This book is written to provide a strong foundation in machine learning using Python libraries by providing real-life case studies and examples. It covers topics such as foundations of machine learning, introduction to Python, descriptive analytics and predictive analytics. Advanced machine learning concepts such as decision tree learning, random forest, boosting, recommended systems, and text analytics are covered. The book takes a balanced approach between theoretical understanding and practical applications. All the topics include real-world examples and provide step-by-step approach on how to explore, build, evaluate, and optimize machine learning models.
About the Author
U Dinesh Kumar is a Professor of Decision Sciences and Information Systems at IIM Bangalore. Dr Dinesh Kumar has published more than 60 research articles in leading academic journals. Twenty Eight of his case studies on Business Analytics based on Indian and multinational organizations such as Aavin Milk Dairy, Apollo Hospitals, Bigbasket, Bollywood, Hewlett and Packard, Larsen & Toubro, Mission Hospital, Hindustan Aeronautics Limited, Indian Premier League Manaranjan Pradhan, an alumnus of IIM Bangalore, has about 20 years of industry experience working on Cloud computing, Big Data & Machine Learning projects. He worked with TCS, HP, and iGATE before becoming a freelance consultant providing consulting and training on Big data, Machine Learning and Deep Learning. He has been teaching Big Data and Machine Learning for 4 years and has trained more than 1000 persons from several large MNCs including EMC, Cisco, Tesco, HP, Goldman Sachs, Software AG and Amadeus.
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