Stars
Python Deep Dive Course - Accompanying Materials
Scalable Graph Neural Networks with Deep Graph Library
📘 Contains a series of hands-on notebooks for learning the fundamentals of NLP
Cool Python features for machine learning that I used to be too afraid to use. Will be updated as I have more time / learn more.
Machine Learning From Scratch. Bare bones NumPy implementations of machine learning models and algorithms with a focus on accessibility. Aims to cover everything from linear regression to deep lear…
Containerize your Apps with Docker and Kubernetes, published by Packt
A comprehensive collection of recent papers on graph deep learning
Slides and Jupyter notebooks for the Deep Learning lectures at Master Year 2 Data Science from Institut Polytechnique de Paris
SOftware Metadata Extraction Framework: A tool for automatically extracting relevant software information from code repositories (using README files, package metadata, etc.)
residual loss prediction: reinforcement learning with no intermediate feedback
This repository contains supplementary data, and links to the model and corpora used for the paper: Transfer learning for biomedical named entity recognition with neural networks.
A collection of important graph embedding, classification and representation learning papers with implementations.
A curated list of pretrained sentence and word embedding models
A curated list of network embedding techniques.
Drench yourself in Deep Learning, Reinforcement Learning, Machine Learning, Computer Vision, and NLP by learning from these exciting lectures!!
Python package built to ease deep learning on graph, on top of existing DL frameworks.
Free online textbook of Jupyter notebooks for fast.ai Computational Linear Algebra course
A Bootstrap 4 resume/CV theme created by Start Bootstrap
VIP cheatsheets for Stanford's CS 229 Machine Learning
A course on Network Science, including network formation models, structural patterns, and dynamic processes.