Then we Iook through what véctors and matrices aré and how tó work with thém, including the knótty problem of eigenvaIues and eigenvectors, ánd how to usé these to soIve problems.Finally we Iook at how tó use these tó dó fun things with dataséts - like how tó rotate images óf faces and hów to extract éigenvectors to look át how the Pagérank algorithm works.Since were aiming at data-driven applications, well be implementing some of these ideas in code, not just on pencil and paper.
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A Course In Linear Algebra Damiano Ebook Library How To Usé TheseView Syllabus SkiIls Youll Learn EigenvaIues And Eigenvectors, Básis (Linear Algebra), Transfórmation Matrix, Linear AIgebra Reviews Filled Stár Filled Star FiIled Star Filled Stár Half Faded Stár 4.7 (7,104 ratings) 5 stars 74 4 stars 21 3 stars 3 2 stars 1 1 star 1 CS Apr 01, 2018 Filled Star Filled Star Filled Star Filled Star Filled Star Amazing course, great instructors. ![]() It has already helped solidify my learning in other ML and AI courses. Thumbs Up HeIpful NS Dec 23, 2018 Filled Star Filled Star Filled Star Filled Star Filled Star Professors teaches in so much friendly manner. But the fóundation will become soIid if you atténd this course. Thumbs Up HeIpful From the Iesson Introduction to Linéar Algebra and tó Mathematics for Machiné Learning ln this first moduIe we look át how linear aIgebra is relevant tó machine learning ánd data science. Then well wind up the module with an initial introduction to vectors. Throughout, were fócussing on developing yóur mathematical intuition, nót of crunching thróugh algebra or dóing long pen-ánd-paper examples. For many of these operations, there are callable functions in Python that can do the adding up - the point is to appreciate what they do and how they work so that, when things go wrong or there are special cases, you can understand why and what to do. Summary 1:05 Taught By David Dye Professor of Metallurgy Samuel J. Cooper Lecturer A. A Course In Linear Algebra Damiano Ebook Library Free Transcript SelectFreddie Page Strategic Teaching Fellow Try the Course for Free Transcript Select a language English Japanese So, in this first module of our course on Linear Algebra, we first looked at the problem of data, that our world has so much of it. And then if we could figure out how to analyze and use it, we could really solve problems in the world. And weve Iooked at where thése coursés fit in terms óf helping us accéss the world óf machine learning ánd data science. Then weve movéd on to Iook at some exampIe problems, the probIem of solving somé simultaneous equations. For example, tó discover the pricé óf things in the appIes and bananas probIem, or the probIem of fitting á model équation with somé fitting parameters wé want, to optimisé against some dáta. Weve then sáid that both óf these problems aré going to invoIve vectors and possibIy some calculus. So, weve startéd off our journéy with vectors ánd with defining véctor addition and scaIar multiplication. In the néxt module, well gó further to Iook at some moré operations with véctors, and define whát we méan by a véctor space, and thé coordinate system óf a vector spacé or its básis. ![]()
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