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Category: "Machine Learning"

Books

  1. CUDA Applications
    Evgenij Lebedev

    Delve into the great ecosystem of CUDA frameworks and libraries through independent projects.Solve modern, real-world technical applications using CUDA.Interesting projects that will help you build High-Performance applications with CUDA.

  2. Do Machine Learning Yourself is a collection of do it yourself (DIY) projects about machine learning, mainly about computer vision, for beginner and intermediate levels. Through a detailed guidance per each project, everything required to do that project yourself will be clear. A focus is to make the projects run in mobile devices.

  3. Hacker's Guide to Machine Learning with Python
    Hands-on guide to solving real-world Machine Learning problems with Scikit-Learn, TensorFlow 2, and Keras
    Venelin Valkov

    This book brings the fundamentals of Machine Learning to you, using tools and techniques used to solve real-world problems in Computer Vision, Natural Language Processing, and Time Series analysis. The skills taught in this book will lay the foundation for you to advance your journey to Machine Learning Mastery!

  4. What is AI ?
    And what is its relation to consciousness and life?
    Reik Oberrath

    Intelligence is problem solving. Is that all which can be said about it? How do natural and artificial intelligence differ? And what has consciousness or even life to do with it? How does AI basically work? What is its benefit and disadvantage? How much do we need AI? These questions and more are discussed and to most of them an answer is given.

  5. This book teaches the different types of convolution operators to design Deep Neural Networks with a variety of illustrative figures and examples. The basic concepts of the convolution operator to its advanced types are described with full details in this book. Reading this book is recommended to all researchers, and engineers in this field.

  6. Modern R with the tidyverse
    Bruno Rodrigues, Phd

    Learn to use R, the tidyverse collection of packages and functional programming concepts to write efficient and readable code.

  7. Learn Python the Simple Way
    The fundamental programming language for Machine Learning (ML), Scientific and Numeric Computing, Robotics and Web Development
    Sanjib Sinha

    Reading "Learn Python the Simple Way", you'll learn how software work.At this moment, Python is one of the fundamental programming languages for Machine Learning (ML), Scientific and Numeric Computing, Robotics and even Web Development.

  8. Hacker's Guide to Neural Networks in JavaScript
    Beginners guide to understanding Machine Learning in the browser with TensorFlow.js
    Venelin Valkov

    Build Machine Learning models (especially Deep Neural Networks) that you can easily integrate with existing or new web apps. Think of your ReactJs, Vue, or Angular app enhanced with the power of Machine Learning models.

  9. Voice of Foreign Exchange™ Expert Advisors
    MQL Expert Advisor Source Code Strategies - Volume I
    Stephen Gose

    The "Voice of Foreign Exchange™" is a series of 8 expert advisors reinventing the "Elliott Wave Theory" and other popular trading methods using modern communications formula. This is Volume I in the Expert Advisor Series. This book has the source code for 2 expert advisors and the Voice over Foreign Exchange™ (Vo4X) engine.

  10. ビジネスの現場で活躍するPython分析と機械学習
    Machine Learning for Bussiness with python
    Ken Nakai (中井 研) and shuhei ando

    Pythonを使って、基本的な分析処理から機械学習・ディープラーニングまで扱う内容になっています。特にビジネス系の職種の方でもPythonを活用して分析処理に挑戦できるように、入門的な内容から始め、現場でよく使われるテクニックを盛り込みました。AIブームにいち早くキャッチアップするとともに日々の仕事でも活かせる内容が学習できるお得なコンテンツです。

  11. Hands-On Machine Learning from Scratch
    Develop a Deeper Understanding of Machine Learning Models by Implementing Them from Scratch in Python
    Venelin Valkov

    "What I cannot create, I do not understand" - Richard Feynman This book will guide you on your journey to deeper Machine Learning understanding by developing algorithms in Python from scratch! Learn why and when Machine learning is the right tool for the job and how to improve low performing models!

  12. Trust Me, I'm A Bot
    Building Digital Trust Using Conversational AI
    Allan Froy

    Building a chatbot is easy. Too easy, in fact. Learn why your bots need to build trust with users and start your journey to a truly engaging chatbot experience.

  13. Startups with China
    Ideas and Execution Plans
    Qiao Zhang

    Have you ever wanted to start a business in China? The book is an ideas library with detailed execution plans to help non-Chinese entrepreneurs start a business in China, within fields of coding, AI and Machine Learning, IoT, Internet, Consumer Products and Services, Investment, Fintech, Data Analytics, B2B and MarTech.

  14. Machine Learning Pipeline
    Experience Gain
    Hisham El-Amir

    Hello! Welcome to this guide to machine learning pipeline. If you want to get up-to-speed with some of the most data modeling techniques and gain experience using them to solve challenging problems, this is a good book for you!

  15. Get a hands-on introduction to machine learning with genetic algorithms using Python. Step-by-step tutorials build your skills from Hello World! to optimizing one genetic algorithm with another, and finally genetic programming; thus preparing you to apply genetic algorithms to problems in your own field of expertise.