ANNLearnHub

Important links to learn Machine Learning and Artificial Inteliigence.

Ravin Kumar's Book Club

1. Causal Inference - https://community.intuitivebayes.com/c/book-club/21
2. State Space Models - https://community.intuitivebayes.com/c/dynamax/38
3. Large language Models - https://community.intuitivebayes.com/t/llms-study-plan-and-first-steps/1062

Synthetic Datasets

1. Synthcity - https://github.com/vanderschaarlab/synthcity

Explainable Models

1. CleanLab - https://github.com/cleanlab/cleanlab
2. Shapash - https://github.com/MAIF/shapash
3. Alibi - https://github.com/SeldonIO/alibi

ML Training

1. UpTrain - https://github.com/uptrain-ai/uptrain

Hyperparameter Optimization

1. Optunity - https://github.com/claesenm/optunity

Course

1. ML - https://www.youtube.com/playlist?list=PLl8OlHZGYOQ7bkVbuRthEsaLr7bONzbXS

Large Language Models

1. Large Language Models Humanize Technology - https://arxiv.org/pdf/2305.05576.pdf
2. LLM Numbers - https://github.com/ray-project/llm-numbers

Talks

1. https://build.microsoft.com/en-US/sessions/db3f4859-cd30-4445-a0cd-553c3304f8e2

Books

1. https://ebookfoundation.github.io/free-programming-books/
2. https://static1.squarespace.com/static/5ff2adbe3fe4fe33db902812/t/6009dd9fa7bc363aa822d2c7/1611259312432/ISLR+Seventh+Printing.pdf

Preprocessing NLP

1. https://towardsdatascience.com/what-on-earth-is-unicode-normalization-56c005c55ad0