TensorFlow Machine Learning Projects: Build 13 real-world projects with advanced numerical computations using the Python ecosystem
暫譯: TensorFlow 機器學習專案:使用 Python 生態系統構建 13 個真實世界專案,進行高級數值計算
Ankit Jain, Armando Fandango, Amita Kapoor
- 出版商: Packt Publishing
- 出版日期: 2018-11-30
- 售價: $1,660
- 貴賓價: 9.5 折 $1,577
- 語言: 英文
- 頁數: 322
- 裝訂: Paperback
- ISBN: 1789132215
- ISBN-13: 9781789132212
-
相關分類:
Python、程式語言、DeepLearning、TensorFlow、Machine Learning
-
相關翻譯:
TensorFlow機器學習項目開發實戰 (簡中版)
相關主題
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
- Overview of Tensorflow and Machine Learning
- Using Machine Learning to detect exoplanets in outer space
- Sentiment Analysis in your browser using Tensorflow.js
- Digit Classification using Tensorflow Lite
- Speech to text and topic extraction using NLP
- Predicting Stock Prices using Gaussian Process Regression
- Credit Card Fraud Detection using Autoencoders
- Generating Uncertainty in Traffic Signs Classifier using Bayesian Neural Networks
- Generating Matching Shoe Bags from Shoe Images Using DiscoGANs
- Classifying Clothing Images using Capsule Networks
- Making Quality Product Recommendations Using TensorFlow
- Object detection at a large scale with Tensorflow
- Generating Book Scripts Using LSTMs
- Playing Pacman using Deep Reinforcement Learning
- What is next?
商品描述(中文翻譯)
**實作 TensorFlow 的功能,如 TensorBoard、TensorFlow.js、TensorFlow Probability 和 TensorFlow Lite,以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則來建立實際專案
- 熟悉 TensorFlow 提供的各種模組
- 實作 GAN、強化學習和膠囊網路的專案
#### 書籍描述
TensorFlow 改變了人們對機器學習的看法。《TensorFlow 機器學習專案》教你如何利用 TensorFlow 在各種實際專案中的優勢——簡單性、效率和靈活性。藉由這本書,你不僅能學會如何使用不同的數據集來建立進階專案,還能利用 TensorFlow 生態系中的各種庫來解決常見挑戰。
首先,你將學會如何使用 TensorFlow 進行機器學習專案;你將探索使用 TensorForest 和 TensorBoard 來檢測系外行星、使用 TensorFlow.js 進行情感分析,以及使用 TensorFlow Lite 進行數字分類的各種專案。
在閱讀過程中,你將在各種實際領域中建立專案,涵蓋自然語言處理 (NLP)、高斯過程、自編碼器、推薦系統和貝葉斯神經網路,還有如生成對抗網路 (GAN)、膠囊網路和強化學習等熱門領域。你將學會如何使用 TensorFlow on Spark API 和 GPU 加速計算來檢測物體,接著學習如何訓練和開發一個循環神經網路 (RNN) 模型來生成書籍腳本。
在本書結束時,你將獲得在工作中建立完整機器學習專案所需的專業知識。
#### 你將學到的內容
- 使用各種數據集和技術理解 TensorFlow 生態系
- 創建質量產品推薦的推薦系統
- 使用 CNN、NLP 和貝葉斯神經網路建立專案
- 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 RNN 生成自己的書籍腳本
#### 本書適合誰
如果你是數據分析師、數據科學家、機器學習專業人士或對 TensorFlow 有基本了解的深度學習愛好者,那麼《TensorFlow 機器學習專案》適合你。如果你想在機器學習領域使用監督式、非監督式和強化學習技術建立端到端專案,這本書也適合你。
#### 目錄
1. TensorFlow 和機器學習概述
2. 使用機器學習檢測外太空中的系外行星
3. 使用 TensorFlow.js 在瀏覽器中進行情感分析
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價
7. 使用自編碼器進行信用卡詐騙檢測
8. 使用貝葉斯神經網路生成交通標誌分類的不確定性
9. 使用 DiscoGAN 從鞋子圖像生成配對鞋袋
10. 使用膠囊網路對服裝圖像進行分類
11. 使用 TensorFlow 進行質量產品推薦
12. 使用 TensorFlow 進行大規模物體檢測
13. 使用 LSTM 生成書籍腳本
14. 使用深度強化學習玩 Pacman
15. 接下來是什麼?