Siraj Raval has some advice for people looking to break into the Machine Learning/AI field for the first time with some resume tips.
What is back propagation, you ask? Well, it’s our old friend gradient descent’s new name when it is applied to neural networks.
If that explanation doesn’t work for you, then check out this video, where Siraj Raval explains back propagation in a way only he can: in song. Best of all, aside from the sick beats, is that the source code from the video is available on GitHub.
A lot of times, research papers don’t have an associated codebase that you can browse and run yourself. In cases like that, you’ll have to code up the paper yourself. Very often, this is easier said than done.
In this video Siraj Raval shows you how you should read and dissect a research paper so you can quickly implement it.
Siraj Raval shares his genius in this Q&A/AMA live stream where he shares his thoughts on blockchain, AI, VR, learning techniques, and a bunch of other software related topics.
Unlike traditional software development, as you progress further in data science and AI, you will encounter more and more advanced mathematics. Given the sad state of how math is taught in schools today (at least in the US), learning math quickly can dramatically impact the quality of your life and your career options.
Fortunately, Siraj Raval has got our back and, in this video, he offers up tips on how to learn math more quickly.
Siraj Raval demonstrates how to use TensorFlow to track people’s facial expressions and body positions with a regular webcam.
Siraj Raval promises to teach you Deep Learning in 6 weeks. Given his track record, it’s safe to say he can pull it off.
Siraj Raval explores the use of AI in classifying diseases in medical imagining.