With so many ML boot camps, books, and online courses, I would like to remind you about some of the free machine learning courses from Stanford.
I took my first machine learning course from Andrew Ng before the start of coursera.org, and it was one of the best courses that I have taken.
Stanford
CS224W: Machine Learning with Graphs
Home page: http://web.stanford.edu/class/cs224w/
Youtube link: https://www.youtube.com/playlist?list=PLoROMvodv4rPLKxIpqhjhPgdQy7imNkDn
Free book: https://www.cs.mcgill.ca/~wlh/grl_book/
Hotness: ★★
This is a course about learning graphic representation to do better prediction. This is a new frontier of machine learning research because most traditional ML models are sequence and grid centric.
CS 329S: Machine Learning Systems Design
Home page: https://stanford-cs329s.github.io/
Free auditing: it starts in Spring 2022 and you can sign up to audit the class live
Hotness: ★★★★★
This is a great course that is more on the practical side. It’s definitely great for industry experience and interview preparation.
CS224N: NLP with Deep Learning
Home page: http://web.stanford.edu/class/cs224n/
Youtube link: https://www.youtube.com/playlist?list=PLoROMvodv4rOhcuXMZkNm7j3fVwBBY42z
Hotness: ★★★★★
This is a great introductory course on NLP (natural language process), but you do need some background in deep learning. Previously, NLP was taught without deep learning but the trend has shifted so there is very good reason to jump straight to deep learning when taking on NLP tasks.
Stanford MLSys Seminar Series
Youtube link: https://www.youtube.com/playlist?list=PLSrTvUm384I9PV10koj_cqit9OfbJXEkq
Hotness: ★★★
This is not exactly a course but a seminar. It’s a great way to hear the practical experiences that people can offer in their ML journey. It does not deep dive into any topic but gives you a sense of various challenges people face in practice. It can be an inspiration for you to think about what in ML that motivates you.
CS330: Multi-Task and Meta-Learning
Home page: https://cs330.stanford.edu/
Youtube link: https://www.youtube.com/playlist?list=PLoROMvodv4rMC6zfYmnD7UG3LVvwaITY5
Hotness: ★★★
This is a more advanced course on ML. Multi-task and meta learning is definite a new trend in the industry. We are basically trying to learn better and quicker in a sense. It is an active area of research that is showing State-of-the-art result in many tasks.
CS234: Reinforcement Learning
Home page: https://web.stanford.edu/class/cs234/
Youtube link: https://www.youtube.com/playlist?list=PLoROMvodv4rOSOPzutgyCTapiGlY2Nd8u
Hotness: ★★
Reinforcement learning is a very different paradigm compared to supervised and unsupervised learning. It has definitely shown very great result in AI, Gaming, and Robotics. It has not been heavily adopted in the industry however because of challenges to find the right application
CS231N: Convolutional Neural Networks for Visual Recognition
Home page: http://cs231n.stanford.edu/
Youtube link: https://www.youtube.com/playlist?list=PL3FW7Lu3i5JvHM8ljYj-zLfQRF3EO8sYv
Hotness: ★★★★
CNN (convolutional neural network) is quite a classic. It’s definitely an area where you see tons of application of ML in practice. This course is taught by Fei-Fei Li, and you will get a deep dive into the architecture of many State-of-the-art visual recognition system end-to-end.
CS246: Mining Massive Data Sets
Home page: http://web.stanford.edu/class/cs246/
Youtube link: https://www.youtube.com/playlist?list=PLLssT5z_DsK9JDLcT8T62VtzwyW9LNepV
Hotness: ★★★
This is a big data course that focuses on data mining and machine learning algorithms for analyzing very large amounts of data. You can learn more practice knowledge of MapReduce and Spark to process very large amounts of data.
CS124: From Languages to Information
Home page: https://web.stanford.edu/class/cs124/
Youtube: https://www.youtube.com/playlist?list=PLaZQkZp6WhWyvdiP49JG-rjyTPck_hvEu
Hotness: ★★
This course is an more advanced topic in NLP. You will learn about why word embedding does not tell you about the connotation of words, and various forms of language (emoji & photo).
EE 364A: Convex Optimization
Home page: https://web.stanford.edu/class/ee364a/
Youtube: https://www.youtube.com/playlist?list=PL3940DD956CDF0622
Hotness: ★★
This course is a great course for student to learn about what optimization is really about. It’s definitely for the more mathematically inclined. It will help you really understand why neural network is so amazing even though it’s not a convex problem.
Ending note
Remember, there are also many other new courses developed by other schools, and I will try to make a list of them later.