Leanpub Header

Skip to main content

Filters

Category: "Machine Learning"

Books

  1. Crowdsourcing and Simulation with Mobile Agents and the JavaScript Agent Machine

    Programming of distributed and Web crowdsourcing applications using mobile agents and the JavaScript Agent Machine can be so easy! Less than 100 lines code are required to create a multi-agent system. Only basic JavaScript knowledge is required.

  2. Aprendizaje Profundo con PyTorch Paso a Paso - Volumen I: Fundamentos
    Aprendizaje Profundo con PyTorch Paso a Paso - Volumen I: Fundamentos
    Una Guía para Principiantes
    Daniel Voigt Godoy and Jesús Martínez-Blanco

    ¿Estás buscando un libro con el que puedas aprender sobre aprendizaje profundo y PyTorch sin tener que pasar horas descifrando texto y código críptico? ¿Un libro técnico que sea también legible y entretenido? ¡Aquí lo tienes!

  3. Serverless 101 - Essential Patterns for Data Scientist
    Serverless 101 - Essential Patterns for Data Scientist
    Hands-on guideline on deploying applications using serverless.com for data scientists
    Konrad Semsch

    Get to know how to deploy small applications and machine learning solutions using the serverless.com framework.

  4. Zefs Guide to Deep Learning Flashcards

    Zefs Guide to Deep Learning Flashcards is a set of digital flashcards that accompany the book Zefs Guide to Deep Learning. Anyone wanting to improve their knowledge of the key concepts in machine learning and deep learning will benefit from studying with these flashcards, whether to land that dream AI job or ace their machine learning exams.

  5. Machine Learning in Python for Process Systems Engineering
    Machine Learning in Python for Process Systems Engineering
    Achieve Operational Excellence Using Process Data
    Ankur Kumar and Jesus Flores Cerrillo

    This book provides a guided tour along the wide range of ML methods that have proven useful in process industry. Step-by-step instructions, supported with real process datasets, show how to develop ML-based solutions for process monitoring, predictive maintenance, fault diagnosis, soft sensing, and process control. Also available at Google Play.

  6. Zefs Guide to Deep Learning

    Zefs Guide to Deep Learning is a short guide to the most important concepts in deep learning, the technique at the center of the current artificial intelligence revolution. It will give you a strong understanding of the core ideas and most important methods and applications. All in around only 150 pages!

  7. The Hitchhiker's Guide to Responsible Machine Learning
    The Hitchhiker's Guide to Responsible Machine Learning
    The introduction to Interpretable and Responsible Machine Learning and eXplainable Artificial Intelligence with code examples for R
    Przemysław Biecek

    Selected modern machine learning techniques and the intuition behind them. Methods are supplemented by code snippets with examples in R language. The process is shown through a comic book describing the adventures of two characters, Beta and Bit.  See the flipbook version at https://betaandbit.github.io/RML/

  8. Statistical foundations of machine learning: the book

    All the statistical foundations you need to understand and use machine learning! It includes R/Pyhton software and Shiny dashboards to illustrate the most important concepts numerically.

  9. Deep Learning in Production
    Deep Learning in Production
    Sergios Karagiannakos

    Build, train, deploy, scale and maintain deep learning models. Understand ML infrastructure and MLOps using hands-on examples.

  10. 入門 日本語自然言語処理
    入門 日本語自然言語処理
    Masato Hagiwara and Paul O'Leary McCann

    日本語テキストを処理したい全てのプログラマ・エンジニアの方へ。分かち書きなどの基本から、自然言語生成などの最新の話題までをカバー。動かして学べるコードや、参照文献も付いています。言語学や機械学習の知識が無くても問題ありません。

  11. Introduction to Japanese Natural Language Processing
    Introduction to Japanese Natural Language Processing
    Masato Hagiwara and Paul O'Leary McCann

    A thorough guide for programmers working with Japanese text, covering fundamental issues like tokenization and recent research topics like generating natural language texts. Working examples are accompanied by extensive reference to allow problem solving even without a background in Japanese or Machine Learning.

  12. Advanced Python for Data Science

    Python is a rich and powerful language, but many data scientists merely scratch the surface, and often feel uncertain about what lies beneath.  This book will go deep into the heart of Python, to truly understand its components, and how we can stitch them together to build better scientific workflows and machine learning systems.

  13. Dungeons & Qubits
    Dungeons & Qubits
    An Adventurer's Tale Beyond the Quantum Computing Tutorials
    Brian N. Siegelwax
    No Description Available
  14. Neural Networks Fundamentals with Python
    Neural Networks Fundamentals with Python
    Rodrigo Girão Serrão @ Mathspp

    Ever wondered what a neural network really is, how it works, or how to implement one? Well, I did, and that is why I tried implementing one. And it was amazing! Now, I just want to help you do it yourself, so that you can take a peek behind the curtains of this world of machine learning, deep learning, and all those buzzwords.

  15. 15 Cheat Sheet Collection in Python + Git + NumPy + ML + Mindset
    15 Cheat Sheet Collection in Python + Git + NumPy + ML + Mindset
    Easy + Quick Learning with Finxter's Best Cheat Sheets
    Finxter

    This 15x PDF collection is a compilation of the best cheat sheets created for my free Finxter Email Academy that teaches Python in byte-sized video and cheat sheet lessons.