Brink H., Richards J., Fetherolf M. Real-World Machine Learning

Manning, 2016. — 427 p. — ISBN: 1617291927, 9781617291920Real-World Machine Learning will teach you the concepts and techniques you need to be a successful machine learning practitioner without overdosing you on abstract theory and complex mathematics. By working through immediately relevant examples in Python, you'll build skills in data acquisition and modeling, classification, and regression. You'll also explore the most important tasks like model validation, optimization, scalability, and real-time streaming. When you're done, you'll be ready to successfully build, deploy, and maintain your own powerful ML systems.What's Inside• Predicting future behavior
• Performance evaluation and optimization
• Analyzing sentiment and making recommendationsNo prior machine learning experience assumed. Readers should know Python.Henrik Brink, Joseph Richards and Mark Fetherolf are experienced data scientists engaged in the daily practice of machine learning.