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MACHINE LEARNING & DEEP LEARNING USING P
MACHINE LEARNING & DEEP LEARNING USING P
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This textbook covers the principles and practices of machine learning and deep learning, with examples using Python and TensorFlow. It is accessible to students and working professionals with varying math skills and includes case studies from professional domains.
\n Format: Paperback
\n Length: 560 pages
\n Publication date: 08 March 2021
\n Publisher: MCGRAW HILL PROFESSIONAL
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Publisher's Note: Products purchased from Third Party sellers are not guaranteed by the publisher for quality, authenticity, or access to any online entitlements included with the product.
Explore the principles and practices of machine learning and deep learning in this comprehensive textbook, designed to be accessible to students and working professionals with varying math skills. You will delve into the theories and applications of machine learning and deep learning, covering topics such as data handling, regression and logistic regression, decision trees, cross-validation techniques, error testing, artificial neural networks (ANN, CNN, and RNN), random forests, boosting, and more.
Machine Learning and Deep Learning Using Python and TensorFlow offers valuable case studies across professional domains, including banking, insurance, e-commerce, retail, and healthcare. The book showcases examples using both Python and TensorFlow programming languages, demonstrating how to leverage this cutting-edge technology in today's "smart" devices.
Presented in a mathematically non-rigorous way, this textbook is ideal for those seeking a deeper understanding of machine learning and deep learning without the technical complexities. It includes image classification and computer vision tasks, providing practical insights into these emerging fields.
Written by a pair of business analytics experts, this textbook is a valuable resource for anyone looking to apply machine learning and deep learning in their professional endeavors.
\n Weight: 1180g\n
Dimension: 262 x 211 x 33 (mm)\n
ISBN-13: 9781260462296\n \n
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