Linear Algebra and Learning from Data Audible –

Linear Algebra and Learning from Data Linear Algebra And The Foundations Of Deep Learning, Together At Last From Professor Gilbert Strang, Acclaimed Author Of Introduction To Linear Algebra, Comes Linear Algebra And Learning From Data, The First Textbook That Teaches Linear Algebra Together With Deep Learning And Neural Nets This Readable Yet Rigorous Textbook Contains A Complete Course In The Linear Algebra And Related Mathematics That Students Need To Know To Get To Grips With Learning From Data Included Are The Four Fundamental Subspaces, Singular Value Decompositions, Special Matrices, Large Matrix Computation Techniques, Compressed Sensing, Probability And Statistics, Optimization, The Architecture Of Neural Nets, Stochastic Gradient Descent And Backpropagation

7 thoughts on “Linear Algebra and Learning from Data

  1. Antonio M. Antonio M. says:

    Es un libro excelente, novedoso e innovador que me esta ayudando a mis clases en al Universidad

  2. Àlvar Martín Llopis Àlvar Martín Llopis says:

    Molt bon llibre sobre statistical learning

  3. J. T. G. J. T. G. says:

    Prof Strang has been writing intoductory linear algebra books since the mid nineteen seventies All of them good In this book he sharply departs from his own and ever other book in introductory presentation and presents the outer product at the same level of detail as the inner product This clarifies many applications, by

  4. BB BB says:

    I learned about this book while looking for a suitable textbook for an intermediate undergraduate course in applied linear algebra Its title and the table of contents suggested that it would be a very good text for such course, diving into topics usually omitted in introductory courses, and linking them to modern application

  5. Dr. Darrin Rasberry Dr. Darrin Rasberry says:

    While not a full on linear algebra book despite the title , this does serve as a perfect undergraduate level introduction to the Machine Learning galaxy and its many, many applications and increasingly popular methodology Computer scientists, mathematicians and engineers as well as math savvy economists and businesspeople could

  6. Matthew Matthew says:

    This book relates two essential topics linear algebra and deep learning Prof Strang sees statistics and optimization as two supplementary topics which bridge the main subjects This book organizes central methods and ideas of data science and provides insight into how linear algebra gives expression to those ideas.

  7. gibonious gibonious says:

    Prof Strang is just a masterful teacher, a teacher s teacher I have followed him for years via both his online lectures and his books, and neither this book nor the companion online course disappoint It is all the admirable that even late in his career he has stayed current in his field he is quite the guru of applied linear algebra an

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