{"product_id":"math-for-deep-learning-isbn-9781718501904","title":"Math for Deep Learning","description":"\u003cb\u003e\u003ci\u003eMath for Deep Learning\u003c\/i\u003e provides the essential math you need to understand deep learning discussions, explore more complex implementations, and better use the deep learning toolkits.\u003c\/b\u003e\u003cbr\u003e\u003cbr\u003eWith \u003ci\u003eMath for Deep Learning\u003c\/i\u003e, you'll learn the essential mathematics used by and as a background for deep learning. \u003cbr\u003e\u003cbr\u003eYou’ll work through Python examples to learn key deep learning related topics in probability, statistics, linear algebra, differential calculus, and matrix calculus as well as how to implement data flow in a neural network, backpropagation, and gradient descent. You’ll also use Python to work through the mathematics that underlies those algorithms and even build a fully-functional neural network.\u003cbr\u003e\u003cbr\u003eIn addition you’ll find coverage of gradient descent including variations commonly used by the deep learning community: SGD, Adam, RMSprop, and Adagrad\/Adadelta.\u003cbr\u003e\u003cbr\u003e \u003cb\u003eIntroduction\u003c\/b\u003e\u003cbr\u003e\u003cb\u003eChapter 1:\u003c\/b\u003e Setting the Stage\u003cbr\u003e\u003cb\u003eChapter 2:\u003c\/b\u003e Probability\u003cbr\u003e\u003cb\u003eChapter 3:\u003c\/b\u003e More Probability\u003cbr\u003e\u003cb\u003eChapter 4:\u003c\/b\u003e Statistics\u003cbr\u003e\u003cb\u003eChapter 5:\u003c\/b\u003e Linear Algebra\u003cbr\u003e\u003cb\u003eChapter 6:\u003c\/b\u003e More Linear Algebra\u003cbr\u003e\u003cb\u003eChapter 7:\u003c\/b\u003e Differential Calculus\u003cbr\u003e\u003cb\u003eChapter 8:\u003c\/b\u003e Matrix Calculus\u003cbr\u003e\u003cb\u003eChapter 9:\u003c\/b\u003e Data Flow in Neural Networks\u003cbr\u003e\u003cb\u003eChapter 10:\u003c\/b\u003e Backpropagation\u003cbr\u003e\u003cb\u003eChapter 11:\u003c\/b\u003e Gradient Descent\u003cbr\u003e\u003cb\u003eAppendix:\u003c\/b\u003e Going Further\"An excellent resource for anyone looking to gain a solid foundation in the mathematics underlying deep learning algorithms. The book is accessible, well-organized, and provides clear explanations and practical examples of key mathematical concepts. I highly recommend it to anyone interested in this field.\"\u003cbr\u003e\u003cb\u003e—Daniel Gutierrez, insideBIGDATA\u003c\/b\u003e\u003cbr\u003e\u003cbr\u003e\"Ronald T. Kneusel has written a handy and compact guide to the mathematics of deep learning. It will be a well-worn reference for equations and algorithms for the student, scientist, and practitioner of neural networks and machine learning. Complete with equations, figures and even sample code in Python, this book is a wonderful mathematical introduction for the reader.\"\u003cbr\u003e\u003cb\u003e—David S. Mazel, Senior Engineer, Regulus-Group\u003c\/b\u003e\u003cbr\u003e\u003cbr\u003e\"What makes \u003ci\u003eMath for Deep Learning\u003c\/i\u003e a stand-out, is that it focuses on providing a sufficient mathematical foundation for deep learning, rather than attempting to cover all of deep learning, and introduce the needed math along the way. Those eager to master deep learning are sure to benefit from this foundation-before-house approach.\"\u003cbr\u003e\u003cb\u003e\u003cb\u003e—\u003c\/b\u003eEd Scott, Ph.D., Solutions Architect \u0026amp; IT Enthusiast\u003c\/b\u003e\u003cb\u003eRonald T. Kneusel \u003c\/b\u003eearned a PhD in machine learning from the University of Colorado, Boulder. He has over 20 years of machine learning industry experience. Kneusel is also the author of Numbers and Computers (2nd ed., Springer 2017), Random Numbers and Computers (Springer 2018), and Practical Deep Learning: A Python-Based Introduction (No Starch Press 2021).","brand":"No Starch Press","offers":[{"title":"Default Title","offer_id":46303747309797,"sku":"NP9781718501904","price":49.99,"currency_code":"USD","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/1842\/7735\/files\/9781718501904.jpg?v=1767732411","url":"https:\/\/k12savings.com\/products\/math-for-deep-learning-isbn-9781718501904","provider":"K12savings","version":"1.0","type":"link"}