vn09

stats385.github.io

Stats 385 course website

100-Days-Of-ML-Code

100 Days of ML Coding

awesome-machine-learning

A curated list of awesome Machine Learning frameworks, libraries and software.

bandicoot

an open-source python toolbox to analyze mobile phone metadata

ByteTrack

ByteTrack: Multi-Object Tracking by Associating Every Detection Box

conversational-datasets

Datasets for conversational AI

cs7051

This repo reserves as the labs for the course CS7051 (NDS - TCD)

d2l-en

Dive into Deep Learning: an interactive deep learning book with code, math, and discussions, based on the NumPy interface.

d2l-pytorch

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

dcm4che

DICOM Implementation in JAVA

deep2Read

https://qdata.github.io/deep2Read/ This website includes a (growing) list of papers and lectures we read about deep learning and related.

DeepLearn

Implementation of research papers on Deep Learning+ NLP+ CV in Python using Keras, Tensorflow and Scikit Learn.

deeplearning-models

A collection of various deep learning architectures, models, and tips

Detectron

FAIR's research platform for object detection research, implementing popular algorithms like Mask R-CNN and RetinaNet.

DNDT

Deep Neural Decision Trees

facets

Visualizations for machine learning datasets

handson-ml

A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in python using Scikit-Learn and TensorFlow.

industry-machine-learning

A curated list of applied machine learning and data science notebooks and libraries accross different industries.

MathsDL-spring18

Topics course Mathematics of Deep Learning, NYU, Spring 18

ML-From-Scratch

Python implementations of Machine Learning models and algorithms from scratch. Aims to cover everything from Data Mining techniques to Deep Learning.

modeldb

A system to manage machine learning models

NUWA

A unified 3D Transformer Pipeline for visual synthesis

paper_notes

practicalAI

A practical approach to learning machine learning.

pure-bash-bible

📖 A collection of pure bash alternatives to external processes.

pwc

Papers with code. Sorted by stars. Updated weekly.

shap

A unified approach to explain the output of any machine learning model.

sherlock

🔎 Find usernames across social networks

stanford-cs-229-machine-learning

VIP cheatsheets for Stanford's CS 229 Machine Learning

Viewers

OHIF zero-footprint DICOM viewer and oncology specific Lesion Tracker, plus shared extension packages