Showing 4 open source projects for "writing a book"

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  • 1
    aigc

    aigc

    An e-book about the real-world application of LLM

    "Building Large Language Model Applications: Application Development and Architecture Design" is an open source e-book about the real-world application of LLM. It introduces the basics and applications of large language models, as well as how to build your own models. These include writing, developing, and managing prompts, exploring what the best large language models can bring, and pattern and architecture design for LLM application development.
    Downloads: 2 This Week
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  • 2
    Key-book

    Key-book

    Proofs, cases, concept supplements, and reference explanations

    ... concepts or theoretical tools in machine learning theory, namely: learnability, (hypothesis space) complexity, generalization bound, stability, consistency, convergence rate, regret circle. Daoyin is a highly theoretical book, involving a large number of mathematical theorems and various proofs. Although the writing team has reduced the difficulty as much as possible, due to the nature of machine learning theory, the book still places high demands on the reader's mathematical background.
    Downloads: 0 This Week
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  • 3
    Machine Learning Yearning

    Machine Learning Yearning

    Machine Learning Yearning

    Artificial intelligence, machine learning and deep learning are transforming numerous industries. Professor Andrew Ng is currently writing a book on how to build machine learning projects. The point of this book is not to teach traditional machine learning algorithms, but to teach you how to make machine learning algorithms work. Some technical courses in AI will give you a tool, and this book will teach you how to use those tools. If you aspire to be a technical leader in AI and want to learn...
    Downloads: 1 This Week
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  • 4
    Pragmatic AI

    Pragmatic AI

    [Book-2019] Pragmatic AI: An Introduction to Cloud-based ML

    Pragmatic AI is the first truly practical guide to solving real-world problems with contemporary machine learning, artificial intelligence, and cloud computing tools. Writing for business professionals, decision-makers, and students who aren’t professional data scientists, Noah Gift demystifies all the tools and technologies you need to get results. He illuminates powerful off-the-shelf cloud-based solutions from Google, Amazon, and Microsoft, as well as accessible techniques using Python and R...
    Downloads: 0 This Week
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