This is the second edition of a popular book originally by author Sebastian Raschka that contains a mix of practical information and techniques on machine learning, deep learning, and modern data analysis. It has been updated using the latest Python open source libraries and now includes the TensorFlow deep learning library. The scikit-learn code has also been fully updated to include recent improvements and additions to the machine learning library.

Author: Sebastian Raschka and Vahid Mirjalili
Publisher: Packt
Date: September 2017
Pages: 622
ISBN: 978-1787125933
Print: 1787125939
Kindle: B0742K7HYF
Audience: Python developers interested in machine learning
Level: Intermediate
Category: Artificial Intelligence

• Understand the key frameworks in data science, machine learning, and deep learning
• Harness the power of the latest Python open source libraries in machine learning
• Explore machine learning techniques using challenging real-world data
• Master deep neural network implementation using the TensorFlow library
• Learn the mechanics of classification algorithms to implement the best tool for the job
• Predict continuous target outcomes using regression analysis
• Uncover hidden patterns and structures in data with clustering
• Delve deeper into textual and social media data using sentiment analysis

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