#70 overall
Linear Algebra
Khan Academy
7 recommenders · 7 threads · recommended in 5 years, 2011–2024 · score 7.2
Khan Academy's free online Linear Algebra course, a set of video lessons and exercises covering vectors, matrices, and related practical topics. Commenters describe it as accessible and in places less coherent than other resources.
Commenters call it very accessible and thorough, and useful as a prerequisite for machine learning and statistics.
Mathematicsbeginnerfreeinteractive MOOC#linear algebra#vectors#matrices#khan academy#math prerequisites
Recommendations by year
20062026
Just FYI, Kahn Academy's Linear Algebra course is great. Very thorough and well-thought-out.
Khan academy will teach you all of pre-k, high-school, pre-calc, calculus and infinite series pretty well. mathsisfun.com is a great resource if that's ever lacking. High school physics on khan is good to give you a practical application of the concepts if they seem too abstract.
I found Strang's youtube lectures the best for linear algebra along with 'vector maths for 3d graphic'. Khan's linear algebra course seems like more a collection of practical things you can do with linear algebra rather than a coherent cource but it's still a great resource.
Khan academy's multi-variable calculus is good enough to give you a reasonable grasp, but I'd call it a good complement rather than sole resource.
I've tended to go through the cycle of watching the lectures, then doing the exercises, going forward, going back after a few months to ensure I understand the whys and not just the hows, and then writing my own notes. Machine Learning et al is a great practical application of all this maths.
- MIT 18.06 - https://ocw.mit.edu/courses/mathematics/18-06-linear-algebra... - The lectures and the textbook for the course are a default recommendation.
- Linear Algebra Done Right - This is a textbook, there are also youtube videos from the author - https://www.youtube.com/playlist?list=PLGAnmvB9m7zOBVCZBUUmS...
- Khan Academy - https://www.khanacademy.org/math/linear-algebra - Also a good place to start, very accessible, missing some of the more advanced material.
- 3blue1brown - https://www.youtube.com/playlist?list=PLZHQObOWTQDPD3MizzM2x... - These videos are good but they're more of a nice overview than a way to learn.
Good post. I want to add several great resources.
- Grokking Deep Learning
https://www.manning.com/books/grokking-deep-learning
This is a fantastic book that assumes no prerequisites other than knowing python, and takes you through the fundamentals of DL. It has very intuitive and easy to follow explanations, and doesn't use any libraries other than NumPy, so you're building the whole thing yourself, from scratch.
- Deep Learning With Python
https://machinelearningmastery.com/deep-learning-with-python...
This is kind of the opposite of the previous one, it doesn't go into math and theory, instead it guides you through building several practical projects with a very simple to use DL library(keras). It's a great way to gain practical experience in addition to theory from the previous book. Also has no prerequisites other than python, and makes it very easy to get started.
- 3blue1brown videos on neural networks:
https://www.youtube.com/playlist?list=PLZHQObOWTQDNU6R1_6700...
Extremely brilliant high-level concise overview of how ANNs work. I highly recommend you get started here. You should also check out his videos on calulus and linear algebra, they're fantastic way to learn the math you need.
- Khan Academy videos - one of the easiest ways to learn the math prerequisites.
Calculus:
https://www.khanacademy.org/math/calculus-home
Linear Algebra:
https://www.khanacademy.org/math/linear-algebra
Probability and Statistics:
https://www.khanacademy.org/math/statistics-probability
- Hands-On Machine Learning with Scikit-Learn and TensorFlow
http://shop.oreilly.com/product/0636920052289.do
I haven't read this one yet, but it looks very promising, and a lot of people seem to find it very useful.
- Andrew Ng's Coursera course
https://www.coursera.org/learn/machine-learning
Everyone knows about this one, I just think every article on AI resources should mention it, one of the most popular ways to get started with ML.
- New MIT courses on Self-Driving cars and AGI
https://selfdrivingcars.mit.edu
https://agi.mit.edu
- The Master Algorithm
https://www.audible.com/pd/Science-Technology/The-Master-Alg...
Excellent high-level overview of ML field and algorithms.
====
Other great stuff:
- Artificial Intelligence: A Modern Approach
http://aima.cs.berkeley.edu/
The leading textbook in Artificial Intelligence. It's not the fastest way to get started, but it's considered one of the best AI textbooks ever written.
- Stanford AI course (CS 188)
https://www.youtube.com/playlist?list=PLIeooNSdhQE5kRrB71yu5...
Brilliant course based on AIMA. Not DL, but solid fundamentals of AI and ML.
- Couple of great playlists on DL, just to complete the collection:
Machine Learning with Python
https://www.youtube.com/playlist?list=PLQVvvaa0QuDfKTOs3Keq_...
Neural Networks Demystified
https://www.youtube.com/watch?v=bxe2T-V8XRs&index=1&list=PLi...
Has anyone completed the Calculus courses on Khan Academy (Integral, Differential and Multivariable)? If so, would you recommend Khan Academy for Calculus instead of the resources mentioned on Better Explained? I'm working through the Linear Algebra courses now on KA and they are very good.
Note for anyone signing up for this who has been in industry for a while: the prerequisites for this class really are prerequisites and it can be quite difficult to follow along if you're too busy trying to get your head around the basic math. You can check out the existing lectures on iTunes U to see what I mean.
Completing the Khan Academy playlists for Linear Algebra and Probability would be pretty useful if you want to be prepared in time for October.
Khan Academy has actually covered everything I've gone through in my statistics class and linear algebra classes, so I'll recommend that as I'm going two semesters with AIMA the upcoming year.
http://www.khanacademy.org/#linear-algebra
http://www.khanacademy.org/#probability
http://www.khanacademy.org/#statistics
A couple of friends recommended these:- (Not sure if they are relevant though for deep learning specifically)
1) http://ocw.mit.edu/courses/mathematics/18-06-linear-algebra-... 2) https://www.khanacademy.org/math/linear-algebra/vectors_and_...
If anyone knows anything else (relevant to deep learning) could you please share :)