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18330

18.330 Introduction to Numerical Analysis

18335

18.335 - Introduction to Numerical Methods course

18337

18.337 - Parallel Computing and Scientific Machine Learning

18s096sciml

18.S096 - Applications of Scientific Machine Learning

18s191

Course 18.S191 at MIT, Spring 2021 - Introduction to computational thinking with Julia:

2020-10-30-odsc

Slides for a talk at the 2020 Open Data Science Conference (West)

30-seconds-of-python

A curated collection of useful Python snippets that you can understand in 30 seconds or less.

6s083

Materials for MIT 6.S083 / 18.S190: Computational thinking with Julia + application to the COVID-19 pandemic

abtesting_mab_epsilongreedy

This repo go over basics of AB Testing followed by a quick test drive of basics of AB Testing followed by Multi Arm Bandit overview and a demo of EpsilonGreedy Algorithm for AB Testing

adversarial-distributional-training

Adversarial Distributional Training (NeurIPS 2020)

adversarialnlp

A generic library for crafting adversarial NLP examples - WIP

ai-odsc-workshop-2019

Materials for the workshop "Applications of NLP in EdTech" at Open Data Science Conference (West), 2019.

autonlp

🤗 AutoNLP: train state-of-the-art natural language processing models and deploy them in a scalable environment automatically

awesome-artificial-intelligence

A curated list of Artificial Intelligence (AI) courses, books, video lectures and papers

awesome-deep-learning

A curated list of awesome Deep Learning tutorials, projects and communities.

awesome-gpt3

awesome-gpt3-1

Curating the best GPT3 tools and resources

awesome-papers

Papers & presentation materials from Hugging Face's internal science day

aws-machine-learning-university-accelerated-cv

aws-machine-learning-university-accelerated-nlp

aws-machine-learning-university-accelerated-tab

back-to-python-basics

Review of basic syntax of understanding and using Python. Much of the material is based off the "Python Crash Course" book by Eric Matthes.

back-to-python-for-data-basics

Review of basic syntax for using Python for understanding and analyzing data. Much of the material is based off syntax snippets pulled together by Chris Albon and the Deep Learning book by Ian Goodfellow, Yoshua Bengio, and Aaron Courville

background-generator

baselines

OpenAI Baselines: high-quality implementations of reinforcement learning algorithms

bayesian_inference_pymc3

Jupyter Python notebook from conference talk on Bayesian inference with PyMC3.

bbo_challenge_starter_kit

Starter kit for the black box optimization challenge at Neurips 2020

bert4keras

keras implement of transformers for humans

bigdata

Hands-On Big Data workshop materials

blog

Public repo for HF blog posts