Hello :) Today is Day 123!
A quick summary of today:
- read about optimization algorithms, and maths for DL from Dive into Deep Learning
Firstly, my notes from the optimization algorithms chapter
Covered topics:
Common challenges in DL optimization, convexity, convexity properties, SGD, momentum, Adagrad, RMSProp, Adadelta, Adam, LR schedulers
As for the maths for DL
This is actually in the apendix, but I decided to read through it, just to check if there is any interesting math.
The content is as follows:
Having this appendix is very nice and definitely helps to answer questions like for example when I went to the roots of multicollinearity (on Day 121) - understanding the math helps understand the root of problems.
As for the MLx Fundamentals it started just as I am finishing this blog. The first day is from 9pm to 3am in my local time, so I will write about it in tomorrow’s blog.
Schedule (time is in BST)
That is all for today!
See you tomorrow :)