Minha sacola

    MACHINE LEARNING WITH PYTORCH AND SCIKIT-LEARN

    Favoritar
    Ref:
    1030989

    Por: R$ 560,00ou X de

    Comprar

    Calcule o frete:

    Para envios internacionais, simule o frete no carrinho de compras.

    Calcule o valor do frete e prazo de entrega para a sua região

    Editora
    ISBN
    Páginas
    Idioma
    Peso
    Acabamento

    Sinopse

    This book of the bestselling and widely acclaimed Python Machine Learning series is a comprehensive guide to machine and deep learning using PyTorch's simple to code framework.

    Purchase of the print or Kindle book includes a free eBook in PDF format.

    Key Features
    Learn applied machine learning with a solid foundation in theory
    Clear, intuitive explanations take you deep into the theory and practice of Python machine learning
    Fully updated and expanded to cover PyTorch, transformers, XGBoost, graph neural networks, and best practices
    Book Description
    Machine Learning with PyTorch and Scikit-Learn is a comprehensive guide to machine learning and deep learning with PyTorch. It acts as both a step-by-step tutorial and a reference you'll keep coming back to as you build your machine learning systems.

    Packed with clear explanations, visualizations, and examples, the book covers all the essential machine learning techniques in depth. While some books teach you only to follow instructions, with this machine learning book, we teach the principles allowing you to build models and applications for yourself.

    Why PyTorch?

    PyTorch is the Pythonic way to learn machine learning, making it easier to learn and simpler to code with. This book explains the essential parts of PyTorch and how to create models using popular libraries, such as PyTorch Lightning and PyTorch Geometric.

    You will also learn about generative adversarial networks (GANs) for generating new data and training intelligent agents with reinforcement learning. Finally, this new edition is expanded to cover the latest trends in deep learning, including graph neural networks and large-scale transformers used for natural language processing (NLP).

    This PyTorch book is your companion to machine learning with Python, whether you're a Python developer new to machine learning or want to deepen your knowledge of the latest developments.

    What you will learn
    Explore frameworks, models, and techniques for machines to 'learn' from data
    Use scikit-learn for machine learning and PyTorch for deep learning
    Train machine learning classifiers on images, text, and more
    Build and train neural networks, transformers, and boosting algorithms
    Discover best practices for evaluating and tuning models
    Predict continuous target outcomes using regression analysis
    Dig deeper into textual and social media data using sentiment analysis
    Who this book is for
    If you have a good grasp of Python basics and want to start learning about machine learning and deep learning, then this is the book for you. This is an essential resource written for developers and data scientists who want to create practical machine learning and deep learning applications using scikit-learn and PyTorch.

    Before you get started with this book, you'll need a good understanding of calculus, as well as linear algebra.

    Table of Contents
    Giving Computers the Ability to Learn from Data
    Training Simple Machine Learning Algorithms for Classification
    A Tour of Machine Learning Classifiers Using Scikit-Learn
    Building Good Training Datasets – Data Preprocessing
    Compressing Data via Dimensionality Reduction
    Learning Best Practices for Model Evaluation and Hyperparameter Tuning
    Combining Different Models for Ensemble Learning
    Applying Machine Learning to Sentiment Analysis
    Predicting Continuous Target Variables with Regression Analysis
    Working with Unlabeled Data – Clustering Analysis
    Implementing a Multilayer Artificial Neural Network from Scratch
    (N.B. Please use the Look Inside option to see further chapters)

    Ficha Técnica

    Especificações

    ISBN9781801819312
    SubtítuloDEVELOP MACHINE LEARNING AND DEEP LEARNING MODELS WITH PYTHON
    Pré vendaNão
    Peso1306g
    Autor para link
    Livro disponível - pronta entregaNão
    Dimensões23 x 18 x 4.4
    IdiomaInglês
    Tipo itemLIVRO IMPORTADO ADQ MERC INTERNO
    Número de páginas774
    Número da edição1ª EDIÇÃO - 2022
    Código Interno1030989
    Código de barras9781801819312
    AcabamentoPAPERBACK
    AutorRASCHKA, SEBASTIAN | LIU,YUXI (HAYDEN) | MIRJALILI, VAHID
    EditoraPACKT PUBLISHING
    Sob encomendaSim

    Conheça outros títulos da coleção

      Este livro é vendido

      SOB ENCOMENDA

      Prazo estimado para disponibilidade em estoque: dias úteis

      (Sujeito aos estoques de nossos fornecedores)

      +

      Prazo do frete selecionado.

      (Veja o prazo total na sacola de compras)

      Comprar