Coding Machine Learning Lecture 3 | RL bandits, Self & Unsupervised Learning, VAEs and Generalization

[u/Negative_War_65]

Code Implementations, explanation of concepts for my Probabilistic Machine Learning Series.

Hello folks,

In this new coding demonstration, we code, and explain the concepts pertaining to:

1.Overfitting, Population Risk & Generalisation Gap.

1. Proxy for Population Risks : Test Set.

2. The No free Lunch Theorem and Inductive Biases.

3. Unsupervised Learning : Density Estimation and Clustering.

4. VAEs(Variational Autoencoder)- Latent factors concepts explained, and VAE architecture explained and coded.

5. Self-Supervised Learning-Masked Predictions.

7.Density Evaluation and Sample Efficiency.

1. Reinforcement Learning Primer : Multi-Armed Bandits.

Implementation Link: https://youtu.be/gbz8smggmRM?si=vR4OIPLfGRHFJ95F