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1

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MATLAB for machine learning (2024)

Ciaburro, Giuseppe [VerfasserIn]

Birmingham, UK : Packt Publishing

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Details

ISBN: 9781835087695

Sprache: Englisch

Seiten: 1 online resource (374 pages) , illustrations

Ausgabe: Second edition.

DDC: 518.0285/536

Schlagwort(e): MATLAB ; Machine learning ; Computer programming

Kurzfassung: Master MATLAB tools for creating machine learning applications through effective code writing, guided by practical examples showcasing the versatility of machine learning in real-world applications Key Features Work with the MATLAB Machine Learning Toolbox to implement a variety of machine learning algorithms Evaluate, deploy, and operationalize your custom models, incorporating bias detection and pipeline monitoring Uncover effective approaches to deep learning for computer vision, time series analysis, and forecasting Purchase of the print or Kindle book includes a free PDF eBook Book Description Discover why the MATLAB programming environment is highly favored by researchers and math experts for machine learning with this guide which is designed to enhance your proficiency in both machine learning and deep learning using MATLAB, paving the way for advanced applications. By navigating the versatile machine learning tools in the MATLAB environment, you'll learn how to seamlessly interact with the workspace. You'll then move on to data cleansing, data mining, and analyzing various types of data in machine learning, and visualize data values on a graph. As you progress, you'll explore various classification and regression techniques, skillfully applying them with MATLAB functions. This book teaches you the essentials of neural networks, guiding you through data fitting, pattern recognition, and cluster analysis. You'll also explore feature selection and extraction techniques for performance improvement through dimensionality reduction. Finally, you'll leverage MATLAB tools for deep learning and managing convolutional neural networks. By the end of the book, you'll be able to put it all together by applying major machine learning algorithms in real-world scenarios. What you will learn Discover different ways to transform data into valuable insights Explore the different types of regression techniques Grasp the basics of classification through Naive Bayes and decision trees Use clustering to group data based on similarity measures Perform data fitting, pattern recognition, and cluster analysis Implement feature selection and extraction for dimensionality reduction Harness MATLAB tools for deep learning exploration Who this book is for This book is for ML engineers, data scientists, DL engineers, and CV/NLP engineers who want to use MATLAB for machine learning and deep learning. A fundamental understanding of programming concepts is necessary to get started.

Anmerkung: Includes index

URL: lizenzpflichtig

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MPI Ethno. Forsch.

2

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Python machine learning cookbook : over 100 recipes to progress from smart data analytics to deep learning using real-world datasets (2019)

Ciaburro, Giuseppe [VerfasserIn] ; Joshi, Prateek [MitwirkendeR]

Birmingham, UK : Packt Publishing

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Details

ISBN: 9781789800753 , 1789800757

Sprache: Englisch

Seiten: 1 online resource (1 volume) , illustrations

Ausgabe: Second edition.

Schlagwort(e): Python (Computer program language) ; Machine learning ; Electronic books ; Electronic books ; local

Kurzfassung: Discover powerful ways to effectively solve real-world machine learning problems using key libraries including scikit-learn, TensorFlow, and PyTorch Key Features Learn and implement machine learning algorithms in a variety of real-life scenarios Cover a range of tasks catering to supervised, unsupervised and reinforcement learning techniques Find easy-to-follow code solutions for tackling common and not-so-common challenges Book Description This eagerly anticipated second edition of the popular Python Machine Learning Cookbook will enable you to adopt a fresh approach to dealing with real-world machine learning and deep learning tasks. With the help of over 100 recipes, you will learn to build powerful machine learning applications using modern libraries from the Python ecosystem. The book will also guide you on how to implement various machine learning algorithms for classification, clustering, and recommendation engines, using a recipe-based approach. With emphasis on practical solutions, dedicated sections in the book will help you to apply supervised and unsupervised learning techniques to real-world problems. Toward the concluding chapters, you will get to grips with recipes that teach you advanced techniques including reinforcement learning, deep neural networks, and automated machine learning. By the end of this book, you will be equipped with the skills you need to apply machine learning techniques and leverage the full capabilities of the Python ecosystem through real-world examples. What you will learn Use predictive modeling and apply it to real-world problems Explore data visualization techniques to interact with your data Learn how to build a recommendation engine Understand how to interact with text data and build models to analyze it Work with speech data and recognize spoken words using Hidden Markov Models Get well versed with reinforcement learning, automated ML, and transfer learning Work with image data and build systems for image recognition and biometric face recognition Use deep neural networks to build an optical character recognition system Who this book is for This book is for data scientists, machine learning developers, deep learning enthusiasts and Python programmers who want to solve real-world challenges using machine-learning techniques and algorithms. If you are facing challenges at work and want ready-to-use code solutions to cover key tasks in machine learning and the deep learning domain, then this book is w...

Anmerkung: Previous edition published: 2016. - Includes bibliographical references. - Description based on online resource; title from title page (Safari, viewed May 15, 2019)

URL: https://learning.oreilly.com/library/view/-/9781789808452/?ar

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MPI Ethno. Forsch.

3

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Keras 2.x projects : 9 projects demonstrating faster experimentation of neural network and deep learning applications using Keras (2018)

Ciaburro, Giuseppe [VerfasserIn]

Birmingham, UK : Packt Publishing

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ISBN: 9781789534160 , 178953416X

Sprache: Englisch

Seiten: 1 online resource (1 volume) , illustrations

Schlagwort(e): Reinforcement learning ; Neural networks (Computer science) ; Machine learning ; Electronic books ; Electronic books ; local

Kurzfassung: Demonstrate fundamentals of Deep Learning and neural network methodologies using Keras 2.x Key Features Experimental projects showcasing the implementation of high-performance deep learning models with Keras. Use-cases across reinforcement learning, natural language processing, GANs and computer vision. Build strong fundamentals of Keras in the area of deep learning and artificial intelligence. Book Description Keras 2.x Projects explains how to leverage the power of Keras to build and train state-of-the-art deep learning models through a series of practical projects that look at a range of real-world application areas. To begin with, you will quickly set up a deep learning environment by installing the Keras library. Through each of the projects, you will explore and learn the advanced concepts of deep learning and will learn how to compute and run your deep learning models using the advanced offerings of Keras. You will train fully-connected multilayer networks, convolutional neural networks, recurrent neural networks, autoencoders and generative adversarial networks using real-world training datasets. The projects you will undertake are all based on real-world scenarios of all complexity levels, covering topics such as language recognition, stock volatility, energy consumption prediction, faster object classification for self-driving vehicles, and more. By the end of this book, you will be well versed with deep learning and its implementation with Keras. You will have all the knowledge you need to train your own deep learning models to solve different kinds of problems. What you will learn Apply regression methods to your data and understand how the regression algorithm works Understand the basic concepts of classification methods and how to implement them in the Keras environment Import and organize data for neural network classification analysis Learn about the role of rectified linear units in the Keras network architecture Implement a recurrent neural network to classify the sentiment of sentences from movie reviews Set the embedding layer and the tensor sizes of a network Who this book is for If you are a data scientist, machine learning engineer, deep learning practitioner or an AI engineer who wants to build speedy intelligent applications with minimal lines of codes, then this book is the best fit for you. Sound knowledge of machine learning and basic familiarity with Keras library would be useful.

Anmerkung: Description based on online resource; title from title page (Safari, viewed February 26, 2019)

URL: lizenzpflichtig

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MPI Ethno. Forsch.

4

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C# 7 and .NET, designing modern cross-platform applications : the open source revolution of .NET Core (2018)

Price, Mark J. [VerfasserIn] ; Khan, Ovais Mehboob Ahmed [MitwirkendeR]

Birmingham, UK : Packt Publishing

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ISBN: 9781789957877 , 1789957877

Sprache: Englisch

Seiten: 1 online resource (1 volume) , illustrations

Serie: Learning path

Schlagwort(e): Microsoft .NET Framework ; C# (Computer program language) ; Cross-platform software development ; Application software ; Development ; Internet programming ; Electronic books ; Electronic books ; local

Kurzfassung: Explore C# and the .NET Core framework to create applications and optimize them with ASP.NET Core 2 Key Features Get to grips with multi-threaded, concurrent, and asynchronous programming in C# and .NET Core Develop modern, cross-platform applications with .NET Core 2.0 and C# 7.0 Create efficient web applications with ASP.NET Core 2. Book Description C# is a widely used programming language, thanks to its easy learning curve, versatility, and support for modern paradigms. The language is used to create desktop apps, background services, web apps, and mobile apps. .NET Core is open source and compatible with Mac OS and Linux. There is no limit to what you can achieve with C# and .NET Core. This Learning Path begins with the basics of C# and object-oriented programming (OOP) and explores features of C#, such as tuples, pattern matching, and out variables. You will understand.NET Standard 2.0 class libraries and ASP.NET Core 2.0, and create professional websites, services, and applications. You will become familiar with mobile app development using Xamarin.Forms and learn to develop high-performing applications by writing optimized code with various profiling techniques. By the end of C# 7 and .NET: Designing Modern Cross-platform Applications, you will have all the knowledge required to build modern, cross-platform apps using C# and .NET. This Learning Path includes content from the following Packt products: C# 7.1 and .NET Core 2.0 - Modern Cross-Platform Development - Third Edition by Mark J. Price C# 7 and .NET Core 2.0 High Performance by Ovais Mehboob Ahmed Khan What you will learn Explore ASP.NET Core to create professional web applications Master OOP with C# to increase code reusability and efficiency Protect your data using encryption and hashing Measure application performance using BenchmarkDotNet Use design techniques to increase your application's performance Learn memory management techniques in .NET Core Understand tools and techniques to monitor application performance Who this book is for This Learning Path is designed for developers who want to gain a solid foundation in C# and .NET Core, and want to build cross-platform applications. To gain maximum benefit from this Learning Path, you must have basic knowledge of C#.

Anmerkung: Description based on online resource; title from title page (Safari, viewed February 20, 2019)

URL: https://learning.oreilly.com/library/view/-/9781789956696/?ar

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MPI Ethno. Forsch.

5

Online-Ressource

C# and .NET Core test-driven development : dive into TDD to create flexible, maintainable, and production-ready .NET Core applications (2018)

Price, Mark J. [Verfasser]

Birmingham, UK : Packt Publishing

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Details

ISBN: 9781788299923 , 1788299922

Sprache: Englisch

Seiten: 1 online resource (1 volume) , illustrations

Paralleltitel: Erscheint auch als

RVK:

ST 250

RVK:

ST 253

Schlagwort(e): Microsoft .NET Framework ; Microsoft Visual studio ; C# (Computer program language) ; Application software Development ; Internet programming

Anmerkung: Description based on online resource; title from title page (Safari, viewed June 13, 2018)

URL: Volltext (URL des Erstveröffentlichers)

URL: https://learning.oreilly.com/library/view/-/9781788292481/?ar

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MPI Ethno. Forsch.

6

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Regression analysis with R : design and develop statistical nodes to identify unique relationships within data at scale (2018)

Ciaburro, Giuseppe [VerfasserIn]

Birmingham, UK : Packt Publishing

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ISBN: 9781788622707 , 1788622707

Sprache: Englisch

Seiten: 1 online resource (1 volume) , illustrations

Schlagwort(e): Regression analysis ; R (Computer program language) ; Statistical hypothesis testing ; Econometric models ; Electronic books ; Electronic books ; local

Kurzfassung: Build effective regression models in R to extract valuable insights from real data About This Book Implement different regression analysis techniques to solve common problems in data science - from data exploration to dealing with missing values From Simple Linear Regression to Logistic Regression - this book covers all regression techniques and their implementation in R A complete guide to building effective regression models in R and interpreting results from them to make valuable predictions Who This Book Is For This book is intended for budding data scientists and data analysts who want to implement regression analysis techniques using R. If you are interested in statistics, data science, machine learning and wants to get an easy introduction to the topic, then this book is what you need! Basic understanding of statistics and math will help you to get the most out of the book. Some programming experience with R will also be helpful What You Will Learn Get started with the journey of data science using Simple linear regression Deal with interaction, collinearity and other problems using multiple linear regression Understand diagnostics and what to do if the assumptions fail with proper analysis Load your dataset, treat missing values, and plot relationships with exploratory data analysis Develop a perfect model keeping overfitting, under-fitting, and cross-validation into consideration Deal with classification problems by applying Logistic regression Explore other regression techniques - Decision trees, Bagging, and Boosting techniques Learn by getting it all in action with the help of a real world case study. In Detail Regression analysis is a statistical process which enables prediction of relationships between variables. The predictions are based on the casual effect of one variable upon another. Regression techniques for modeling and analyzing are employed on large set of data in order to reveal hidden relationship among the variables. This book will give you a rundown explaining what regression analysis is, explaining you the process from scratch. The first few chapters give an understanding of what the different types of learning are - supervised and unsupervised, how these learnings differ from each other. We then move to covering the supervised learning in details covering the various aspects of regression analysis. The outline of chapters are arranged in a way that gives a feel of all the steps covered in a data science process - l...

Anmerkung: Description based on online resource; title from title page (Safari, viewed February 27, 2018)

URL: https://learning.oreilly.com/library/view/-/9781788627306/?ar

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MPI Ethno. Forsch.

7

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Hands-on machine learning on Google cloud platform : implementing smart and efficient analytics using Cloud ML Engine (2018)

Ciaburro, Giuseppe [Verfasser] ; Ayyadevara, V. Kishore ; Perrier, Alexis

Birmingham, UK : Packt Publishing

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ISBN: 9781788398879 , 1788398874

Sprache: Englisch

Seiten: 1 online resource (1 volume) , illustrations

Paralleltitel: Erscheint auch als

RVK:

ST 510

Schlagwort(e): Google (Firm) ; Machine learning ; Cloud computing

Anmerkung: Description based on online resource; title from title page (Safari, viewed May 30, 2018)

URL: Volltext (URL des Erstveröffentlichers)

URL: https://learning.oreilly.com/library/view/-/9781788393485/?ar

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MPI Ethno. Forsch.

8

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C# 7 and .NET Core 2.0 high performance : build highly performant, multi-threaded, and concurrent applications using C# 7 and .NET Core 2.0 (2018)

Price, Mark J. [Verfasser]

Birmingham, UK : Packt Publishing

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ISBN: 9781788474603 , 1788474600

Sprache: Englisch

Seiten: 1 online resource (1 volume) , illustrations

Paralleltitel: Erscheint auch als

Schlagwort(e): Microsoft Visual studio ; Microsoft .NET Framework ; C# (Computer program language) ; Application software Development

Anmerkung: Description based on online resource; title from title page (Safari, viewed May 24, 2018)

URL: Volltext (URL des Erstveröffentlichers)

URL: https://learning.oreilly.com/library/view/-/9781788470049/?ar

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MPI Ethno. Forsch.

9

Online-Ressource

Hands-on data warehousing with Azure Data Factory : ETL techniques to load and transform data from various sources, both on-premises and on cloud (2018)

Coté, Christian [VerfasserIn] ; Gutzait, Michelle [MitwirkendeR] ; Ciaburro, Giuseppe [MitwirkendeR]

Birmingham, UK : Packt Publishing

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ISBN: 9781789130096 , 1789130093

Sprache: Englisch

Seiten: 1 online resource (1 volume) , illustrations

Schlagwort(e): Windows Azure ; Data warehousing ; Database management ; Information storage and retrieval systems ; Data processing ; Cloud computing ; Electronic books ; Electronic books ; local

Kurzfassung: Leverage the power of Microsoft Azure Data Factory v2 to build hybrid data solutions About This Book Combine the power of Azure Data Factory v2 and SQL Server Integration Services Design and enhance performance and scalability of a modern ETL hybrid solution Interact with the loaded data in data warehouse and data lake using Power BI Who This Book Is For This book is for you if you are a software professional who develops and implements ETL solutions using Microsoft SQL Server or Azure cloud. It will be an added advantage if you are a software engineer, DW/ETL architect, or ETL developer, and know how to create a new ETL implementation or enhance an existing one with ADF or SSIS. What You Will Learn Understand the key components of an ETL solution using Azure Data Factory and Integration Services Design the architecture of a modern ETL hybrid solution Implement ETL solutions for both on-premises and Azure data Improve the performance and scalability of your ETL solution Gain thorough knowledge of new capabilities and features added to Azure Data Factory and Integration Services In Detail ETL is one of the essential techniques in data processing. Given data is everywhere, ETL will always be the vital process to handle data from different sources. Hands-On Data Warehousing with Azure Data Factory starts with the basic concepts of data warehousing and ETL process. You will learn how Azure Data Factory and SSIS can be used to understand the key components of an ETL solution. You will go through different services offered by Azure that can be used by ADF and SSIS, such as Azure Data Lake Analytics, Machine Learning and Databrick's Spark with the help of practical examples. You will explore how to design and implement ETL hybrid solutions using different integration services with a step-by-step approach. Once you get to grips with all this, you will use Power BI to interact with data coming from different sources in order to reveal valuable insights. By the end of this book, you will not only learn how to build your own ETL solutions but also address the key challenges that are faced while building them. Style and approach A step-by-step guide to develop data movement code using SSIS, Azure Data Factory, and database stored procedures for implementing intelligent BI solutions. Downloading the example code for this book You can download the example code files for all Packt books you have purchased from your account at http://www.PacktPub.com. If you ...

Anmerkung: Description based on online resource; title from title page (Safari, viewed June 29, 2018)

URL: https://learning.oreilly.com/library/view/-/9781789137620/?ar

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MPI Ethno. Forsch.

10

Online-Ressource

C# 7 and .NET Core modern cross-platform development : create powerful cross-platform applications using C# 7, .NET Core, and Visual Studio 2017 or Visual Studio Code (2017)

Price, Mark J. [VerfasserIn]

Birmingham, UK : Packt Publishing

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ISBN: 9781787120266 , 1787120260

Sprache: Englisch

Seiten: 1 online resource (1 volume) , illustrations

Ausgabe: Second edition.

Schlagwort(e): Microsoft Visual studio ; C# (Computer program language) ; Microsoft .NET Framework ; Application software ; Development ; Internet programming ; Electronic books ; Electronic books ; local

Kurzfassung: Modern Cross-Platform Development About This Book Build modern, cross-platform applications with .NET Core Get up to speed with C#, and up to date with all the latest features of C# 7 Start creating professional web applications with ASP.NET Core Who This Book Is For This book is targeted towards readers who have some prior programming experience or have a science, technology, engineering, or mathematics (STEM) background, and want to gain a solid foundation with C# and to be introduced to the types of applications they could build and will work cross-platform on Windows, Linux, and macOS. What You Will Learn Build cross-platform applications using C# 7 and .NET Core Explore ASP.NET Core and learn how to create professional web applications Improve your application's performance using multitasking Use Entity Framework Core and find out how to build code-first databases Master object-oriented programming with C# to increase code reuse and efficiency Familiarize yourself with cross-device app development using the Universal Windows Platform and XAML Query and manipulate data using LINQ Protect your data by using encryption and hashing In Detail If you want to build powerful cross-platform applications with C# 7 and .NET Core, then this book is for you. First, we'll run you through the basics of C#, as well as object-oriented programming, before taking a quick tour through the latest features of C# 7 such as tuples, pattern matching, out variables, and so on. After quickly taking you through C# and how .NET works, we'll dive into the .NET Standard 1.6 class libraries, covering topics such as performance, monitoring, debugging, serialization and encryption. The final section will demonstrate the major types of application that you can build and deploy cross-device and cross-platform. In this section, we'll cover Universal Windows Platform (UWP) apps, web applications, mobile apps, and web services. Lastly, we'll look at how you can package and deploy your applications so that they can be hosted on all of today's most popular platforms, including Linux and Docker. By the end of the book, you'll be armed with all the knowledge you need to build modern, cross-platform applications using C# and .NET Core. Style and approach This book takes a step-by-step approach and is filled with exciting projects and fascinating theory. It uses three high-impact sections to equip you with all the tools you'll need to build modern, cross-platform applications using ...

Anmerkung: Description based on online resource; title from cover (Safari, viewed April 17, 2017)

URL: https://learning.oreilly.com/library/view/-/9781787129559/?ar

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MPI Ethno. Forsch.

11

Online-Ressource

C# 7 and .NET Core modern cross-platform development : Create powerful applications with .NET Standard 2.0, ASP.NET Core 2.0, and Entity Framework Core 2.0, using Visual Studio 2017 or Visual Studio Code (2017)

Price, Mark J. [Verfasser]

Birmingham, UK : Packt Publishing

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ISBN: 9781788478694 , 178847869X

Sprache: Englisch

Seiten: 1 online resource (1 volume) , illustrations

Ausgabe: Third edition

Paralleltitel: Erscheint auch als

RVK:

ST 250

RVK:

ST 253

Schlagwort(e): Microsoft Visual studio ; Microsoft .NET Framework ; C# (Computer program language) ; Application software Development ; Internet programming

Anmerkung: Description based on online resource; title from title page (viewed January 9, 2018)

URL: Volltext (URL des Erstveröffentlichers)

URL: https://learning.oreilly.com/library/view/-/9781788398077/?ar

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MPI Ethno. Forsch.

12

Online-Ressource

Neural networks with R : smart models using CNN, RNN, deep learning, and artificial intelligence principles (2017)

Ciaburro, Giuseppe [VerfasserIn] ; Venkateswaran, Balaji [MitwirkendeR]

Birmingham, UK : Packt Publishing

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ISBN: 9781788399418 , 1788399412

Sprache: Englisch

Seiten: 1 online resource (1 volume) , illustrations

Schlagwort(e): R (Computer program language) ; Neural networks (Computer science) ; Machine learning ; Artificial intelligence ; Electronic books ; Electronic books ; local

Kurzfassung: Uncover the power of artificial neural networks by implementing them through R code. About This Book Develop a strong background in neural networks with R, to implement them in your applications Build smart systems using the power of deep learning Real-world case studies to illustrate the power of neural network models Who This Book Is For This book is intended for anyone who has a statistical background with knowledge in R and wants to work with neural networks to get better results from complex data. If you are interested in artificial intelligence and deep learning and you want to level up, then this book is what you need! What You Will Learn Set up R packages for neural networks and deep learning Understand the core concepts of artificial neural networks Understand neurons, perceptrons, bias, weights, and activation functions Implement supervised and unsupervised machine learning in R for neural networks Predict and classify data automatically using neural networks Evaluate and fine-tune the models you build. In Detail Neural networks are one of the most fascinating machine learning models for solving complex computational problems efficiently. Neural networks are used to solve wide range of problems in different areas of AI and machine learning. This book explains the niche aspects of neural networking and provides you with foundation to get started with advanced topics. The book begins with neural network design using the neural net package, then you'll build a solid foundation knowledge of how a neural network learns from data, and the principles behind it. This book covers various types of neural network including recurrent neural networks and convoluted neural networks. You will not only learn how to train neural networks, but will also explore generalization of these networks. Later we will delve into combining different neural network models and work with the real-world use cases. By the end of this book, you will learn to implement neural network models in your applications with the help of practical examples in the book. Style and approach A step-by-step guide filled with real-world practical examples.

Anmerkung: Description based on online resource; title from title page (Safari, viewed October 31, 2017)

URL: https://learning.oreilly.com/library/view/-/9781788397872/?ar

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MPI Ethno. Forsch.

13

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MATLAB for machine learning : functions, algorithms, and use cases (2017)

Ciaburro, Giuseppe [VerfasserIn]

Birmingham, UK : Packt Publishing

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Details

ISBN: 9781788399395 , 1788399390

Sprache: Englisch

Seiten: 1 online resource (1 volume) , illustrations

Schlagwort(e): MATLAB ; Machine learning ; Neural networks (Computer science) ; Electronic books ; Electronic books ; local

Kurzfassung: Extract patterns and knowledge from your data in easy way using MATLAB About This Book Get your first steps into machine learning with the help of this easy-to-follow guide Learn regression, clustering, classification, predictive analytics, artificial neural networks and more with MATLAB Understand how your data works and identify hidden layers in the data with the power of machine learning. Who This Book Is For This book is for data analysts, data scientists, students, or anyone who is looking to get started with machine learning and want to build efficient data processing and predicting applications. A mathematical and statistical background will really help in following this book well. What You Will Learn Learn the introductory concepts of machine learning. Discover different ways to transform data using SAS XPORT, import and export tools, Explore the different types of regression techniques such as simple & multiple linear regression, ordinary least squares estimation, correlations and how to apply them to your data. Discover the basics of classification methods and how to implement Naive Bayes algorithm and Decision Trees in the Matlab environment. Uncover how to use clustering methods like hierarchical clustering to grouping data using the similarity measures. Know how to perform data fitting, pattern recognition, and clustering analysis with the help of MATLAB Neural Network Toolbox. Learn feature selection and extraction for dimensionality reduction leading to improved performance. In Detail MATLAB is the language of choice for many researchers and mathematics experts for machine learning. This book will help you build a foundation in machine learning using MATLAB for beginners. You'll start by getting your system ready with t he MATLAB environment for machine learning and you'll see how to easily interact with the Matlab workspace. We'll then move on to data cleansing, mining and analyzing various data types in machine learning and you'll see how to display data values on a plot. Next, you'll get to know about the different types of regression techniques and how to apply them to your data using the MATLAB functions. You'll understand the basic concepts of neural networks and perform data fitting, pattern recognition, and clustering analysis. Finally, you'll explore feature selection and extraction techniques for dimensionality reduction for performance improvement. At the end of the book, you will learn to put it all together into rea...

Anmerkung: Description based on online resource; title from title page (Safari, viewed September 25, 2017)

URL: https://learning.oreilly.com/library/view/-/9781788398435/?ar

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MPI Ethno. Forsch.

14

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C# 6 and .NET Core 1.0 modern cross-platform development : create powerful cross-platform applications using C# 6, Net Core 1.0 ASP.NET Core 1.0 and Visual Studio 2015 (2016)

Price, Mark J. [VerfasserIn]

Birmingham, UK : Packt Publishing

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Details

ISBN: 9781783558544 , 1783558547

Sprache: Englisch

Seiten: 1 online resource (1 volume) , illustrations

Serie: Community experience distilled

Schlagwort(e): Microsoft Visual studio ; C# (Computer program language) ; Microsoft .NET Framework ; Application software ; Development ; Internet programming ; Electronic books ; Electronic books ; local

Kurzfassung: The book has now been updated About This Book Build modern, cross-platform applications with .NET Core 1.0 Get up-to-speed with C#, and up-to-date with all the latest features of C# 6 Start creating professional web applications with ASP.NET Core 1.0 Who This Book Is For Are you struggling to get started with C#? Or maybe you're interested in the potential of the new cross-platform features that .NET Core can offer? If so, C# 6 and .NET Core 1.0 is the book for you. While you don't need to know any of the latest features of C# or .NET to get started, it would be beneficial if you have some programming experience. What You Will Learn Build cross-platform applications using C# 6 and .NET Core 1.0 Explore ASP.NET Core 1.0 and learn how to create professional web applications Improve your application's performance using multitasking Use Entity Framework Core 1.0 and learn how to build Code-First databases Master object-oriented programming with C# to increase code reuse and efficiency Familiarize yourself with cross-device app development using the Universal Windows Platform and XAML Query and manipulate data using LINQ Protect your data by using encryption and hashing In Detail With the release of .NET Core 1.0, you can now create applications for Mac OS X and Linux, as well as Windows, using the development tools you know and love. C# 6 and .NET Core 1.0 has been divided into three high-impact sections to help start putting these new features to work. First, we'll run you through the basics of C#, as well as object-orient programming, before taking a quick tour through the latest features of C# 6 such as string interpolation for easier variable value output, exception filtering, and how to perform static class imports. We'll also cover both the full-feature, mature .NET Framework and the new, cross-platform .NET Core. After quickly taking you through C# and how .NET works, we'll dive into the internals of the .NET class libraries, covering topics such as performance, monitoring, debugging, internationalization, serialization, and encryption. We'll look at Entity Framework Core 1.0 and how to develop Code-First entity data models, as well as how to use LINQ to query and manipulate that data. The final section will demonstrate the major types of applications that you can build and deploy cross-device and cross-platform. In this section, we'll cover Universal Windows Platform (UWP) apps, web applications, and web services. Lastly, we'll help you bu...

Anmerkung: Includes index. - Description based on online resource; title from cover (viewed April 11, 2016)

URL: https://learning.oreilly.com/library/view/-/9781785285691/?ar

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