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  • 1
    Online Resource
    Online Resource
    Julia Programming Language - From Zero to Expert (2021)
    [Erscheinungsort nicht ermittelbar] : Packt Publishing | Boston, MA : Safari
    Details
    ISBN: 9781803230719
    Language: English
    Pages: 1 online resource (1 video file, approximately 3 hr., 33 min.)
    Edition: 1st edition
    Keywords: Electronic videos
    Abstract: Explore Julia, the next-generation language, for advancing in the field of data science, machine learning, and numerical computing About This Video Learn the syntax of Julia and its differences from Python Learn machine learning models, both traditional and deep Explore data science case studies, including analysis and clustering In Detail The objective of this course is to give you a strong foundation needed to excel in Julia and learn the core of the language as well as the applied side in the shortest amount of time possible. We won't waste time with the theory of why Julia is fast. We will jump right into the details and start coding. You will quickly realize how easy it is to learn this state-of-the-art and promising language. You will see how you can start using Julia to excel in your current job without moving the whole stack to Julia immediately. After explaining the basic concepts, we jump to case studies in data science and then machine learning. We apply both traditional machine learning models and then get to deep learning. You will see how Julia can help you create deep learning models from scratch in just a few lines of code and then move on to the state-of-the-art models without spending too much time. This way, you get to learn the most important concepts in this subject in the shortest amount of time possible without having to deal with the details of the less relevant topics. Once you have developed an intuition of the important stuff, you can then learn the latest and greatest models even on your own! By the end of the course, you will have a strong understanding of Julia programming language fundamentals. Who this book is for This course is for all levels of data science and machine learning practitioners aiming to enhance their abilities and skill level in DS and ML. Developers who want to know how to harness the power of big data can also go for this course. A basic understanding of programming is a must. Understanding Python, basic data science (reading CSVs and so on), and basic concepts of deep learning (such as classification) is not necessary but would be helpful.
    Note: Online resource; Title from title screen (viewed September 23, 2021) , Mode of access: World Wide Web.
    URL: lizenzpflichtig
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  • 2
    Online Resource
    Online Resource
    Probability / statistics : the foundations of machine learning (2022)
    [Place of publication not identified] : Packt Publishing
    Details
    ISBN: 9781803241197 , 1803241195
    Language: English
    Pages: 1 online resource (1 video file (6 hr., 36 min.)) , sound, color.
    Edition: [First edition].
    DDC: 006.3/1
    Keywords: Machine learning ; Probabilities Data processing ; Statistics Data processing ; Instructional films ; Nonfiction films ; Internet videos
    Abstract: Learn how to use probability/statistics in all areas of computer science, data science, and machine learning About This Video A practical approach towards understanding the core concepts of probability and statistics Focuses on the applications of these important mathematical concepts in data science, machine learning, and other areas Understand why probability is the foundation of all modern machine learning In Detail The objective of this course is to give you a solid foundation needed to excel in all areas of computer science--specifically data science and machine learning. The issue is that most of the probability and statistics courses are too theory-oriented. They get tangled in the math without discussing the importance of applications. Applications are always given secondary importance. In this course, we take a code-oriented approach. We apply all concepts through code. In fact, we skip over all the useless theory that isn't relevant to computer science. Instead, we focus on the concepts that are more useful for data science, machine learning, and other areas of computer science. For instance, many probability courses skip over Bayesian inference. We will get to this immensely important concept rather quickly and give it due attention as it is widely thought of as the future of analysis! This way, you get to learn the most important concepts in this subject in the shortest amount of time possible without having to deal with the details of the less relevant topics. Once you have developed an intuition of the important stuff, you can then learn the latest and greatest models even on your own! Audience This course is designed for beginner ML and data science developers who need a solid foundation, for developers curious about data science and machine learning, for people looking to find out why probability is the foundation of all modern machine learning, or for developers who want to know how to harness the power of big data.
    Note: "Updated in June 2022.". - Online resource; title from title details screen (O'Reilly, viewed July 6, 2022)
    URL: lizenzpflichtig
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  • 3
    Online Resource
    Online Resource
    Create your first DApp on Ethereum : a concise tutorial (2022)
    [Place of publication not identified] : Packt Publishing
    Details
    ISBN: 9781803232980 , 1803232986
    Language: English
    Pages: 1 online resource (1 video file (1 hr., 18 min.)) , sound, color.
    Edition: [First edition].
    DDC: 005.8/24
    Keywords: Blockchains (Databases) ; Electronic funds transfers ; Electronic data processing Distributed processing ; Computer software Development ; Instructional films ; Nonfiction films ; Internet videos
    Abstract: Setup a local blockchain, create and deploy two simple smart contracts for DApps using Ethereum, Hardhat, and node.js About This Video Learn how to create DApps (smart contracts) using Ethereum, Hardhat, and node.js Learn how to deploy your own DApp with minimal effort A complete hands-on course for better learning experience In Detail Blockchains and technologies supported by blockchains such as distributed apps (DApps/smart contracts), NFTs, and Web3 are taking the world by storm. Everyone is talking about them and developers knowledgeable in these technologies are some of the highest-paid in the world! There are so many components to a DApp that you can easily get lost in the hundreds of components, libraries, and tools floating around the web. To learn how to create DApps, you can assume that a blockchain is a distributed data store that provides certain guarantees. Then, start using existing blockchain frameworks to deploy your DApps just as you would deploy your sites on the web without having to rebuild a webserver! This is the approach we take in this course. You will set up a blockchain environment using stable, easy-to-use frameworks. Then, you will look at two smart contracts (or DApps) and deploy them first locally and later a global distributed TestNet. This will take you through all the steps needed to deploy your own DApp with minimal effort. In the end, you will deploy your (and your clients') DApps on the Ethereum mainnet. By the end of this course, you will be able to create your first DApp on Ethereum. Audience This course is designed for anyone who wants to get started with DApps (smart contracts) or is having trouble with getting started with DApps. This course is for anyone who wants to learn DApps without having to recreate whole blockchain architectures. For this course, one needs no previous understanding of blockchains, just some knowledge of basic JavaScript is required. React is used for a sample application. So, knowing it is a plus.
    Note: "Updated in June 2022.". - Online resource; title from title details screen (O'Reilly, viewed July 6, 2022)
    URL: lizenzpflichtig
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  • 4
    Online Resource
    Online Resource
    Beyond basic programming : intermediate Python (2018)
    [Place of publication not identified] : Packt Publishing
    Details
    ISBN: 9781838559458
    Language: English
    Pages: 1 online resource (1 streaming video file (3 hr., 9 min., 21 sec.)) , digital, sound, color
    Keywords: Python (Computer program language) ; Computer programming ; Electronic videos ; local
    Abstract: "How do you go from a novice programmer to an expert? How do you become a professional? This course answers this question. In it, we will build on top of your existing basic understanding of the Python language (and programming in general). We will cover concepts that will take you to the next level of programming expertise. These will include language constructs that are typically not covered in a beginner-level course--concepts such as generators, decorators, callbacks, higher-order functions, context managers, and more. We will also discuss some tools that are not difficult but are essential to the life of a professional programmer. An example of this is logging for tracking down bugs, a simple technique that is used in all production-level software but is never touched upon in typical programming courses. We will discuss parallel programming, multi-threading, and synchronization issues--another important concept you must understand to code in a production environment. We discuss these through a case study to explain WHY you need them as well as HOW to use them."--Resource description page.
    Note: Title from title screen (Safari, viewed February 13, 2019). - Publication information from resource description page (Safari, viewed February 13, 2019)
    URL: lizenzpflichtig
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