Primeking47's Projects
Data augmentation for NLP, accepted at EMNLP 2021 Findings
🧑🏫 60 Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, sophia, ...), gans(cyclegan, stylegan2, ...), 🎮 reinforcement learning (ppo, dqn), capsnet, distillation, ... 🧠
astroML notebooks. They are rendered at http://www.astroml.org/astroML-notebooks
:memo: An awesome Data Science repository to learn and apply for real world problems.
A curated list of awesome Machine Learning frameworks, libraries and software.
Building Data Science Applications with FastAPI, Published by Packt
A node-based image processing GUI aimed at making chaining image processing tasks easy and customizable. Born as an AI upscaling application, chaiNNer has grown into an extremely flexible and powerful programmatic image processing application.
Public repository of Google Colab notebooks to use with Phenix
Contains several fortran 90 subroutines used to calculate various land-atmosphere coupling metrics
Data-driven dynamical systems toolbox.
IPython notebooks with demo code intended as a companion to the book "Data-Driven Science and Engineering: Machine Learning, Dynamical Systems, and Control" by Steven L. Brunton and J. Nathan Kutz
Books, courses, videos and blogs, mostly about Deep Learning.
Open source guides/codes for mastering deep learning to deploying deep learning in production in PyTorch, Python, C++ and more.
State-of-the-Art Deep Learning scripts organized by models - easy to train and deploy with reproducible accuracy and performance on enterprise-grade infrastructure.
Code for the book Deep Learning with PyTorch by Eli Stevens, Luca Antiga, and Thomas Viehmann.
A set of examples around pytorch in Vision, Text, Reinforcement Learning, etc.
🚀✨ Help beginners to contribute to open source projects
Fluid dynamics component of Chemical Engineering Design Library (ChEDL)
Free R-Tips is a FREE Newsletter provided by Business Science. It comes with bite-sized code tutorials every week.
Topic Modelling for Humans
A collection of useful .gitignore templates
A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.
Lab Materials for MIT 6.S191: Introduction to Deep Learning
Pipe network flow analysis toolkit
:red_circle: MiniSom is a minimalistic implementation of the Self Organizing Maps
🛠 All-in-one web-based IDE specialized for machine learning and data science.
mlpack: a fast, header-only C++ machine learning library
Samples for Intel® oneAPI Toolkits
oneAPI Data Analytics Library (oneDAL)
oneAPI Deep Neural Network Library (oneDNN)
React
Typescript
Django
Laravel
Facebook
Microsoft
Google
Alibaba
D3
Tencent