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Chapter 1. Training and Performance AssessmentChapter 2. Neural Networks Chapter 3. Overfitting and Regulation Chapter 4. Support Vector Machines Chapter 5. Random Forest, Bagging and Boosting of Decision Trees
'If you're applying machine learning to marketing or sales, this book is a must-have. It uniquely blends the theory with the practice, each chapter covering a machine learning algorithm and then illustrating its use for a commercially viable scenario. Seriously, that's not something you'll find in any other book.'
'Machine Learning and Artificial Intelligence in Marketing and Sales: Essential Reference for Practitioners and Data Scientists strikes a, difficult to achieve, balance between providing sufficient information on commonly used but complex machine learning and AI tools, and yet keeping the book accessible and applicable to business practitioners with technical orientation. This is a great introduction book for those who wish to know not only about machine learning and AI, but also what it really is, and how to apply it in marketing and sales settings.'
'This book is a great resource for Data scientists as a reference to anchor your technical understanding, build your intuition of the core machine learning models and at the same time elevate it for application in the real-world context of Marketing and Sales.'
'For readers well-versed in the Support Vector Machine, artificial neural nets, and deep learning, the book will be immediately useful. For readers new to these topics, the authors' accessible style lowers entry barriers. The book is required reading for managers, analysts, professors, and consultants involved in marketing and sales.'
'Syam and Kaul's book is a comprehensive treatise on data science of marketing, a rich and deeply informative dive into the next generation of marketing analytics solutions. The work comprehensively integrates the theoretical concepts of Machine Learning with practical applications of marketing, making it essential for either ML Engineers solving marketing problems or marketing analysts looking to get a rigorous treatment of the nascent science.'
'The authors have skillfully tailored the content to a wide audience. I found this book as a solid reference guide for students and a reference for data science practitioners alike. While the book covers the most important Machine Learning topics in lucid detail, it also provides insightful executive summaries, and, most importantly, showcases applications of each model in the practical world of Sales and Marketing. I will wholeheartedly recommend this book to anyone interested in learning Machine Learning and Artificial Intelligence.'