Practical Machine Learning in Python by Malcolm Gloyer

Recent technology developments have facilitated machine learning on laptops. Most publications on this subject concentrate on teaching technology by using trivial examples to help readers understand the technological concepts resulting in technical proficiency but a lack of understanding how to (or being overwhelmed by the complexity when starting to) apply machine learning to real world problems. This book will deal with both the technology and the practical application of machine learning technology by explaining, via case studies presented in the appendices, how machine learning can be implemented to demonstrate artificial intelligence and draw inference from practical, real world problems.

Malcolm Gloyer, Chartered Member of the Chartered Institute for Securities and Investments explains some solutions to the challenges of practical machine learning in Python. As a Certified Practicing Project Manager (CPPM MAIPM), Malcolm has more than 30 years' experience working on projects in the UK and Australia, specialising in data strategy, market and credit risk, derivatives, commodities and artificial intelligence.

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