Название: Real-World Machine Learning Автор: Henrik Brink, Joseph Richards, Mark Fetherolf Издательство: Manning Publications Год: 2016 Страниц: 264 Формат: PDF Размер: 15 Mb Язык: English
Real-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.
Real-World Machine Learning is a practical guide designed to teach working developers the art of ML project execution. Without overdosing you on academic theory and complex mathematics, it introduces the day-to-day practice of machine learning, preparing you to successfully build and deploy powerful ML systems.
Predicting future behavior Performance evaluation and optimization Analyzing sentiment and making recommendations
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Real-World Machine Learning 
