Machine Learning For Absolute Beginners
by Oliver Theobald · first published 2017
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I studied Physics in college, so I mostly knew the Math. Here's what I used to self-learn: 1. Machine Learning for Absolute Beginners by Oliver Theobald 2. ISLR 3. Machine Learning by Andrew Ng on Coursera 4. Deep Learning by Andrew Ng on Coursera 5. fast.ai 6. Sebastian Raschka's PyTorch book Good Math refreshers: 1. Mathematics…
on “Google just released a 100% free learning path on Generative AI with 9 Courses” ↗…really easy. - There are a number of paths you can go from there. Here's what I did. -- IBM Data Science Professional Certificate (not deep at all, but lays out the landscape well; did it in a week) -- Machine Learning for Absolute Beginners by Oliver Theobald which you can finish in an evening. -- Machine Learning Specialization by Andrew Ng on Coursera. -- Deep Learning Specialization by Andrew Ng on Coursera. -- fast.ai course. - Learn…
on “Ask HN: How to Break into AI Engineering” ↗…be Khan Academy and knowing your gaps. Fill your gaps. Learn HS level Calculus, Linear Algebra, and Statistics. You will need more Calculus and Linear Algebra later. But not now. Then try studying "Machine Learning for Absolute Beginners" book. It not very mathy. Then just keep going through ML courses. Learn what you need on the way. The "way" of math needed in Machine Learning is not the same "way" that brings you scores in school/college…
on “Ask HN: How to learn math from zero for adults?” ↗