TensorFlow Machine Learning Cookbook - Second Edition

Nick McClure

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商品描述

Skip the theory and get the most out of Tensorflow to build production-ready machine learning models

Key Features

  • Exploit the features of Tensorflow to build and deploy machine learning models
  • Train neural networks to tackle real-world problems in Computer Vision and NLP
  • Handy techniques to write production-ready code for your Tensorflow models

Book Description

TensorFlow is an open source software library for Machine Intelligence. The independent recipes in this book will teach you how to use TensorFlow for complex data computations and allow you to dig deeper and gain more insights into your data than ever before.

With the help of this book, you will work with recipes for training models, model evaluation, sentiment analysis, regression analysis, clustering analysis, artificial neural networks, and more. You will explore RNNs, CNNs, GANs, reinforcement learning, and capsule networks, each using Google's machine learning library, TensorFlow. Through real-world examples, you will get hands-on experience with linear regression techniques with TensorFlow. Once you are familiar and comfortable with the TensorFlow ecosystem, you will be shown how to take it to production.

By the end of the book, you will be proficient in the field of machine intelligence using TensorFlow. You will also have good insight into deep learning and be capable of implementing machine learning algorithms in real-world scenarios.

What you will learn

  • Become familiar with the basic features of the TensorFlow library
  • Get to know Linear Regression techniques with TensorFlow
  • Learn SVMs with hands-on recipes
  • Implement neural networks to improve predictive modeling
  • Apply NLP and sentiment analysis to your data
  • Master CNN and RNN through practical recipes
  • Implement the gradient boosted random forest to predict housing prices
  • Take TensorFlow into production

Who this book is for

If you are a data scientist or a machine learning engineer with some knowledge of linear algebra, statistics, and machine learning, this book is for you. If you want to skip the theory and build production-ready machine learning models using Tensorflow without reading pages and pages of material, this book is for you. Some background in Python programming is assumed.

Table of Contents

  1. Getting Started with TensorFlow
  2. The TensorFlow Way
  3. Linear Regression
  4. Support Vector Machines
  5. Nearest Neighbor Methods
  6. Neural Networks
  7. Natural Language Processing
  8. Convolutional Neural Networks
  9. Recurrent Neural Networks
  10. Taking TensorFlow to Production
  11. More with TensorFlow

商品描述(中文翻譯)

跳過理論,並充分利用Tensorflow來建立可投入生產的機器學習模型

主要特點:
- 利用Tensorflow的功能來建立和部署機器學習模型
- 訓練神經網絡以應對計算機視覺和自然語言處理中的實際問題
- 提供實用技巧,以編寫適用於Tensorflow模型的生產就緒代碼

書籍描述:
TensorFlow是一個用於機器智能的開源軟件庫。本書中的獨立範例將教您如何使用TensorFlow進行複雜的數據計算,並讓您比以往更深入地瞭解數據。

通過本書的幫助,您將學習到有關訓練模型、模型評估、情感分析、回歸分析、聚類分析、人工神經網絡等方面的技巧。您將使用Google的機器學習庫TensorFlow探索循環神經網絡、卷積神經網絡、生成對抗網絡、強化學習和膠囊網絡。通過真實世界的例子,您將親身體驗使用TensorFlow進行線性回歸技術的實踐。一旦您熟悉並熟悉TensorFlow生態系統,您將學習如何將其應用於生產環境中。

通過本書,您將精通使用TensorFlow進行機器智能領域。您還將對深度學習有深入的了解,並能夠在實際情境中實施機器學習算法。

您將學到:
- 熟悉TensorFlow庫的基本功能
- 了解使用TensorFlow進行線性回歸技術
- 學習使用實用範例進行支持向量機
- 實施神經網絡以改進預測建模
- 將自然語言處理和情感分析應用於數據
- 通過實用範例掌握卷積神經網絡和循環神經網絡
- 實施梯度提升隨機森林以預測房價
- 將TensorFlow應用於生產環境

本書適合對線性代數、統計學和機器學習有一定了解的數據科學家或機器學習工程師。如果您想跳過理論,並使用Tensorflow建立可投入生產的機器學習模型,而不必閱讀大量的資料,那麼本書適合您。需要一些Python編程背景。