Applied Machine Learning | Gopal M. | Second Edition | McGraw Hill Publication ( English Medium )

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Applied Machine Learning | Gopal M. | Second Edition | McGraw Hill Publication ( English Medium )

Applied Machine Learning, Second Edition by Gopal M. is a comprehensive guide for anyone looking to delve into the world of machine learning and its practical applications. This updated edition provides readers with a solid foundation in the fundamentals of machine learning while also offering insights into advanced techniques and real-world case studies. The book covers key topics such as data preprocessing, feature engineering, model selection, evaluation metrics, and deployment strategies. Readers will learn how to build and train machine learning models using popular algorithms such as linear regression, logistic regression, decision trees, random forests, support vector machines, and neural networks. One of the standout features of this book is its focus on hands-on exercises and projects that allow readers to apply their knowledge in a practical setting. The author provides step-by-step instructions for implementing machine learning algorithms in Python using popular libraries such as scikit-learn and TensorFlow. By working through these exercises, readers will gain valuable experience in solving real-world problems using machine learning techniques. In addition to covering traditional supervised and unsupervised learning methods, Applied Machine Learning also explores cutting-edge topics such as deep learning, reinforcement learning, natural language processing, and computer vision. The book offers a comprehensive overview of these advanced techniques along with examples of how they can be applied in various domains such as healthcare, finance, marketing, and more. Whether you are a beginner looking to learn the basics of machine learning or an experienced practitioner seeking to expand your skills, Applied Machine Learning has something to offer for everyone. With its clear explanations, practical examples, and hands-on exercises, this book is an invaluable resource for anyone interested in harnessing the power of machine learning to solve complex problems.

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Product Details

SKU / BOOK Code:	McGraw-App-Mach-Learn-(E)
Publisher:	McGraw Hill
Author:	Gopal M.
Binding Type:	Paperback
No. of Pages:	522
ISBN-10:	9354601590
ISBN-13:	9789354601590
Edition:	Second Edition
Language:	English Medium
Publish Year:	2021-12
Weight (g):	950
Product Condition:	New
Reading Age:	Above 18 Years
Country of Origin:	India
Genre:	Textbooks & Study Guides
Manufacturer:	McGraw Hill
Importer:	McGraw Hill
Packer:	Fullfilled by Supplier

Product Description

Applied Machine Learning | Gopal M. | Second Edition | McGraw Hill Publication ( English Medium )

Applied Machine Learning, Second Edition by Gopal M. is a comprehensive guide for anyone looking to delve into the world of machine learning and its practical applications. This updated edition provides readers with a solid foundation in the fundamentals of machine learning while also offering insights into advanced techniques and real-world case studies. The book covers key topics such as data preprocessing, feature engineering, model selection, evaluation metrics, and deployment strategies. Readers will learn how to build and train machine learning models using popular algorithms such as linear regression, logistic regression, decision trees, random forests, support vector machines, and neural networks. One of the standout features of this book is its focus on hands-on exercises and projects that allow readers to apply their knowledge in a practical setting. The author provides step-by-step instructions for implementing machine learning algorithms in Python using popular libraries such as scikit-learn and TensorFlow. By working through these exercises, readers will gain valuable experience in solving real-world problems using machine learning techniques. In addition to covering traditional supervised and unsupervised learning methods, Applied Machine Learning also explores cutting-edge topics such as deep learning, reinforcement learning, natural language processing, and computer vision. The book offers a comprehensive overview of these advanced techniques along with examples of how they can be applied in various domains such as healthcare, finance, marketing, and more. Whether you are a beginner looking to learn the basics of machine learning or an experienced practitioner seeking to expand your skills, Applied Machine Learning has something to offer for everyone. With its clear explanations, practical examples, and hands-on exercises, this book is an invaluable resource for anyone interested in harnessing the power of machine learning to solve complex problems.

Search Keywords - Applied Machine Learning Gopal M, Applied Machine Learning Second Edition, McGraw Hill Publication Applied Machine Learning, Best Book on Machine Learning, Practical Guide to Machine Learning, Machine Learning Algorithms Explained, Hands-On Machine Learning Projects, Python for Machine Learning, Data Preprocessing Techniques, Feature Engineering in Machine Learning, Model Selection Strategies, Evaluation Metrics for Machine Learning Models, Deployment Strategies for ML Models, Deep Learning Applications, Reinforcement Learning Examples, Natural Language Processing Tutorial, Computer Vision Projects, Machine Learning Case Studies, Machine Learning Books for Beginners, Advanced Techniques in Machine Learning

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