An update to my previous post
Opening the textbook again at forty 01 for deep learning (feat. regression theory)
To learn deep learning and machine learning, I'm carefully going back over the Python I rushed through a few months ago for a stock-trading system. Along the way, I'm having a pretty striking experience.
normalstory.tistory.com
1. Neural-network-ish. (It isn't a neural network ㅜㅜ, but first, let's at least understand the 'structure' of the perceptron, which makes up a neural network ㅎ
https://www.notion.so/thinknormal/31763ef907fd41c1b074b224f4f844d8
Finally, the single-layer perceptron
An overview of the neural-network structure
www.notion.so
https://www.notion.so/thinknormal/st-215d9b852d944ad5af7530123aa44d95
Multilayer perceptron (neural-network-ish)
XOR multilayer perceptron
www.notion.so
https://www.notion.so/thinknormal/s-803a2d2dd99341bf8740307b8b82d93f
Backpropagation-ish
How to apply gradient descent to neural networks
www.notion.so
https://www.notion.so/thinknormal/101dbea015034a61932cade1d60d05af
Neural-network model design
Package imports
www.notion.so
https://www.notion.so/thinknormal/feat-pandas-7a434f45b01d4c009d7690f87e1b3316
Understanding data (feat. pandas)
1. Deep learning starts with data collection
www.notion.so
