Machine Learning with TensorFlow 1.x: Second generation machine learning with Google's brainchild - TensorFlow 1.x

Tackle common commercial machine learning problems with Google's TensorFlow 1.x library and build deployable solutions.

About This Book

• Enter the new era of second-generation machine learning with Python with this practical and insightful guide
• Set up TensorFlow 1.x for actual industrial use, including high-performance setup aspects such as multi-GPU support
• Create pipelines for training and using applying classifiers using raw real-world data

Who This Book Is For

This book is for data scientists and researchers who are looking to either migrate from an existing machine learning library or jump into a machine learning platform headfirst. The book is also for software developers who wish to learn deep learning by example. Particular focus is placed on solving commercial deep learning problems from several industries using TensorFlow's unique features. No commercial domain knowledge is required, but familiarity with Python and matrix math is expected.

What You Will Learn

• Explore how to use different machine learning models to ask different questions of your data
• Learn how to build deep neural networks using TensorFlow 1.x
• Cover key tasks such as clustering, sentiment analysis, and regression analysis using TensorFlow 1.x
• Find out how to write clean and elegant Python code that will optimize the strength of your algorithms
• Discover how to embed your machine learning model in a web application for increased accessibility
• Learn how to use multiple GPUs for faster training using AWS

In Detail

Google's TensorFlow is a game changer in the world of machine learning. It has made machine learning faster, simpler, and more accessible than ever before. This book will teach you how to easily get started with machine learning using the power of Python and TensorFlow 1.x.

Firstly, you'll cover the basic installation procedure and explore the capabilities of TensorFlow 1.x. This is followed by training and running the first classifier, and coverage of the unique features of the library including data flow graphs, training, and the visualization of performance with TensorBoard-all within an example-rich context using problems from multiple industries. You'll be able to further explore text and image analysis, and be introduced to CNN models and their setup in TensorFlow 1.x. Next, you'll implement a complete real-life production system from training to serving a deep learning model. As you advance you'll learn about Amazon Web Services (AWS) and create a deep neural network to solve a video action recognition problem. Lastly, you'll convert the Caffe model to TensorFlow and be introduced to the high-level TensorFlow library, TensorFlow-Slim.

By the end of this book, you will be geared up to take on any challenges of implementing TensorFlow 1.x in your machine learning environment.

Style and approach

This comprehensive guide will enable you to understand the latest advances in machine learning and will empower you to implement this knowledge in your machine learning environment.

使用Google的TensorFlow 1.x程式庫解決常見的商業機器學習問題，並建立可部署的解決方案。

關於本書：
- 進入第二代機器學習的新時代，使用Python進行實際的工業應用，本書提供實用且深入的指南。
- 設置TensorFlow 1.x以進行實際的工業應用，包括多GPU支援等高性能設置方面。
- 使用原始真實世界數據創建訓練和應用分類器的流程。

本書適合對象：
- 本書適合數據科學家和研究人員，他們希望從現有的機器學習庫遷移或直接進入機器學習平台。本書也適合希望通過實例學習深度學習的軟件開發人員。重點放在使用TensorFlow的獨特功能解決來自多個行業的商業深度學習問題上。不需要商業領域知識，但需要熟悉Python和矩陣數學。

你將學到什麼：
- 探索如何使用不同的機器學習模型對數據提出不同的問題。
- 學習如何使用TensorFlow 1.x構建深度神經網絡。
- 使用TensorFlow 1.x進行關鍵任務，如聚類、情感分析和回歸分析。
- 學習如何編寫乾淨優雅的Python代碼，優化算法的強度。
- 發現如何將機器學習模型嵌入Web應用程序，提高可訪問性。
- 學習如何使用AWS的多個GPU進行更快的訓練。

詳細內容：
- Google的TensorFlow在機器學習領域是一個改變者。它使機器學習比以往更快、更簡單、更易於接觸。本書將教你如何使用Python和TensorFlow 1.x輕鬆入門機器學習。
- 首先，你將了解基本的安裝程序，並探索TensorFlow 1.x的功能。然後進行訓練和運行第一個分類器，並介紹庫的獨特功能，包括數據流圖、訓練和使用TensorBoard進行性能可視化，並通過多個行業的問題進行實例演示。你還將進一步探索文本和圖像分析，並介紹在TensorFlow 1.x中設置CNN模型。接下來，你將實現一個完整的實際生產系統，從訓練到提供深度學習模型。隨著進一步的學習，你將了解Amazon Web Services（AWS），並創建一個深度神經網絡來解決視頻動作識別問題。最後，你將把Caffe模型轉換為TensorFlow，並介紹高級TensorFlow庫TensorFlow-Slim。
- 通過閱讀本書，你將準備好在機器學習環境中應對任何TensorFlow 1.x的挑戰。

風格和方法：
- 這本全面的指南將使你了解機器學習的最新進展，並使你能夠在機器學習環境中實施這些知識。