHub What are the constraints and limitations of the Python support Use Jupyter Notebooks and find what are some of the problems you may find Useful Resources VSCode for the Web documentation Minimal Python book Free Azure Certification for Students Develop web applications with Visual Studio Code.
    Note: Online resource; title from title details screen (O'Reilly, viewed June 21, 2022)
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  • 22
    Online Resource
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    [Place of publication not identified] : Pragmatic AI Solutions
    Language: English
    Pages: 1 online resource (1 video file (12 min.)) , sound, color.
    Edition: [First edition].
    DDC: 006.3/12
    Keywords: Windows Azure ; Cloud computing ; Windows Azure ; Cloud computing ; Instructional films ; Internet videos ; Nonfiction films ; Instructional films ; Nonfiction films ; Internet videos
    Abstract: Automated deletion of Azure Resources Prevent surprise bills with automation Prevent your Azure bill from running wild! In this video I show how you can automate the removal of Azure resources on demand or by schedule. With GitHub Actions and an Azure account you can prevent services from running wild and causing unnecessary billing overcharges! With automation in place, there is no need to remember what VM you left running! First, you'll start by creating a GitHub Action that authenticates to Azure, then you will query locally your resource groups to identify which ones you can delete. Next, you will port the query over to the Action workflow. Finally, you will delete resources that match, making sure those are fully removed, preventing a large bill. You will need a GitHub and Azure account, an Azure Service Principal and the Azure CLI installed locally. Learning Objectives In this lesson you will learn: Create a GitHub Action workflow to query Resource Groups Query Resource Groups that match locally Use scripting to extract Resource Group names Remove Resource Groups with the Azure CLI in GitHub Actions Useful Resources Sample GitHub repository Create an Azure Service Principal for GitHub Actions Azure Service Principal documentation Install Azure CLI Free Azure Certification for Students Introduction to GitHub Actions Run Python In GitHub Actions.
    Note: Online resource; title from title details screen (O'Reilly, viewed June 20, 2022). - Online resource; title from title details screen (O'Reilly, viewed June 21, 2022)
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  • 23
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    Online Resource
    [Place of publication not identified] : Pragmatic AI Solutions
    Language: English
    Pages: 1 online resource (1 video file (1 hr., 38 min.)) , sound, color.
    Edition: [First edition].
    DDC: 005.1
    Keywords: Application software Development ; Cloud computing ; Instructional films ; Nonfiction films ; Internet videos
    Abstract: GitHub Codespaces Course A full introduction to Codespaces with practical examples This course will show you everything you need to know to be productive using GitHub Codespaces , a service that allows you to run a configurable development environment with one-click launch with a remote compute in the cloud. Being able to run Visual Studio Code in the cloud for any project with a pre-configured environment is going to allow you to concentrate on the learning if you are student, the teaching if you are a professor, or being plain productive if you are already a technologist. Learning Objectives This course goes through some of the basics of using default Codespaces environments, but it also goes into configuring environments to take advantage of its best features, including: Learning about Codespaces uses and how it fits for learning, teaching, or working in projects Running default Codespaces and configuring it in your GitHub account Configuring Codespaces for different development environments Applying practical examples in Codespaces environments using Docker, Python, and many other tools About your instructor Alfredo Deza has over a decade of experience as a Software Engineer doing DevOps, automation, and scalable system architecture. Before getting into technology he participated in the 2004 Olympic Games and was the first-ever World Champion in High Jump representing Peru. He currently works in Developer Relations at Microsoft and is an Adjunct Professor at Duke University. This solid background in technology and teaching, including his experience creating courses with Codespaces is seen throughout this course, where you will get a first-hand experience with practical examples as well as applicable configuration for any development environment. Resources Python Bootcamp Pytest Master Class Practical MLOps book What is GitHub Codespaces Azure Codespaces Template.
    Note: Online resource; title from title details screen (O'Reilly, viewed September 27, 2022)
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  • 24
    Online Resource
    Online Resource
    [Place of publication not identified] : Pragmatic AI Solutions
    Language: English
    Pages: 1 online resource (1 video file (1 hr., 28 min.)) , sound, color.
    Edition: [First edition].
    DDC: 005.26/2
    Keywords: Python (Computer program language) ; Computer programming ; Python (Langage de programmation) ; Programmation (Informatique) ; computer programming ; Instructional films ; Nonfiction films ; Internet videos ; Films de formation ; Films autres que de fiction ; Vidéos sur Internet ; Webcast
    Abstract: Python Command Line Tools Course This is a full Python CLI course that will take you from the most basic approaches to command line tools in Python to the more advanced featuers that use frameworks like argparse and Click. Everything on this course is available in the course Repository on GitHub, so that you can follow the examples closely and use that as a foundation with all examples and sample files. Building a CLI is the foundation for automation in your daily work By the end of the course you should feel confident in creating a tool, and the following: Create simple CLI tools without any frameworks Learn about arguments, flags, help menus and how to create them automatically Use the argparse framework to build more complex tools Build a CLI with the Click framework Use special features of Click like colored output and argument types Modularizing and project scaffolding in Python Packaging and packaging files in Python How to create tests and run them automatically Continuous Integration and Continuous Deployment with Github Actions for Python Packaging a CLI tool with an executable Distributing a CLI tool on PyPI (the Python Package Index) How to automatically test your project on a PR (GitHub pull request) How to automate publishing your tool to PyPI on a release We'll cover 3 different ways to create tools, from the very basic (with sys.argv) to using a framework that comes with Python ( argparse), and finally the more involved, by using an external library like Click. This flexibility is essential because it will let you decide when to use a simple single file with no dependencies to a fully featured framework like Click. Then you will learn about the project layout, modularizing and organizing your code in directories and files while keeping everything useful for a CLI. You will test your code using Pytest and then package your code using Python packaging files and tools. You will continue by automating everything, including the testing and linting using GitHub Actions, and finally publishing your project to the Python Package Index so that it can be installed by anyone in the world. Course Resources Course Repository on GitHub Build Python applications from scratch.
    Note: Online resource; title from title details screen (O'Reilly, viewed March 9, 2022)
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    Online Resource
    [Place of publication not identified] : Pragmatic AI Solutions
    Language: English
    Pages: 1 online resource (1 video file (4 min.)) , sound, color.
    Edition: [First edition].
    DDC: 005.13/3
    Keywords: Python (Computer program language) ; Computer programming ; Python (Langage de programmation) ; Programmation (Informatique) ; computer programming ; Instructional films ; Nonfiction films ; Internet videos ; Films de formation ; Films autres que de fiction ; Vidéos sur Internet ; Webcast
    Abstract: What is the if __name__ condition in Python for? If you've seen __main__ at the end of a Python script and wondered why that is there it is to avoid side effects when importing and allowing you to run the file as a script on the terminal. If you want more details, watch this short video where we work with a Python script to find out those side effects and how the Python script can change once the if condition with __name__ is done at the end. Next Steps Now that you know about the conditional at the end, you might want to explore writing Python scripts that use this trick. There are several examples you can follow in these GitHub repositories with argparse, the Click framework and using sys.argv: argparse GitHub repo examples sys.argv GitHub repo examples Build Python applications from scratch.
    Note: Online resource; title from title details screen (O'Reilly, viewed March 9, 2022)
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    Online Resource
    [Place of publication not identified] : Pragmatic AI Solutions
    Language: English
    Pages: 1 online resource (1 video file (23 min.)) , sound, color.
    Edition: [First edition].
    DDC: 005.133
    Keywords: Python (Computer program language) ; Information storage and retrieval systems ; Instructional films ; Nonfiction films ; Internet videos
    Abstract: Learn how to use Python dictionaries to store and retrieve data. Although dictionaries look complex with different ways to represent, retrieve, and store data, they can be straightforward to use. In this course I'll show you how to create, store, retrieve, and loop over dictionaries. Once you go through these different actions, you should be able to choose the right approach to work effectively with dictionaries. If you are already familiar with Python lists and you are ready to take the next step with dictionaries, then this course is for you.
    Note: Online resource; title from title details screen (O’Reilly, viewed June 2, 2022)
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    [Place of publication not identified] : Pragmatic AI Solutions
    Language: English
    Pages: 1 online resource (1 video file (9 min.)) , sound, color.
    Edition: [First edition].
    DDC: 005.7
    Keywords: Big data ; Microsoft Azure (Computing platform) ; Données volumineuses ; Instructional films ; Nonfiction films ; Internet videos ; Films de formation ; Films autres que de fiction ; Vidéos sur Internet ; Webcast
    Abstract: Azure Databricks with Pandas and Open Datasets. Find out how to get a working cluster with Databricks using Azure and then use the full Pandas API operating in the cluster with Open Datasets and a Python Jupyter Notebook. This video will walk you through creating a workspace in Azure to create the Databricks service, then create the cluster that comes with the Pyspark Pandas API, and finally import the open datasets into the cluster. Although straightforward to create a Databricks cluster with Azure, it is a bit more involved to run a Python Jupyter Notebook that has Azure ML Open Datasets installed and availabe in the cluster along with the ability to use the full Pandas API you are used to working with and taking advantage of the clustering capabilities from Databricks.
    Note: Online resource; title from title details screen (O’Reilly, viewed March 10, 2022)
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    Online Resource
    [Place of publication not identified] : Pragmatic AI Solutions
    Language: English
    Pages: 1 online resource (1 video file (15 min.)) , sound, color
    Edition: [First edition].
    DDC: 006.3/1
    Keywords: Machine learning ; Computer software Development ; Computer software ; Development ; Machine learning ; Instructional films ; Internet videos ; Nonfiction films ; Instructional films ; Nonfiction films ; Internet videos
    Abstract: MLOps packaging: HuggingFace and GitHub Container Registry Use automation to package models to GitHub Learn how to package a HuggingFace GPT2 model using automation with MLOps and pushing the result to GitHub Container Registry. With just a little bit of Python and FastAPI you can have a powerful text generation API that is self-documented! Automation is a foundational piece of MLOps, and using GitHub Actions to package a model automatically and on-demand with GitHub Actions you can create robust deployments and testing scenarios for machine learning operations. Learn Objectives In this video lesson, I'll go over the details with an example repository you can use for reference including the following learning objectives: Create a FastAPI application with HuggingFace Interact with the model with HTTP from a container using FastAPI Containerize the application using GitHub Actions Create repository secrets to login and push to GitHub Container Registry (ghcr.io) Resources Example repository Practical MLOps book MLOps Maturity Model Packaging ML models.
    Note: Online resource; title from title details screen (O'Reilly, viewed August 24, 2022)
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    [Place of publication not identified] : Pragmatic AI Solutions
    Language: English
    Pages: 1 online resource (1 video file (17 min.)) , sound, color.
    Edition: [First edition].
    DDC: 005.3
    Keywords: Application software Development ; Cloud computing ; Microsoft Azure (Computing platform) ; Instructional films ; Nonfiction films ; Internet videos
    Abstract: MLOps packaging: HuggingFace and Azure Container Registry Use automation to package models Learn how to package a HuggingFace GPT2 model for text generation using automation with MLOps and pushing the result to Azure Container Registry. With just a little bit of Python and FastAPI you can have a powerful text generation API that is self-documented! Learn Objectives In this video lesson, I'll go over the details with an example repository you can use for reference including the following learning objectives: Create a FastAPI application with HuggingFace Interact with the model with HTTP from a container using FastAPI Containerize the application using GitHub Actions Create repository secrets to login and push to Azure Container Registry Resources Example repository Practical MLOps book MLOps Maturity Model Packaging ML models.
    Note: Online resource; title from title details screen (O'Reilly, viewed July 6, 2022)
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    [Place of publication not identified] : Pragmatic AI Solutions
    Language: English
    Pages: 1 online resource (1 video file (48 min.)) , sound, color.
    Edition: [First edition].
    DDC: 004.67/82
    Keywords: Windows Azure ; Cloud computing ; Application software Development ; Instructional films ; Nonfiction films ; Internet videos
    Abstract: Deploy a containerized web app to Azure There are many services out there that allow you to deploy a container to the cloud. Although a straightforward operation, it is critical to understand how to create a robust automation deployment system. This course will create a Python Flask application from scratch, will containerize it, set the automation for it and then deploy it to Azure. This course lays out the foundations for creating more powerful containerized applications beyond the simple examples. You can add a Machine Learning model into the container and the end result would be the same: a robust deployment system that can get changes quickly onto Azure with any changes to the main branch. The continuous deployment system is a game changer as a skill set, making you a far more valuable engineer. In this video you will learn: Create a Python Flask application for containerization Use a Dockerfile to create the Flask container Use GitHub Actions to automatically deploy the container after a pull request or changes to the main branch Push your container to the GitHub container registry from the GitHub repository Create the web app on the Azure portal and connect it to GitHub Actions Host the containerized Python Flask application on Azure Debugging techniques for broken containers and other common errors like incorrect ports Useful Resources GitHub repository with sample code Free Azure Certification for Students Try Azure for Free AZ-900 Azure Fundamentals reference guide Azure SAMBA file share Azure Remote Compute for VSCode.
    Note: Online resource; title from title details screen (O'Reilly, viewed May 10, 2022)
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    [Place of publication not identified] : Pragmatic AI Solutions
    Language: English
    Pages: 1 online resource (1 video file (1 hr., 2 min.)) , sound, color
    Edition: [First edition].
    DDC: 005.13/3
    Keywords: Python (Computer program language) ; Python (Computer program language) ; Instructional films ; Internet videos ; Nonfiction films ; Instructional films ; Nonfiction films ; Internet videos
    Abstract: Python for Beginners Over 1 hour of course material with practice code Quickly learn learn the basics of Python In this course, you will learn how to undersetand Python fundamentals. This is an easy course for absolute beginners that will get you introduced to logic, variables, types, and data structures. This should be the first step when learning Python, and this course includes example repositories with interactive Jupyter Notebooks that you can use to practice yourself. All lessons and videos have accompanying GitHub Repositories with example code. Reference GitHub Repository Learn Objectives This course has extensive content that covers Python for beginners and then moves onto data structures including handling logic and applying it to sample problems. It will include the following learning objectives: Work with logic in Python Assign variables and use variables Use different data structures like lists and dictionaries Explore some other data structures like tuples and sets Add, modify, and extract data from data structures Resources Python Dictionaries course Pytest Master Class Python Bootcamp for Data Practical MLOps book.
    Note: Online resource; title from title details screen (O'Reilly, viewed August 23, 2022)
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    [Place of publication not identified] : Pragmatic AI Solutions
    Language: English
    Pages: 1 online resource (1 video file (1 hr., 1 min.)) , sound, color.
    Edition: [First edition].
    DDC: 005.13/3
    Keywords: Python (Computer program language) ; Numerical analysis Data processing ; Information visualization ; Information visualization ; Numerical analysis ; Data processing ; Python (Computer program language) ; Instructional films ; Internet videos ; Nonfiction films ; Instructional films ; Nonfiction films ; Internet videos
    Abstract: Intro to Pandas Over 1 hour of course material with practice code Quickly learn to use Pandas with examples Learn how to work with data using Pandas and NumPy. From loading and reading datasets from different sources to plotting graphs and exploring common problems in data. Pandas will allow you to perform transformations and export your data into different formats, and NumPy will boost your ability to work with numerical data. This course is meant for beginners that want to understand Pandas from the start and find more about NumPy. All lessons and videos have accompanying GitHub Repositories with example code. Reference GitHub Repository Learning Objectives In this course you will learn to: Load and export data from different sources Manipulate data in datasets Apply functions and transform columns Query for specific data Perform common operations on NumPy arrays Resources Python for beginners course Python Functions and Classes course Python Dictionaries course Introduction to Testing in Python course Pytest Master Class Python Bootcamp for Data Practical MLOps book.
    Note: Online resource; title from title details screen (O'Reilly, viewed August 23, 2022)
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    [Place of publication not identified] : Pragmatic AI Solutions
    Language: English
    Pages: 1 online resource (1 video file (1 hr., 1 min.)) , sound, color.
    Edition: [First edition].
    DDC: 005.13/3
    Keywords: Python (Computer program language) ; Python (Computer program language) ; Instructional films ; Internet videos ; Nonfiction films ; Instructional films ; Nonfiction films ; Internet videos
    Abstract: Python Functions and Classes Over 1 hour of course material with practice code Quickly learn learn the basics of Python functions and classes In this course, you will learn how to work with functions, classes and methods. These are the basis of almost any program you might create with Python. Functions and classes are useful for organizing code, increasing maintainability and code reuse. This course is perfect for beginners to Python that want to go beyond variables and logic and want to start working with object-oriented programming. This course includes example repositories with interactive Jupyter Notebooks that you can use to practice yourself. All lessons and videos have accompanying GitHub Repositories with example code. Reference GitHub Repository Learn Objectives This course includes the following learning objectives: In this week you will learn to: Create and work with functions. Build classes and methods. Require arguments or make them optional Use keyword arguments and use fallback values Resources Python Bootcamp for Data course Python for Beginners course Pytest Master Class Practical MLOps book.
    Note: Online resource; title from title details screen (O'Reilly, viewed August 23, 2022)
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    [Place of publication not identified] : Pragmatic AI Solutions
    Language: English
    Pages: 1 online resource (1 video file (2 hr., 5 min.)) , sound, color.
    Edition: [First edition].
    DDC: 005.13/3
    Keywords: Rust (Computer program language) ; Computer software Development ; Computer software ; Development ; Rust (Computer program language) ; Instructional films ; Internet videos ; Nonfiction films ; Instructional films ; Nonfiction films ; Internet videos
    Abstract: 52 Weeks of Rust Learning Rust by Live Coding This video series live codes Rust and iteratively learns the language. Lessons Covered Include: 1.0 52 weeks rust ep 1 getting started setup env 2.0 52 weeks rust ep 2 starting scripts 3.0 52 weeks rust ep 3 functions 4.0 52 weeks rust ep 4 loops 5.0 52 weeks rust ep 5 ownership more looping Learning Objectives Learn Rust by Live Coding Additional Popular Resources Pytest Master Class AWS Solutions Architect Professional Course Github Actions and GitOps in One Hour Video Course Jenkins CI/CD and Github in One Hour Video Course AWS Certified Cloud Practitioner Video Course Advanced Testing with Pytest Video Course AWS Solutions Architect Certification In ONE HOUR Python for DevOps Master Class 2022: CI/CD, Github Actions, Containers, and Microservices MLOPs Foundations: Chapter 2 Walkthrough of Practical MLOps Learn Docker containers in One Hour Video Course Introduction to MLOps Walkthrough AZ-900 (Azure Fundamentals) Quick reference guide 52 Weeks of AWS Episode 8: Infrastructure as Code with CDK and AWS Lambda Learn GCP Cloud Functions in One Hour Video Course Python Devops in TWO HOURS! MLOps Platforms From Zero: DatMLOps Platforms From Zero: Databricks, MLFlow/MLRun/SKLearn AWS Machine Learning Certification In ONE HOUR Fast, documented Machine Learning APIs with FastAPI Zero to One: AWS Lambda with SAM and Python in One Hour AWS Storage Solutions 2022: EBS/S3/EFS/Glacier Python Bootcamp for Data Testing In Python book Minimal Python book Practical MLOps book Python for DevOps-Playlist.
    Note: Online resource; title from title details screen (O'Reilly, viewed August 23, 2022)
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    [Place of publication not identified] : Pragmatic AI Solutions
    Language: English
    Pages: 1 online resource (1 video file (28 min.)) , sound, color.
    Edition: [First edition].
    DDC: 004.67/82
    Keywords: Microsoft Azure (Computing platform) ; Cloud computing ; Instructional films ; Nonfiction films ; Internet videos
    Abstract: Introduction to Azure Functions Create a function with Python and Flask Learn how to create an Azure Function in the fastest way using instant deployment with Visual Studio Code, and then find out how to take it to the next level by using the Flask framework to take advantage of common Python patterns you might already be used to. Finally, we'll go through automation steps using GitHub Actions so that you can re-deploy your Azure Function after merging changes. This will give you confidence for deployment, make it less error-prone, and give you a foundational workflow to implement serverless technology using the Azure cloud. Learning Objectives Create an Azure Function using the Azure Portal Quickly build a function using Visual Studio Code Deploy in one click with the Azure Functions extension Modify your code and routes to use Flask Use GitHub Actions for automating the deployment process About your instructor Alfredo Deza has over a decade of experience as a Software Engineer doing DevOps, automation, and scalable system architecture. Before getting into technology he participated in the 2004 Olympic Games and was the first-ever World Champion in High Jump representing Peru. He currently works in Developer Relations at Microsoft and is an Adjunct Professor at Duke University. This solid background in technology and teaching, including his experience creating courses with Codespaces is seen throughout this course, where you will get a first-hand experience with practical examples as well as applicable configuration for any development environment. Resources GitHub Codespaces course Microsoft Azure Fundamentals (AZ-900) Certification Pytest Master Class Practical MLOps book.
    Note: "Pragmatic AI Labs course.". - Online resource; title from title details screen (O'Reilly, viewed September 27, 2022)
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    [Place of publication not identified] : Pragmatic AI Solutions
    Language: English
    Pages: 1 online resource (1 video file (18 min.)) , sound, color.
    Edition: [First edition].
    DDC: 005.75/65
    Keywords: PostgreSQL ; Database management ; Instructional films ; Nonfiction films ; Internet videos
    Abstract: Azure PostgreSQL Setup and deploy an Azure PostgreSQL database Learn how to setup a PostgreSQL database using the Azure cloud. From the different options you have to create a PostgreSQL database (flexible or single server) to connection strings and firewall settings. This video will walk you through all you need to know to setup the resources, understand the constraints, and then correctly connect from a remote workstation using psql . Learning Objectives In this video you will learn to: Use the Azure Portal to create a PostgreSQL database Select between single and flexible server options Understand the constraints to create a database Setup firewall settings for external access Use psql to connect from a remote workstation to PostgreSQL Use the default database to connect Resources Azure Fundamentals Certification Azure Fundamentals quick reference guide Azure remote compute for VSCode Automated Azure resource cleanup Learn Azure ML (AutoML) in One hour.
    Note: Online resource; title from title details screen (O'Reilly, viewed December 12, 2022)
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    Language: English
    Pages: 1 online resource (1 video file, approximately 1 hr., 14 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Learn to use optimization strategies and greedy algorithms in one hour.
    Note: Online resource; Title from title screen (viewed March 7, 2021) , Mode of access: World Wide Web.
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    Language: English
    Pages: 1 online resource (1 video file, approximately 60 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Get started with Vim in this one-hour video. Everything you need to know to get up and running quickly. Topics include: * Opening, saving, and quiting files * Basic movements and operations, like copying and deleting * Updating the .vimrc configuration file for customization * Installing plugins and further customization
    Note: Online resource; Title from title screen (viewed January 8, 2021) , Mode of access: World Wide Web.
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    Language: English
    Pages: 1 online resource (1 video file, approximately 1 hr., 9 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Get started with Google Cloud Platform (GCP) and Cloud Functions in this one-hour video. Everything you need to know to get up and running quickly using serverless technology from GCP. Topics include: * An introduction to serverless technologies * Create a cloud function, install dependencies, and use different runtimes like Python 3.8 * Debug issues when a cloud function deployment fails * Use Google's Machine Learning offering to do live translations to any language * Enable authentication for your cloud function
    Note: Online resource; Title from title screen (viewed January 14, 2021) , Mode of access: World Wide Web.
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    Language: English
    Pages: 1 online resource (1 video file, approximately 6 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Learn to do GPU programming in Python in Five Minutes
    Note: Online resource; Title from title screen (viewed January 12, 2021) , Mode of access: World Wide Web.
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    Language: English
    Pages: 1 online resource (1 video file, approximately 34 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: AWS Solutions Architect Certification In ONE HOUR!
    Note: Online resource; Title from title screen (viewed January 14, 2021) , Mode of access: World Wide Web.
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    Language: English
    Pages: 1 online resource (1 video file, approximately 1 hr., 3 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Get started building powerful Command-line Tools with Python. From a single file with no dependencies to packaging and publishing your tool on the Python Package Index. Everything you need to know to get up and running quickly to create Python command-line tools. Topics include: * An introduction to Python scripts and Python packaging * Declare dependencies and package your script for installing and sharing. * Use argparse or upgrade to a more powerful framework like Click * Add flags, options and arguments to fine-tune and control your command-line tool
    Note: Online resource; Title from title screen (viewed January 22, 2021) , Mode of access: World Wide Web.
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    [Erscheinungsort nicht ermittelbar] : Pragmatic AI Solutions | Boston, MA : Safari
    Language: English
    Pages: 1 online resource (1 video file, approximately 56 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Get started with Docker and building powerful containers in this one-hour video. From the basics of containers, and its differences with virtual machines, to interactive commands and containerization of applications. Everything you need to know to get up and running quickly to use containers and grasp docker concepts. Topics include: * An introduction to containers and their differences with Virtual Machines * Start, stop, and manage containers. * Map container ports to local ports, mount volumes, and other startup flags for container images. * Get access to running containers to interactively debug a service like Nnginx. * Build a Python application with a Dockerfile, and deploy it running the latest Python version.
    Note: Online resource; Title from title screen (viewed January 28, 2021) , Mode of access: World Wide Web.
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    [Erscheinungsort nicht ermittelbar] : Pragmatic AI Solutions | Boston, MA : Safari
    Language: English
    Pages: 1 online resource (1 video file, approximately 54 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Learn to do Data Science with Python, Pandas and Colab Notebook in one hour! This video lesson takes you through a Covid-19 Dataset from the NyTimes and shows you how to explore it. The libraries involved include: Pandas, Colab, Plotly, sklearn, numpy and matplotlib. A suggested structure for Data Science projects is included: Ingest, EDA, Modeling and Conclusion. Finally, the course wraps up with how to integrate Cloud based business analytics including the following tools. AWS Cloud9, IPython, AWS Rekognition, AWS Translate and AWS Comprehend. These solutions are explored with both boto3 and the AWS Console. Follow along with the Github Resource: https://github.com/paiml/minimal-python/blob/master/Chapter7_data_science.ipynb
    Note: Online resource; Title from title screen (viewed February 6, 2021) , Mode of access: World Wide Web.
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    [Erscheinungsort nicht ermittelbar] : Pragmatic AI Solutions | Boston, MA : Safari
    Language: English
    Pages: 1 online resource (1 video file, approximately 1 hr., 44 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Python Devops in TWO HOURS!
    Note: Online resource; Title from title screen (viewed January 27, 2021) , Mode of access: World Wide Web.
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    [Erscheinungsort nicht ermittelbar] : Pragmatic AI Solutions | Boston, MA : Safari
    Language: English
    Pages: 1 online resource (1 video file, approximately 30 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: AWS Machine Learning Certification In ONE HOUR!
    Note: Online resource; Title from title screen (viewed January 23, 2021) , Mode of access: World Wide Web.
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    [Erscheinungsort nicht ermittelbar] : Pragmatic AI Solutions | Boston, MA : Safari
    Language: English
    Pages: 1 online resource (1 video file, approximately 20 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Learn to use AWS Elastic Beanstalk to deploy a Flask application. This tutorial covers Continuous Delivery of a Python Flask application using AWS Code Build. Elastic Beanstalk is a PAAS (Platform as a Service) that has powerful tools and integrations. This video course covers building out an development environment in Cloud9, a Makefile system and then finally, a full fledged CI/CD pipeline using Pylint and AWS Code Build of a Flask API. Follow along with the Github Resource: https://github.com/nogibjj/Flask-Elastic-Beanstalk.
    Note: Online resource; Title from title screen (viewed February 3, 2021) , Mode of access: World Wide Web.
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    [Erscheinungsort nicht ermittelbar] : Pragmatic AI Solutions | Boston, MA : Safari
    Language: English
    Pages: 1 online resource (1 video file, approximately 53 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Get started with Jenkins, Jenkins Pipelines, and Github integration in this introductory video to the most widely used CI/CD platform in the world: Jenkins. Learn how to setup an example repository from Github into Jenkins using the same techniques you would need to scale a massive CI CD production environment. Topics include: * Install and configure Jenkins including plugins like Blue Ocean that enables pipelines * Create a Personal Access Token (PAT) in Github to connect a repository to Jenkins * Setup a trigger to run automated tests for the Github repository using a Jenkinsfile * Add a remote node or slave to the Jenkins master instance via SSH to quickly scale up operations * Validate that the project builds and deploys correctly
    Note: Online resource; Title from title screen (viewed February 18, 2021) , Mode of access: World Wide Web.
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    [Erscheinungsort nicht ermittelbar] : Pragmatic AI Solutions | Boston, MA : Safari
    Language: English
    Pages: 1 online resource (1 video file, approximately 1 hr., 13 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Zero to One: Data Science to MLOps in One Hour. Learn to frame a problem, then convert it into a data science project and present it to stakeholders. Later, move that prediction system to producting using MLOps Topics include: * Big Tech Misinformation and what can be done about it using Data Science. * Doing MLOps with sklearn and Flask by creating Microservices * Using sklearn, pandas, plotly, matplotlib, KMeans clustering, ELI5, shap and other libraries * Putting code into production using the Python MLOps Cookbook found here: https://github.com/noahgift/data-story-telling
    Note: Online resource; Title from title screen (viewed March 20, 2021) , Mode of access: World Wide Web.
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    [Erscheinungsort nicht ermittelbar] : Pragmatic AI Solutions | Boston, MA : Safari
    Language: English
    Pages: 1 online resource (1 video file, approximately 45 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Enhance testing Python projects by adding Tox, a testing management tool that can easily create test matrices. In this video course, learn how to use different functional test strategies and expand basic unit testing by combining different software versions. Topics include: * Use Pytest for fast verification of unit tests * Detect missing dependencies that can get packaged and released even when tests are passing * Build a test matrix by adding factors and combinatorial versions by leveraging Tox to avoid boilerplate configuration * Use different Python versions to test the same code
    Note: Online resource; Title from title screen (viewed March 18, 2021) , Mode of access: World Wide Web.
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    Language: English
    Pages: 1 online resource (1 video file, approximately 56 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Learn all about distributed tracing in this 1 hour course. If you want to go beyond logging and monitoring, and trying to tell a story by connecting the dots, then distributed tracing is the way to go. Topics include: * Opentracing and the foundations of distributed tracing libraries like Jaeger * Micro-service strategies and other microservice implementations that make distributed-tracing a perfect use case * Implement distributed tracing instrumentation in a Github project using docker compose with multiple Docker containers * Leverage the knowledge to use hosted services like Datadog for querying and debugging traces
    Note: Online resource; Title from title screen (viewed April 15, 2021) , Mode of access: World Wide Web.
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    [Erscheinungsort nicht ermittelbar] : Pragmatic AI Solutions | Boston, MA : Safari
    Language: English
    Pages: 1 online resource (1 video file, approximately 26 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Learn to debug Python code quickly! Topics include: * Continuous Integration * Python Debugger: PDB * Debugging with print statements * Debugging with IPython * Using pylint and pytest to debug code
    Note: Online resource; Title from title screen (viewed April 14, 2021) , Mode of access: World Wide Web.
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    [Erscheinungsort nicht ermittelbar] : Pragmatic AI Solutions | Boston, MA : Safari
    Language: English
    Pages: 1 online resource (1 video file, approximately 21 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Learn to build Machine Learning solutions without writing any code with CreateML from Apple. Topics include: * Computer Vision * Image Classification * OS X * Apple * Core ML
    Note: Online resource; Title from title screen (viewed April 22, 2021) , Mode of access: World Wide Web.
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    [Erscheinungsort nicht ermittelbar] : Pragmatic AI Solutions | Boston, MA : Safari
    Language: English
    Pages: 1 online resource (1 video file, approximately 44 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Python exceptions are exceptional at helping your program take decisions. It is natural to feel the urge to catch them all and ignore them. But powerful programs can be created by learning how to leverage them in order to make robust scripts and take your coding skills to the next level. In this video, I cover several techniques that will help you improve your exception handling. Topics include: * Create a script that uses exception poorly, and then improve it * Slowly clean up broad catching exceptions to improve the script * Learn how to produce better errors from exceptions * Leverage other tools like logging to produce meaningful errors and tracebacks while keeping messages clean Follow along the repository to continue using more examples: https://github.com/alfredodeza/exceptions/
    Note: Online resource; Title from title screen (viewed April 22, 2021) , Mode of access: World Wide Web.
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    [Erscheinungsort nicht ermittelbar] : Pragmatic AI Solutions | Boston, MA : Safari
    Language: English
    Pages: 1 online resource (1 video file, approximately 60 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Sometimes scraping is the only way to extract meaningful data when there are no options like an accessible API. Parsing raw HTML can be intimidating and full of failures if you aren't used to existing tooling that can help you parse faster and more efficiently. In this video, learn all the basics including some advanced techniques to parse HTML and extract data with the Scrapy library in Python. k Topics include: * Install, configure, and create a new project with Scrapy, a powerful scraping library written in Python * See what is required to start parsing a website, including looking at raw HTML, tags, and CSS. * Identify data to create a dataset or datasets to perform data science analysis later * Capture parsed data and save it in different formats locally * Ultra fast scraping techniques by using the filesystem directly A few resources that are helpful if you are trying to do scraping, some of them covered in the course: * Scrapy Library * Scrapy Getting started tutorial
    Note: Online resource; Title from title screen (viewed May 13, 2021) , Mode of access: World Wide Web.
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    Language: English
    Pages: 1 online resource (1 video file, approximately 22 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Learn to use Google AutoML Vision to train models with out writing code. Topics include: * Google AutoML Vision with Corel.AI * Core ML * Tensorflow Lite * Edge Inference * MLOps for Edge Computer Vision
    Note: Online resource; Title from title screen (viewed April 27, 2021) , Mode of access: World Wide Web.
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    [Erscheinungsort nicht ermittelbar] : Pragmatic AI Solutions | Boston, MA : Safari
    Language: English
    Pages: 1 online resource (1 video file, approximately 1 hr., 18 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Learn to use Google AutoML to build a computer vision prediction model via their Qwiklabs website. Later, compare Apple's CreateML with the same data set and build an AutoML prediction model that deploy to the edge. Topics include: * Google AutoML * Apple CreateML * Apple CoreML * Computer Vision * Cloud Computing * Single label image classification * Using AutoML as a prototyping Tool * Edge Computer Vision Models
    Note: Online resource; Title from title screen (viewed May 15, 2021) , Mode of access: World Wide Web.
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    Language: English
    Pages: 1 online resource (1 video file, approximately 1 hr., 23 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Learn to use the AWS (Amazon Web Services) platfrom to perform Computer Vision with the Python Language. This video course takes you from zero and introduces you to using the AWS Rekognition Console, AWS Cloud Shell and AWS Cloud9 environment to build computer vision solutions. Topics include: * Using AWS Rekognition to do Celebrity Recognition, Text Detection, PPE Detection and Image Labeling * Setting up AWS Cloud Shell to use the AWS SDK * Doing S3 copies with the AWS command-line SDK * Setting up AWS Cloud9 for development * Configuring bashrc file for use with Python * Using IPython with the AWS Boto3 SDK * Using Python Click to create command-line tools with colorized output * Using Github Actions to test and lint a computer vision project
    Note: Online resource; Title from title screen (viewed May 9, 2021) , Mode of access: World Wide Web.
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    [Erscheinungsort nicht ermittelbar] : Pragmatic AI Solutions | Boston, MA : Safari
    Language: English
    Pages: 1 online resource (1 video file, approximately 36 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Learn to use MLOPs methodology to build applied computer vision solutions. Topics include: * Apple CreateML * AutoML * Image Classification * Kaizen * Computer Vision
    Note: Online resource; Title from title screen (viewed April 30, 2021) , Mode of access: World Wide Web.
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    Language: English
    Pages: 1 online resource (1 video file, approximately 32 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: What is an SBOM (Software Bill Of Materials) and why should you care? An SBOM is a critical cybersecurity component to keep track and catalog what is installed (and at what versions) in production environments. With recent cybersecurity threats, SBOMs play an important role to implement a remediation strategy when threats and vulnerabilities are reported. Without an SBOM, it is borderline impossible to detect what exactly is released into production, and what may be vulnerable today. Topics include: * Understand the concepts behind an SBOM * Create an SBOM and use different output formats like CycloneDX to import into other systems * Use an SBOM to detect CVE and other vulnerabilities associated with installed software * Capture information about pre-installed system dependencies and nested dependencies * Use CycloneDX and other machine-readable formats like JSON to import outputs into other systems A few resources that are helpful if you are trying to get started with SBOMs, generating them and using them to capture vulnerabilities: * A simple, user-friendly SBOM generator: Syft * A fast vulnerability matcher that uses SBOMs as input: Grype * The CycloneDX format
    Note: Online resource; Title from title screen (viewed May 18, 2021) , Mode of access: World Wide Web.
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    Language: English
    Pages: 1 online resource (1 video file, approximately 40 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Use FastAPI to expose an HTTP API for fast live predictions using an ONNX Machine Learning Model. FastAPI is a Python web framework that provides easy development of documented HTTP APIs by offering self-documented endpoints with Swagger - a tool to describe, document, and use RESTful web services. Learn how to quickly put together an API which validates requests, and self-documents its endpoints using OpenAPI via Swagger. Quickly produce a robust interface for others to consume your Machine Learning model by following core best-practices of MLOps. Parts of this video cover the basics of packaging Machine Learning models, as covered in the Practical MLOps book. Topics include: * Create a Python project to serve live predictions using FastAPI * Use a Dockerfile to package the model and the API using Docker containerization * With minimal Python code, expose an ONNX model to perform sentiment analysis over an HTTP endpoint * Dynamically interact with the API using the self-documented endpoint in the container. Useful links: * Demo Github Repository with sample code * Practical MLOps book * FastAPI Intro tutorial * RoBERTa ONNX Model for sentiment analysis
    Note: Online resource; Title from title screen (viewed July 16, 2021) , Mode of access: World Wide Web.
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    Language: English
    Pages: 1 online resource (1 video file, approximately 36 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Apply DevOps principles to Jenkins by automating tasks using the Jenkins API with Python. Create a powerful command-line tool with the Click framework to harness the API and trigger remote jobs with a simple invocation. Using code (and Python in this case) to automate frequent tasks is an import DevOps principle that you should apply whenever possible. Some of the concepts in this video are covered in the Python For DevOps book. Learn how to identify core concepts when trying to automate something like Jenkins, like identifying the API access, authorization, and the possibility of finding a helper library to make things easier. your Machine Learning model by following core best-practices of MLOps. Topics include: * Setup a main Jenkins instance with Docker, using the official Jenkins LTS image. * Create a user with an API token, so that it is authorized to operate Jenkins. * Use a Jupyter notebook to try out the API using Python and figure out concepts that can be applied later * Create a command-line tool using the Click framework to quickly trigger Jenkins jobs. Useful links: * Jenkins LTS Docker image documentation * Official Jenkins LTS Docker image * Python-Jenkins library documentation * Python-Jenkins Library * Python for DevOps Book
    Note: Online resource; Title from title screen (viewed August 2, 2021) , Mode of access: World Wide Web.
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    Language: English
    Pages: 1 online resource (1 video file, approximately 1 hr., 27 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Learn the foundations of MLOPs Topics include: * Linux and Bash * AWS Cloud9 and AWS Cloud Shell and other Cloud Topics * The intuition behind MLOps techniques: optimization, gradient descent and data science.
    Note: Online resource; Title from title screen (viewed August 7, 2021) , Mode of access: World Wide Web.
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    Language: English
    Pages: 1 online resource (1 video file, approximately 25 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Topics include: * Solar * Tesla * Nest * Smart Home * Time of Use * Net metering * Battery Backup * EV (electric vehicle) * Artificial Intelligence * Level 1 Charging * Level 2 Charging * Level 3 Charging
    Note: Online resource; Title from title screen (viewed July 25, 2021) , Mode of access: World Wide Web.
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    Language: English
    Pages: 1 online resource (1 video file, approximately 27 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Packaging in Python has always been polarizing. From complicated beginnings where you couldn't uninstall libraries, to virtualenv that allows you to work in a self-contained environment that can be thrown away. In this video, I'll present an introduction to Conda, and to a chanel-specific variation of it that is maintained by the community called miniforge. If you are looking for a way to get scientific packages for the new Apple M1 silicon, this video will also help you out get everything sorted, including installing versions of Python that are pre-packaged and ready for data science tasks. Topics include: * Install Conda by using the community version called miniforge. * Use conda to install a specific version of Python, without system installs * Find more about the differences between virtualenv, pip, and conda * Install data science libraries in the new Apple M1 silicon Useful links: * Conda documentation * Conda Forge community documentation * Conda miniforge project
    Note: Online resource; Title from title screen (viewed August 18, 2021) , Mode of access: World Wide Web.
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    Language: English
    Pages: 1 online resource (1 video file, approximately 16 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local ; Electronic videos
    Abstract: It is essential to have a strategy defined when figuring out your career. Starting out is difficult. Regardless what your background is, you need to have a clear idea how to get to your dream job. Even if you are not in technology and want a data-science position, you have to have a clear path towards data-science. In this video I'll cover some of the stories that allowed me to gain perspective in my career in tech, along with some advice that can help you out. Topics include: * Find some techniques to define your career and next steps * Design a custom strategy to help answer career questions * Accurately determine what might be a good job or position Useful links: * Start a career in Tech * Learn Python from scratch
    Note: Online resource; Title from title screen (viewed September 13, 2021) , Mode of access: World Wide Web.
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    Language: English
    Pages: 1 online resource (1 video file, approximately 15 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Use AWS Step Functions to solve problems
    Note: Online resource; Title from title screen (viewed September 12, 2021) , Mode of access: World Wide Web.
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    Language: English
    Pages: 1 online resource (1 video file, approximately 1 hr., 26 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Learn to use optimization techninques along with AWS Step Functions
    Note: Online resource; Title from title screen (viewed September 12, 2021) , Mode of access: World Wide Web.
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    Language: English
    Pages: 1 online resource (1 video file, approximately 2 hr., 30 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Learn about six key elements of MLOPs based on the best-selling book Practical MLOps Topics include: * Source Code Management * Continuous Integration and Continuous Delivery * Development Environment * Deploy Environment * Microservices including Flask and FastAPI * Business Logic
    Note: Online resource; Title from title screen (viewed September 2, 2021) , Mode of access: World Wide Web.
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    Language: English
    Pages: 1 online resource (1 video file, approximately 43 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Learn to ruthlessly scrape data using APIs you discover as well as cut and paste. Topics include: * Business Analytics * Data Science * Google Colab * Jupyter * Scraping * Cut and Paste * Google Sheets * Cleaning Data * Using Pandas with found data * Using the Twitter and Pandas API
    Note: Online resource; Title from title screen (viewed September 4, 2021) , Mode of access: World Wide Web.
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    Language: English
    Pages: 1 online resource (1 video file, approximately 1 hr., 32 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: A walkthrough of Chapter 7 of the O'Reilly book Practical MLOps. Learn about real-world computer vision including a recap of Tesla AI day 2021. Topics include: * Getting models into production * Tesla FSD * Tesla Computer Vision * Tesla AI Day * DataOps * ML Platforms * Sagemaker * Continuous Integration and Continuous Deployment * MLOps cookbook * ML Engineering * Data Engineering * AWS App runner * GCP * Azure * Containers * Kaizen
    Note: Online resource; Title from title screen (viewed August 24, 2021) , Mode of access: World Wide Web.
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    Language: English
    Pages: 1 online resource (1 video file, approximately 2 hr., 30 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Learn to master key components of Python functions. Topics include: * Input, Output and Unit of Work * Decorators, Yield Statements, Generators, Closures and Nested Functions * Using Github Codespaces and Github Actions * Building Command-line tools * Microservices including Flask and FastAPI * Using AWS Cloud9 along side AWS App Runner
    Note: Online resource; Title from title screen (viewed September 3, 2021) , Mode of access: World Wide Web.
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    Language: English
    Pages: 1 online resource (1 video file, approximately 4 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Learn the foundations of Agile Project Management in this quick video snippit featuring global technical project management expert Jerry Castro. Topics include: * Agile * Balancing chaos vs order * How to get started with Agile
    Note: Online resource; Title from title screen (viewed August 25, 2021) , Mode of access: World Wide Web.
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    Language: English
    Pages: 1 online resource (1 video file, approximately 59 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Learn to build Computer Vision MVPs quickly using AutoML. Topics include: * Getting models into production * Apple Create ML * Google Vertex AI * Image Classification * CoreML * Tensorflow * Rapid Prototyping * GCP * Azure * Containers * Kaizen
    Note: Online resource; Title from title screen (viewed August 28, 2021) , Mode of access: World Wide Web.
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    Language: English
    Pages: 1 online resource (1 video file, approximately 1 hr., 11 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Learn to get started on the right setup on your first day as a data scientist or business analytics professional. Topics include: * Business Analytics * Data Science * Google Colab * Jupyter * Github Actions and Github Codespaces * Continuous Integration and Delivery * EDA * GCP * AWS * Azure
    Note: Online resource; Title from title screen (viewed August 28, 2021) , Mode of access: World Wide Web.
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    Language: English
    Pages: 1 online resource (1 video file, approximately 1 hr., 23 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: A walkthrough of Chapter 5 of the O'Reilly book Practical MLOps. Topics include: * Getting models into production * Feature Store vs Data Warehouse * AutoML * MLOps * DataOps * ML Platforms * Sagemaker * Continuous Integration and Continuous Deployment * MLOps cookbook * ML Engineering * Data Engineering * Spark * GCP * Azure * Containers * Kaizen
    Note: Online resource; Title from title screen (viewed August 14, 2021) , Mode of access: World Wide Web.
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    Language: English
    Pages: 1 online resource (1 video file, approximately 1 hr., 2 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Get started with Github and Github Actions in this introductory video to GitOps concepts, by building a container, setting some Github Actions to prevent problems, and finally, push to DockerHub in a fully automated way. These concepts are critical to get automation best-practices in place with Github. Particularly useful when collaborating with others and trying to run automated checks on Dockerfiles and git repos. Topics include: * Create a new Github repository * Enable Github Actions checks and steps for a new repository. * Find a Github Action to lint and check a Dockerfile to prevent issues before merging on pull requests. * Add Github Secrets and reuse them in a Github Action * Validate that a container builds correctly, and automatically push to dockerhub
    Note: Online resource; Title from title screen (viewed February 12, 2021) , Mode of access: World Wide Web.
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    Language: English
    Pages: 1 online resource (1 video file, approximately 44 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Zero to One: AWS Lambda with SAM and Python in One Hour. Learn to use AWS Cloud9 to develop serverless applications with Python and SAM (Serverless Application Model) Topics include: * Building a Lambda inside of Cloud9 * Deploying a containerized service to Amazon ECR and AWS Lambda * Invoking API Gateway based AWS Lambda services using sam invoke and AWS Cloud9
    Note: Online resource; Title from title screen (viewed April 3, 2021) , Mode of access: World Wide Web.
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    Language: English
    Pages: 1 online resource (1 video file, approximately 15 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Learn some counter-intuitive ways to think about programming as a beginner. It is ok to feel stupid, it means you are on the right path! Topics include: * Failure is good * The goal of programming is to reduce complexity * Automation is a requirement * Continuously Improve your code * Embrace Automation and Monitoring
    Note: Online resource; Title from title screen (viewed April 17, 2021) , Mode of access: World Wide Web.
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    Language: English
    Pages: 1 online resource (1 video file, approximately 14 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: How are you generating revenue in your business or career. This lesson talks about consulting, salary and MRR including investing. Topics include: * Consulting * Salary * Investments * Autonomy vs Dependency * MRR (Monthly Recurring Revenue)
    Note: Online resource; Title from title screen (viewed April 22, 2021) , Mode of access: World Wide Web.
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    Language: English
    Pages: 1 online resource (1 video file, approximately 39 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Learn the essentials of Bash for Cloud Computing Topics include: * AWS Cloud Shell and Github Code Spaces Shell programming * Editing Bashrc * Using Vim * Using shell navigation including: cd, ls, pwd, history * editing the Bash prompt and creating simple Bash Scripts, as well as Python Virtual Environments with Bash
    Note: Online resource; Title from title screen (viewed May 6, 2021) , Mode of access: World Wide Web.
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    Language: English
    Pages: 1 online resource (1 video file, approximately 14 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Learn to think like a Venture Capitalist about your career and design for failure. Topics include: * Cost of Living * Open Source Software * Investments * Designing your 1-3 year experiences * Being proactive vs reactive
    Note: Online resource; Title from title screen (viewed April 28, 2021) , Mode of access: World Wide Web.
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    Language: English
    Pages: 1 online resource (1 video file, approximately 54 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Get started with security vulnerability scanning and integrating that with Github, Github Actions and automated security checks in pull requests. Learn how to scan reported vulnerabilities in projects and Docker containers, so that you can publish images to Docker hub or merge pull requests while knowing that changes in dependencies are secure. Topics include: * Install and run locally a security vulnerability scanner * Catalog a project with an SBOM (Software Bill Of Materials) so that the scanner can do vulnerability matching. * Setup a Github Action to automatically scan vulnerabilities in a project and optionally fail a build to prevent a merge. * Scan a Docker container image that is built locally against the latest vulnerabilities, based on any CVE reported publicly
    Note: Online resource; Title from title screen (viewed February 25, 2021) , Mode of access: World Wide Web.
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    Language: English
    Pages: 1 online resource (1 video file, approximately 1 hr., 6 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Get started with MLOps and Github Actions to package a container with an ONNX model that does live inferencing with a Flask application. By using Azure ML, learn how to download the large ONNX model into the Github Action workflow, package it as a container and then push it to a container registry. For reference use the https://github.com/alfredodeza/flask-roberta repository Topics include: * Create a container that does live inferencing with Flask and the ONNX runtime * Package the model and verify it works locally * Setup a Github Action to authenticate to Azure ML and download a previously registered model * Build the new container as a Github Action, authenticate to Docker Hub or Github Packages * Push the new container to the Github registry or any other registry like Docker Hub
    Note: Online resource; Title from title screen (viewed March 5, 2021) , Mode of access: World Wide Web.
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    Language: English
    Pages: 1 online resource (1 video file, approximately 47 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Distribute the load of Jenkins builds with a remote Docker instance or Kubernetes server in this 1-hour long tutorial Topics include: * Configure a remote Docker instance to interact with the master Jenkins server * Modify an existing job to use Docker to do builds using labels * Setup a remote kubernetes instance to connect to Jenkins with JNLP * Use the right container image to connect back to Jenkins as a remote container node
    Note: Online resource; Title from title screen (viewed March 12, 2021) , Mode of access: World Wide Web.
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    Language: English
    Pages: 1 online resource (1 video file, approximately 1 hr., 14 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: In this video you walk through the foundational concepts of Machine Learning.
    Note: Online resource; Title from title screen (viewed February 27, 2021) , Mode of access: World Wide Web.
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    Language: English
    Pages: 1 online resource (1 video file, approximately 1 hr., 15 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Learn to use no-code and low-code solutions to perform Natural Processing. In this video you walk through building a text based analysis using Python and Cloud Tools. You learn how to perform document similarity, visualize word clouds and use Amazon AI Tools. The techniques covered include: * Google Colab * Spacy * AWS Quicksite * AWS Comprehend * AWS Rekognition * NLTK * WordCloud * Pandas * Plotly * Github Finally, the course analyzes Hemingway books using popular off the shelf Python libraries. Follow along with the Github Resource: https://github.com/noahgift/exploratory-data-analysis
    Note: Online resource; Title from title screen (viewed February 20, 2021) , Mode of access: World Wide Web.
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    Language: English
    Pages: 1 online resource (1 video file, approximately 37 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: One of the important aspects of MLOps, also known as Machine Learning Operations or Operationalizing Machine learning, is to package ML models. How exactly do you package ML models? In this video I show you exactly what that means, and go through the process of packaging an ONNX model taken from the ONNX Model Zoo. I end up with a docker container that can be shared, exposing an API that is ready to consume and perform live predictions for sentiment analysis. Topics include: * What are the concepts behind packaging Machine Learning Models * Create a sentiment analysis API tool with Flask * Define dependencies and a Dockerfile for packaging * Create a container with an ONNX model that can be deployed anywhere with an HTTP API A few resources that are helpful if you are trying to get started with SBOMs, generating them and using them to capture vulnerabilities: * The RoBERTa ONNX Model * Schema labeling concetps for Docker containers * The Practical MLOps code respository full of examples
    Note: Online resource; Title from title screen (viewed May 27, 2021) , Mode of access: World Wide Web.
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    Language: English
    Pages: 1 online resource (1 video file, approximately 46 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: A walkthrough of Chapter 1 of the O'Reilly book Practical MLOps. Topics include: * DevOps * MLOps * DataOps * ML Platforms * Sagemaker * Continuous Integration and Continuous Deployment * MLOps cookbook * ML Engineering * Data Engineering * Spark * GCP * Azure * Containers * Kaizen
    Note: Online resource; Title from title screen (viewed July 31, 2021) , Mode of access: World Wide Web.
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    Language: English
    Pages: 1 online resource (1 video file, approximately 35 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Learn how to use AWS in one Hour
    Note: Online resource; Title from title screen (viewed January 9, 2021) , Mode of access: World Wide Web.
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    Language: English
    Pages: 1 online resource (1 video file, approximately 1 hr., 3 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Get started with Machine Learning and Auto ML using Azure ML Studio easily building powerful models and deploy them in a scalable environment. Everything you need to know to get up and running quickly in Machine Learning using Azure, from datasets to containerized deployments and data validation. Topics include: * An introduction to Azure ML Studio and AutoML * Import datasets and version them within Azure - even from remote locations like Github * Create compute clusters for training and live inferencing * Select models for deployment into Kubernetes or Docker Container instances * Practice MLOps, operationalizing a deployed model with logs and metrics via Application Insights * Consume a live endpoint with a deployed model over an HTTP API * Use the generated Swagger files to grasp the HTTP endpoints
    Note: Online resource; Title from title screen (viewed February 4, 2021) , Mode of access: World Wide Web.
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    Language: English
    Pages: 1 online resource (1 video file, approximately 19 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Learn to use containers to build Microservices on the AWS platform. In this video you walk through building a Flask Microservice using the following AWS tools: * AWS Cloud9 * AWS ECR (Elastic Container Registery) * AWS ECS (AWS Container Service) * AWS Fargate (Container as a Service) Finally, the course builds and deploys a Fargate container that was provisioned to ECR. Follow along with the Github Resource: https://github.com/noahgift/eks-fargate-tutorial
    Note: Online resource; Title from title screen (viewed February 18, 2021) , Mode of access: World Wide Web.
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    Language: English
    Pages: 1 online resource (1 video file, approximately 1 hr., 16 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Learn to tell stories with Data and then present those conclusions to Business Executives. Learn to use Colab/Jupyter Notebooks to build Data Science notebooks that tell a story. Topics include: * Effects of Intermittent Fasting, Sugar, Wealth and Real Estate Values on society * Visualizing data through Plotly graphs with 3D Interactive Visualizations of KMeans clustering * Using sklearn, pandas, plotly, matplotlib, KMeans clustering, ELI5, shap and other libraries * The role of the Matthew Effect on society. The Github Project is here: https://github.com/noahgift/data-story-telling
    Note: Online resource; Title from title screen (viewed March 13, 2021) , Mode of access: World Wide Web.
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    Language: English
    Pages: 1 online resource (1 video file, approximately 59 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: The Go programming language is becoming more popular these days with cloud-native applications and the Kubernetes ecosystem. If you are coming from Python, you will find yourself surprised to see similar patterns, while at the same time see some things that are missing or plain impossible with Go. In this course, I will introduce you to some of the basics of Golang from a Python perspective, so that you can reduce the friction trying to learn it. Topics include: * Packages, imports and variable definitions * From lists to arrays and slices * From Python dictionaries to Go maps * Looping on data structures, retrieving and adding values or items * Error handling, and the surprising fact that there aren't any tracebacks or exceptions in Go A few resources that are helpful if you are trying to learn Go, some of them covered in the course: * Visual Studio Code for Go * The Go playground * An (interactive) tour of Go
    Note: Online resource; Title from title screen (viewed May 5, 2021) , Mode of access: World Wide Web.
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    Language: English
    Pages: 1 online resource (1 video file, approximately 24 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Learn to use AWS App Runner to do an MLOps workflow that deploys a Flask Microservice that running sklearn. This tutorial walks you through how to deploy code from the O'Reilly book Practical MLOps using the AWS App Runner Service. Topics include: * MLOps * AWS App Runner * Container as a Service * Python * Flask * Microservice * Sklearn * Machine Learning Engineering
    Note: Online resource; Title from title screen (viewed May 23, 2021) , Mode of access: World Wide Web.
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    Language: English
    Pages: 1 online resource (1 video file, approximately 37 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Learn to pass ANY AWS Certification Exam on the first try. Topics include: * AWS Certifications * AWS Certified Cloud Practitioner * AWS Exam Guide * AWS White Papers * AWS Sample Questions * AWS Cloud Shell * AWS Unofficial Questions * AWS Academy
    Note: Online resource; Title from title screen (viewed June 6, 2021) , Mode of access: World Wide Web.
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  • 97
    Online Resource
    Online Resource
    [Erscheinungsort nicht ermittelbar] : Pragmatic AI Solutions | Boston, MA : Safari
    Language: English
    Pages: 1 online resource (1 video file, approximately 37 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Learn to AWS Sagemaker Autopilot from zero and deploy a model to production.
    Note: Online resource; Title from title screen (viewed June 29, 2021) , Mode of access: World Wide Web.
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  • 98
    Online Resource
    Online Resource
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Language: English
    Pages: 1 online resource (1 video file, approximately 11 hr., 5 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local ; Audiobooks ; local
    Abstract: As the digital economy changes the rules of the game for enterprises, the role of software and IT architects is also transforming. Rather than focus on technical decisions alone, architects and senior technologists need to combine organizational and technical knowledge to effect change in their company's structure and processes. To accomplish that, they need to connect the IT engine room to the penthouse, where the business strategy is defined. In this guide, author Gregor Hohpe shares real-world advice and hard-learned lessons from actual IT transformations. His anecdotes help architects, senior developers, and other IT professionals prepare for a more complex but rewarding role in the enterprise. This book is ideal for: Software architects and senior developers looking to shape the company's technology direction or assist in an organizational transformation Enterprise architects and senior technologists searching for practical advice on how to navigate technical and organizational topics CTOs and senior technical architects who are devising an IT strategy that impacts the way the organization works IT managers who want to learn what's worked and what hasn't in large-scale transformation
    Note: Online resource; Title from title screen (viewed August 25, 2020) , Mode of access: World Wide Web.
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  • 99
    Online Resource
    Online Resource
    [Erscheinungsort nicht ermittelbar] : Packt Publishing | Boston, MA : Safari
    ISBN: 9781800208797
    Language: English
    Pages: 1 online resource (1 video file, approximately 4 hr., 22 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: UX Process for Beginners from User Interviews to Personas, User stories, Information architecture to Usability testing About This Video Define product scope and feature matrix Understand how to drive user and stakeholder interviews Master UX Process in a simplified way In Detail There are hundreds of elements involved in a UX Design process and each design firm uses its own version of the implementation. It, therefore, leads to confusion among the beginners about where to start the user experience process. This project-based course starts off by introducing to you the project that you will be working on throughout the course and understand the concepts as you progress. Your target will be to create and improve the user experience of an e-commerce startup called Frankland. You will learn to determine the starting point among the pool of different aspects to be covered including user interviews, personas, customer journey maps, and defining the scope of the product. By the end of this course, you'll have understood the complete UX process and its significance in the website and mobile app development.
    Note: Online resource; Title from title screen (viewed January 31, 2020) , Mode of access: World Wide Web.
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  • 100
    Online Resource
    Online Resource
    [Erscheinungsort nicht ermittelbar] : Packt Publishing | Boston, MA : Safari
    ISBN: 9781839219238
    Language: English
    Pages: 1 online resource (1 video file, approximately 5 hr., 47 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Unlock your coding potential by solving real-world Python exercises. About This Video Solve a variety of real-world programming and logical problems by leveraging the power of Python Improve your skills in using language features, algorithms, data structures, design patterns, and more Expand your development skills by gaining hands-on experience in data analysis, visualisation, web scraping and more In Detail Python is one of the most popular and widely used programming languages in a variety of fields such as data science, analysis, gaming, GUI programming, Networking, and more. Are you someone who loves challenges and gets excited about solving them? If you've been using Python for some time and would like to test how good a Python wrangler you are, you've come to the right place! In this course, you will uncover key Python features and implement them while testing your own ability to solve particular challenges. Each unique problem will not only test your knowledge of the language, but also your ability to think outside of the box and come up with the best solutions. Our course is divided into levels to help you go from being a beginner to professional level "Pythonista"! And in case you're stumped, you don't have to worry: we'll show you the best solutions to the challenges laid out in the course. By the end of this course, you will become a confident "Python Pro", ready to take up any challenge and solve it with your mastery. So, are you up for the challenge?
    Note: Online resource; Title from title screen (viewed May 26, 2020) , Mode of access: World Wide Web.
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