Making Buddies with Machine Studying was a legendary internal-only Google course specifically created to encourage freshmen and amuse consultants. As we speak, it’s accessible to everybody! Now you can take pleasure in it by following these hyperlinks:
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Half 1 — Introduction to ML: bit.ly/mfml_part1
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Half 2 — Lifetime of a Machine Studying Venture: bit.ly/mfml_part2
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Half three — AI from Prototype and Manufacturing: bit.ly/mfml_part3
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Half four — Opening the Black Field: bit.ly/mfml_part4
In regards to the course
The course is designed to provide the instruments you want for efficient participation in machine studying for fixing enterprise issues and for being a superb citizen in an more and more AI-fueled world. MFML is ideal for all people; it focuses on conceptual understanding (reasonably than the mathematical and programming particulars) and guides you thru the concepts that kind the idea of profitable approaches to machine studying. It has one thing for everybody!
After finishing this course, you’ll:
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achieve an intuitive and proper understanding of core machine studying ideas.
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perceive the flavour of a number of standard machine studying strategies.
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keep away from frequent errors in machine studying.
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know the way machine studying might help your endeavors.
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achieve perception into the steps concerned in main machine studying tasks from conception to launch and past.
Chapter by chapter
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Half 1 — Introduction to ML
- Half 2 — Lifetime of a Machine Studying Venture
- Half three — AI from Prototype and Manufacturing
- Half four — Opening the Black Field
Whereas the primary three components targeted on supplying you with the ideas and roadmaps to guide a profitable utilized machine studying venture, Half four indulges your curiosity about what’s happening underneath the hood. The ultimate chapter covers the instinct behind:
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Clustering and k-Means
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Lazy studying and k-NN
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Perceptron
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Maximal Margin Classifier
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Help Vector Classifier
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Help Vector Machines
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Choice Timber
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Boosted Aggregation
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Random Forests
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Ensemble Fashions
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Naive Bayes
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Linear Regression
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Logistic Regression
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Neural Networks / Deep Studying
You’ll achieve insights into an entire bunch of algorithms… all with out having to check the equations. To be truthful, these equations are what’s already in all of the textbooks, so the purpose of this course was to present you one thing you’ll be able to’t get elsewhere. It’s all about instinct and conceptual understanding. Fortunately, after you’ve absorbed the instinct, these equations will make way more sense if/once you do select to check them.
