ML Day 2 - Talking about

1. Basic Terms like Features, Labels, Examples, etc.

2. Training and Fitting

3. Regression v/s Classification

4. Loss on Datasets

4a. L1 and L2 loss

5. MSE

6. Reducing Loss

6a. Gradient Descent

6b. Stochastic Gradient Descent (SGD)

6c. Mini-Batch SGD

7. Coming Up next

"Best way to learn is to share"

Do let me know if there's something I can update or rectify in the document. Any suggestions are most welcome. Happy Diwali.

Sorry for the laziness made this post for Linkedin.

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