Building Machine Learning Systems with Python, 2nd Edition: Get more from your data through creating practical machine learning systems with Python

Using machine learning to gain deeper insights from data is a key skill required by modern application developers and analysts alike. Python is a wonderful language to develop machine learning applications. As 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 datasets, using modeling, creating recommendation systems. Later on, the book covers advanced topics such as topic modeling, basket analysis, and cloud computing. These will extend your abilities and enable you to create large complex systems.

About This Book

• Build full-featured web applications, such as Spring MVC applications, efficiently that will get you up and running with Spring web development
• Reuse working code snippets handy for integration scenarios such as Twitter, e-mail, FTP, databases, and many others
• An advanced guide which includes Java programs to integrate Spring with Thymeleaf

Who This Book Is For

If you are a Java developer with experience in developing applications with Spring, then this book is perfect for you. A good working knowledge of Spring programming conventions and applying dependency injections is recommended to make the most of this book.

This book primarily targets Python developers who want to learn and use Python's machine learning capabilities and gain valuable insights from data to develop effective solutions for business problems.