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annotated_deep_learning_paper_implementations

🧑‍🏫 59 Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, ...), gans(cyclegan, stylegan2, ...), 🎮 reinforcement learning (ppo, dqn), capsnet, distillation, ... 🧠

attention-is-all-you-need-paper

Implementation of Vaswani, Ashish, et al. "Attention is all you need." Advances in neural information processing systems. 2017.

awesome-deep-learning

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

awesome-diffusion-models

A collection of resources and papers on Diffusion Models

awesome-diffusion-models-in-medical-imaging

Diffusion Models in Medical Imaging

cav-keras

Concept activation vectors for Keras

coding-interview-university

A complete computer science study plan to become a software engineer.

cs224w-slides-to-code

csc-7991-deeplearning

CSC 7991 Deep Learning Project

cv_notebooks

Set of Jupyter Notebooks linked to Roboflow Blogpost and used in our YouTube videos.

deep-learning-in-production

In this repository, I will share some useful notes and references about deploying deep learning-based models in production.

deep-learning-in-production-1

Build, train, deploy, scale and maintain deep learning models. Understand ML infrastructure and MLOps using hands-on examples.

deep_relational_reasoning_epilepsy

Official TensorFlow implementation of Deep Relational Reasoning for prediction of language impairments and seizure outcomes

deeplearningpython35

neuralnetworksanddeeplearning.com integrated scripts for Python 3.5.2 and Theano with CUDA support

diffusion-models-in-vision-a-survey

This repository categorizes the papers about diffusion models applied in computer vision according to their target task. The classifcation is based on our survey: https://arxiv.org/abs/2209.04747v1

dualselfdistillation

Official PyTorch implementation of Dual Self-Distillation (DSD) in U-shaped Networks for Medical Image Segmentation

fastbook

The fastai book, published as Jupyter Notebooks

gaussiannb

Gaussian Naive Bayes (GaussianNB) classifier

generativemodels

MONAI Generative Models makes it easy to train, evaluate, and deploy generative models and related applications

gnnpapers

Must-read papers on graph neural networks (GNN)

graph_nets

Build Graph Nets in Tensorflow

graph_sampling

Graph Sampling is a python package containing various approaches which samples the original graph according to different sample sizes.

histocartography

Histocartography is a framework bringing together AI and Digital Pathology

imimic-rcvs

This repository contains the code for implementing Bidirectional Relevance scores for Digital Histopathology, which was used for the results in the iMIMIC workshop paper: Regression Concept Vectors for Bidirectional Explanations in Histopathology

keras-deep-graph-learning

Welcome to Keras Deep Learning on Graphs (Keras-DGL) http://vermaMachineLearning.github.io/keras-deep-graph-learning

leetcode

Python & JAVA Solutions for Leetcode

leetcode-solutions

:octocat: (Weekly Update) Python / C++ 11 Solutions of All 1172 LeetCode Problems

literaturedl4graph

A comprehensive collection of recent papers on graph deep learning

machine-learning-interview-enlightener

This repo is meant to serve as a guide for Machine Learning/AI technical interviews.

made-with-ml

Learn how to design, develop, deploy and iterate on production-grade ML applications.