Jupyter Notebook containing code for Image & Video background removal using u2net

The Compositional Perturbation Autoencoder (CPA) is a deep generative framework to learn effects of perturbations at the single-cell level. CPA performs OOD predictions of unseen combinations of drugs, learns interpretable embeddings, estimates dose-response curves, and provides uncertainty estimates.

deeplearning.ai , By Andrew Ng, All slide and notebook + data + solutions and video link

This Python library makes it easy to display images and videos in a notebook.

Basic Cheat Sheet for Python (PDF, Markdown and Jupyter Notebook)

VISSL is FAIR's library of extensible, modular and scalable components for SOTA Self-Supervised Learning with images.

Classical Aerodynamics of potential flow using Python and Jupyter Notebooks

Visualize and explore NLP language models. Ecco creates interactive visualizations directly in Jupyter notebooks explaining the behavior of Transformer-based language models (like GPT2).

Python implementations (on jupyter notebook) of algorithms described in the book "PRML"