Explore the principles and practices of machine learning and deep learning This comprehensive textbook lays out the theories and applications of machine learning and deep learning in a style that is approachable for students and working professionals at all math skill levels. Readers will discover how to handle data, regression and logistic regression, decision trees, cross-validation techniques and error testing, artificial neural networks (ANN, CNN and RNN), random forests, boosting, and more. Machine Learning and Deep Learning Using Python and TensorFlow includes valuable case studies across professional domains, including banking, insurance, e-commerce, retail, and healthcare. The book presents examples using both Python and TensorFlow programming languages and clearly demonstrates how to utilize this cutting-edge technology in today’s “smart” devices. 1.) Presented in a mathematically non-rigorous way 2.) Includes image classification and computer vision tasks 3.) Written by a pair of business analytics experts
Venkata Reddy Konasani (Vijayawada, Andhra Pradesh, India) is a data scientist and corporate trainer with experience in credit risk modeling, market response model building, social media analytics, and machine learning and deep learning. He holds a Master's degree in applied statistics and informatics from IIT Bombay. Shailendra Kadre (Bangalore, Karnataka, India) works at Hewlett Packard and holds a master?s degree in mechanical engineering from IIT Delhi. He is the author of two books and numerous articles dealing with business analytics.
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