Building Machine Learning Systems with Python

by Luis Pedro Coelho, Willi Richert

Get more from your data through creating practical machine learning systems with PythonAbout This BookBuild your own Python-based machine learning systems tailored to solve any problemDiscover how Python offers a multiple context solution for create machine learning systemsPractical scenarios using the key Python machine learning libraries to successfully implement in your projectsWho This Book Is ForThis 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.

What You Will LearnBuild a classification system that can be applied to text, images, or soundsUse NumPy, SciPy, scikit-learn – scientific Python open source libraries for scientific computing and machine learningExplore the mahotas library for image processing and computer visionBuild a topic model for the whole of WikipediaEmploy Amazon Web Services to run analysis on the cloudDebug machine learning problemsGet to grips with recommendations using basket analysisRecommend products to users based on past purchasesIn DetailUsing 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.

With this book, you gain the tools and understanding required to build your own systems, tailored to solve your real-world data analysis problems.

Genres: Computer Science

328 pages, Kindle Edition

First published March 26, 2015

Reviews

[Ahmet Fuat · Rating 3 out of 5]

Approaching to ML algorithms and examples are nice. But code pieces of examples are really bad. So many errors are there and sometimes you are confused which code pieces belong to where. I recommend you to just read the book and not try to implement specified code pieces.