Building Machine Learning Systems With Python

As the Big Data explosion continues at an almost incomprehensible rate, being able to understand and process it becomes even more challenging. With Building Machine Learning Systems with Python, you'll learn everything you need to tackle the modern data deluge - by harnessing the unique capabilities of Python and its extensive range of numerical and scientific libraries, you will be able to create complex algorithms that can 'learn' from data, allowing you to uncover patterns, make predictions, and gain a more in-depth understanding of your data.

Featuring a wealth of real-world examples, this book provides gives you with an accessible route into Python machine learning. Learn the Iris dataset, find out how to build complex classifiers, and get to grips with clustering through practical examples that deliver complex ideas with clarity. Dig deeper into machine learning, and discover guidance on classification and regression, with practical machine learning projects outlining effective strategies for sentiment analysis and basket analysis. The book also takes you through the latest in computer vision, demonstrating how image processing can be used for pattern recognition, as well as showing you how to get a clearer picture of your data and trends by using dimensionality reduction.

Keep up to speed with one of the most exciting trends to emerge from the world of data science and dig deeper into your data with Python with this unique data science tutorial.

Learn how to create machine learning algorithms using the flexibility of Python

Get to grips with scikit-learn and other Python scientific libraries that support machine learning projects

Employ computer vision using mahotas for image processing that will help you uncover patterns and trends in your data

Learn topic modelling and build a topic model for Wikipedia

Analyze Twitter data using sentiment analysis

Get to grips with classification and regression with real-world examples

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About the Author

Willi Richert

Willi Richert has a PhD in Machine Learning/Robotics and currently works for Microsoft in the Bing Core Relevance Team. He performs statistical machine translation.

Luis Pedro Coelho

Luis Pedro Coelho is a Computational Biologist: someone who uses computers as a tool to understand biological systems. Within this large field, Luis works in Bioimage Informatics, which is the application of machine learning techniques to the analysis of images of biological specimens. His main focus is on the processing of large scale image data. With robotic microscopes, it is possible to acquire hundreds of thousands of images in a day, and visual inspection of all the images becomes impossible. Luis has a PhD from Carnegie Mellon University, which is one of the leading universities in the world in the area of machine learning. He is also the author of several scientific publications. Luis started developing open source software in 1998 as a way to apply to real code what he was learning in his computer science courses at the Technical University of Lisbon. In 2004, he started developing in Python and has contributed to several open source libraries in this language. He is the lead developer on mahotas, the popular computer vision package for Python, and is the contributor of several machine learning codes..