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Machine Learning Using TensorFlow Cookbook

Alexia Audevart (Autor)

Packt Publishing (Editora)

R$ 292,15
SKU: 9781800208865

Comprehensive recipes to give you valuable insights on Transformers, Reinforcement Learning, and more


Key Features:

  • Deep Learning solutions from Kaggle Masters and Google Developer Experts
  • Get to grips with the fundamentals including variables, matrices, and data sources
  • Learn advanced techniques to make your algorithms faster and more accurate


Book Description:

The independent recipes in Machine Learning Using TensorFlow Cookbook will teach you how to perform complex data computations and gain valuable insights into your data. Dive into recipes on training models, model evaluation, sentiment analysis, regression analysis, artificial neural networks, and deep learning - each using Google's machine learning library, TensorFlow.


This cookbook covers the fundamentals of the TensorFlow library, including variables, matrices, and various data sources. You'll discover real-world implementations of Keras and TensorFlow and learn how to use estimators to train linear models and boosted trees, both for classification and regression.


Explore the practical applications of a variety of deep learning architectures, such as recurrent neural networks and Transformers, and see how they can be used to solve computer vision and natural language processing (NLP) problems.


With the help of this book, you will be proficient in using TensorFlow, understand deep learning from the basics, and be able to implement machine learning algorithms in real-world scenarios.


What You Will Learn:

  • Take TensorFlow into production
  • Implement and fine-tune Transformer models for various NLP tasks
  • Apply reinforcement learning algorithms using the TF-Agents framework
  • Understand linear regression techniques and use Estimators to train linear models
  • Execute n

Sobre o Livro

Receitas práticas mostram como usar TensorFlow e Keras para treinamento de modelos, avaliação de desempenho e tarefas de regressão com exemplos concretos de código.

No campo de deep learning, o livro traz implementações de redes recorrentes e Transformers aplicadas a visão computacional e processamento de linguagem natural, incluindo casos de uso e ajustes de arquitetura.

Capítulos dedicados à produção abordam Estimators, TF‑Agents para aprendizado por reforço e técnicas para otimizar velocidade e precisão de algoritmos em cenários reais.

Características

Categoria Informática
Subcategoria Inteligência artificial
Autores Alexia Audevart
Sobre o Autor Alexia Audevart é autora de obras técnicas na área de aprendizado de máquina, com foco em implementações práticas usando bibliotecas modernas como TensorFlow.
Idioma Inglês
Quantidade de Páginas 416
Acabamento Brochura
Editora Packt Publishing
ISBN 9781800208865
Tamanho 19.1x23.5
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