TensorFlow Machine Learning Projects: Build 13 real-world projects with advanced numerical computations using the Python ecosystem

Ankit Jain, Armando Fandango, Amita Kapoor

商品描述

Implement TensorFlow's offerings such as TensorBoard, TensorFlow.js, TensorFlow Probability, and TensorFlow Lite to build smart automation projects

Key Features

  • Use machine learning and deep learning principles to build real-world projects
  • Get to grips with TensorFlow's impressive range of module offerings
  • Implement projects on GANs, reinforcement learning, and capsule network

Book Description

TensorFlow has transformed the way machine learning is perceived. TensorFlow Machine Learning Projects teaches you how to exploit the benefits―simplicity, efficiency, and flexibility―of using TensorFlow in various real-world projects. With the help of this book, you'll not only learn how to build advanced projects using different datasets but also be able to tackle common challenges using a range of libraries from the TensorFlow ecosystem.

To start with, you'll get to grips with using TensorFlow for machine learning projects; you'll explore a wide range of projects using TensorForest and TensorBoard for detecting exoplanets, TensorFlow.js for sentiment analysis, and TensorFlow Lite for digit classification.

As you make your way through the book, you'll build projects in various real-world domains, incorporating natural language processing (NLP), the Gaussian process, autoencoders, recommender systems, and Bayesian neural networks, along with trending areas such as Generative Adversarial Networks (GANs), capsule networks, and reinforcement learning. You'll learn how to use the TensorFlow on Spark API and GPU-accelerated computing with TensorFlow to detect objects, followed by how to train and develop a recurrent neural network (RNN) model to generate book scripts.

By the end of this book, you'll have gained the required expertise to build full-fledged machine learning projects at work.

What you will learn

  • Understand the TensorFlow ecosystem using various datasets and techniques
  • Create recommendation systems for quality product recommendations
  • Build projects using CNNs, NLP, and Bayesian neural networks
  • Play Pac-Man using deep reinforcement learning
  • Deploy scalable TensorFlow-based machine learning systems
  • Generate your own book script using RNNs

Who this book is for

TensorFlow Machine Learning Projects is for you if you are a data analyst, data scientist, machine learning professional, or deep learning enthusiast with basic knowledge of TensorFlow. This book is also for you if you want to build end-to-end projects in the machine learning domain using supervised, unsupervised, and reinforcement learning techniques

Table of Contents

  1. Overview of Tensorflow and Machine Learning
  2. Using Machine Learning to detect exoplanets in outer space
  3. Sentiment Analysis in your browser using Tensorflow.js
  4. Digit Classification using Tensorflow Lite
  5. Speech to text and topic extraction using NLP
  6. Predicting Stock Prices using Gaussian Process Regression
  7. Credit Card Fraud Detection using Autoencoders
  8. Generating Uncertainty in Traffic Signs Classifier using Bayesian Neural Networks
  9. Generating Matching Shoe Bags from Shoe Images Using DiscoGANs
  10. Classifying Clothing Images using Capsule Networks
  11. Making Quality Product Recommendations Using TensorFlow
  12. Object detection at a large scale with Tensorflow
  13. Generating Book Scripts Using LSTMs
  14. Playing Pacman using Deep Reinforcement Learning
  15. What is next?

商品描述(中文翻譯)

使用TensorFlow的功能,如TensorBoard、TensorFlow.js、TensorFlow Probability和TensorFlow Lite,來建立智能自動化專案。

主要特點:
- 使用機器學習和深度學習原理來建立真實世界的專案
- 熟悉TensorFlow提供的各種模組
- 實施生成對抗網絡(GANs)、強化學習和膠囊網絡等專案

書籍描述:
TensorFlow已經改變了機器學習的認知方式。《TensorFlow機器學習專案》教你如何利用TensorFlow在各種真實世界的專案中利用其簡單、高效和靈活的優勢。通過這本書的幫助,你不僅會學習如何使用不同的數據集構建高級專案,還能夠使用TensorFlow生態系統中的各種庫來應對常見的挑戰。

首先,你將學習如何使用TensorFlow進行機器學習專案;你將使用TensorForest和TensorBoard來檢測外行星,使用TensorFlow.js進行情感分析,以及使用TensorFlow Lite進行數字分類。

隨著你閱讀本書,你將在各種真實世界的領域中建立專案,包括自然語言處理(NLP)、高斯過程、自編碼器、推薦系統和貝葉斯神經網絡,以及生成對抗網絡(GANs)、膠囊網絡和強化學習等熱門領域。你將學習如何使用TensorFlow on Spark API和使用TensorFlow進行GPU加速計算來檢測物體,然後訓練和開發循環神經網絡(RNN)模型來生成書籍劇本。

通過閱讀本書,你將獲得在工作中構建完整機器學習專案所需的專業知識。

你將學到什麼:
- 使用不同的數據集和技術了解TensorFlow生態系統
- 創建品質產品推薦系統
- 使用卷積神經網絡(CNNs)、自然語言處理(NLP)和貝葉斯神經網絡構建專案
- 使用深度強化學習玩Pac-Man
- 部署可擴展的基於TensorFlow的機器學習系統
- 使用循環神經網絡(RNNs)生成自己的書籍劇本

本書適合對TensorFlow有基本知識的數據分析師、數據科學家、機器學習專業人士或深度學習愛好者。如果你想使用監督、非監督和強化學習技術在機器學習領域中構建端到端專案,這本書也適合你。

目錄:
1. Tensorflow和機器學習概述
2. 使用機器學習在外太空中檢測外行星
3. 在瀏覽器中使用Tensorflow.js進行情感分析
4. 使用Tensorflow Lite進行數字分類
5. 使用NLP進行語音轉文字和主題提取
6. 使用高斯過程回歸預測股票價格
7. 使用自編碼器進行信用卡詐騙檢測
8. 使用貝葉斯神經網絡生成交通標誌分類器的不確定性
9. 使用DiscoGANs從鞋子圖像生成匹配的鞋袋
10. 使用膠囊網絡進行服裝圖像分類
11. 使用TensorFlow進行優質產品推薦
12. 使用Tensorflow進行大規模物體檢測
13. 使用LSTMs生成書籍劇本
14. 使用深度強化學習玩Pacman
15. 下一步是什麼?