I’d like to get into machine learning over the next couple of years but I’m a self-taught SWE and don’t have a CS background (BBA in Risk Management) All of the courses and resources I’ve found focus on a certain tool or framework - I’d really like to have a solid understanding of the mathematics and any other prerequisites. Is anyone open to lending me advice on a learning path?
Take an online Stanford class or 2. Don’t do the udacity shit.
Basic linear algebra, probability, stats, and optimization is all you pretty much need. Where are you weak?
Machine Learning (Stanford) on Coursera is a good start. Then, deeplearning.ai.
I am trying to do the same. No CS background. Looking to learn in the next 1 year. DM me if you want to team up.
Read PRML for understanding the under the hood of ML
Kinda old eh. I’d suggest introduction to statistical learning
There is nothing particularly new in ISL so the “old” argument doesn’t make much sense
If you are new, start with Keras or PyTorch. You will probably give up after 2 days if you start with Tensorflow.
An Introduction to Statistical Learning. Free pdf available online.
I'd start here: http://themlbook.com/
Employers don't hire without past project experience, even if you have done online courses. Experts - Do you recommend building deeplearning.ai or any other projects and putting on github? Any open source libs i can contribute? What is the best way to showcase some practical experience beyond coursework?
Start with tool, framework and application. Work backwards on math needed for deep dives.