Building Machine Learning Systems with Python : Bring the power of scikit-learn, keras, tensorflow and much more, 3/e (Paperback)

Get more from your data through creating practical machine learning systems with Python

Key Features

• Build your own Python-based machine learning systems tailored to solve any problem
• Gain the best use of tools and build your own systems to carry out tasks such as classification, sentiment analysis, reinforcement learning, GAN, autoencoders, neural netoworks any many other areas
• Includes practical examples to learn how to build systems that can be applied to text, images to solve real world problems

Book Description

Machine learning allow models or systems to learn without being explicitly programmed. Python is one of the preferable language which is used to develop machine learning applications banking on its extensive library support. The book Building Machine Learning Systems with Python, Third Edition will address the trending domains by covering the most used data-sets to build practical machine learning systems.

Using machine learning to gain deeper insights from data is a key skill required by modern application developers and analysts alike. Python, being a dynamic language, it allows for fast exploration and experimentation. With its excellent collection of open source machine learning libraries you can focus on the task at hand while being able to quickly try out many ideas. This book shows you exactly how to find patterns in your raw data. You will start by brushing up on your Python machine learning knowledge and introducing libraries. You'll quickly get to grips with serious, real-world projects on data-sets, using modeling, creating recommendation systems. With this book, you gain the tools and understanding required to build your own systems, tailored to solve your real-world data analysis problems.

By the end of this book you will be able to build machine learning systems doing tasks such as classification, sentiment analysis, reinforcement learning, GAN, autoencoders and many more

What you will learn

• Build a classification system that can be applied to text, images, or sounds
• Employ Amazon Web Services to run analysis on the cloud
• Solve problems related to regression using Tensorflow
• Explore the steps to add collaborative filtering using Tensorflow
• Understand different ways to apply DNN (Deep Neural Networks) on structured data

Who This Book Is For

This book is intended for Python developers who wants to learn how to build machine leanring systems with growing complexties. We will be using Python's machine learning capabilities to develop effective solutions at work.

透過使用Python創建實用的機器學習系統，讓您從數據中獲得更多價值。

主要特點：

- 構建自己的基於Python的機器學習系統，以解決任何問題
- 充分利用工具，構建自己的系統，執行分類、情感分析、強化學習、GAN、自編碼器、神經網絡等任務
- 包含實際示例，學習如何構建可應用於文本、圖像的系統，解決現實世界問題

書籍描述：

機器學習使模型或系統能夠在不需要明確編程的情況下進行學習。Python是一種常用的語言，用於開發依賴其廣泛庫支持的機器學習應用。《Python機器學習系統構建》第三版將涵蓋最常用的數據集，以構建實用的機器學習系統。

利用機器學習從數據中獲得更深入的洞察力是現代應用程序開發人員和分析師所需的關鍵技能。Python作為一種動態語言，可以進行快速探索和實驗。憑藉其出色的開源機器學習庫集合，您可以專注於手頭的任務，同時能夠快速嘗試許多想法。本書將向您展示如何在原始數據中找到模式。您將從複習Python機器學習知識並介紹庫開始。您將迅速掌握在數據集上進行嚴肅的實際項目，使用建模、創建推薦系統等技術。通過本書，您將獲得構建自己的系統所需的工具和理解，以解決現實世界的數據分析問題。

通過本書，您將能夠構建執行分類、情感分析、強化學習、GAN、自編碼器等任務的機器學習系統。

您將學到：

- 構建可應用於文本、圖像或聲音的分類系統
- 使用Amazon Web Services在雲端上進行分析
- 使用Tensorflow解決與回歸相關的問題
- 探索使用Tensorflow添加協同過濾的步驟
- 了解在結構化數據上應用DNN（深度神經網絡）的不同方法

本書適合對Python開發人員，他們希望學習如何構建越來越複雜的機器學習系統。我們將使用Python的機器學習能力來開發有效的解決方案。