An Extendible (General) Continual Learning Framework based on Pytorch - official codebase of Dark Experience for General Continual Learning

Awesome Incremental Learning

Must-read papers on prompt-based tuning for pre-trained language models.

Contrastive Language-Image Pretraining

Code for "Supermasks in Superposition"

The official PyTorch code for 'DER: Dynamically Expandable Representation for Class Incremental Learning' accepted by CVPR2021

A pytorch implementations of Adversarial attacks and utils

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…

Machine Learning Interviews from FAAG, Snapchat, LinkedIn.

The HSIC Bottleneck: Deep Learning without Back-Propagation

PyTorch implementation of various methods for continual learning (XdG, EWC, online EWC, SI, LwF, GR, GR+distill, RtF, ER, A-GEM, iCaRL).

Studying for a tech interview sucks. Here's an open source cheat sheet to help

Machine Learning and Computer Vision Engineer - Technical Interview Questions

此项目是机器学习(Machine Learning)、深度学习(Deep Learning)、NLP面试中常考到的知识点和代码实现，也是作为一个算法工程师必会的理论基础知识。

📚 技术面试必备基础知识、Leetcode、计算机操作系统、计算机网络、系统设计、Java、Python、C++

Adversarially Robust Transfer Learning with LWF loss applied to the deep feature representation (penultimate) layer

This project reproduces the book Dive Into Deep Learning (www.d2l.ai), adapting the code from MXNet into PyTorch.

This repository contains implementations and illustrative code to accompany DeepMind publications

Python code for paper - Variational Deep Embedding : A Generative Approach to Clustering

starter from "How to Train a GAN?" at NIPS2016

Notebooks for learning deep learning

aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view. All in pure Python ;)

This is code of book "Learn Deep Learning with PyTorch"

Latex code for making neural networks diagrams