Stars
Development repository for the Triton language and compiler
Apache Superset is a Data Visualization and Data Exploration Platform
Aim 💫 — An easy-to-use & supercharged open-source experiment tracker.
Labs and demos for courses for GCP Training (http://cloud.google.com/training).
🚴 Call stack profiler for Python. Shows you why your code is slow!
Google Research
A complete computer science study plan to become a software engineer.
Danfo.js is an open source, JavaScript library providing high performance, intuitive, and easy to use data structures for manipulating and processing structured data.
🔎 Monitor deep learning model training and hardware usage from your mobile phone 📱
⚡ Automatically decrypt encryptions without knowing the key or cipher, decode encodings, and crack hashes ⚡
A minimal PyTorch re-implementation of the OpenAI GPT (Generative Pretrained Transformer) training
Visualize and compare datasets, target values and associations, with one line of code.
Portal is the fastest way to load and visualize your deep neural networks on images and videos 🔮
Merlion: A Machine Learning Framework for Time Series Intelligence
Deep neural network to extract intelligent information from invoice documents.
This repository accompanies the book "Getting Started with Natural Language Processing"
The goal of this project is to enable users to create cool web demos using the newly released OpenAI GPT-3 API with just a few lines of Python.
Approaching (Almost) Any Machine Learning Problem
A framework for detecting, highlighting and correcting grammatical errors on natural language text. Created by Prithiviraj Damodaran. Open to pull requests and other forms of collaboration.
Python Feature Engineering Cookbook, published by Packt
Open source speech to text models for Indic Languages
NitroFE is a Python feature engineering engine which provides a variety of modules designed to internally save past dependent values for providing continuous calculation.
Proximal Policy Optimization (PPO) algorithm for Super Mario Bros
Papers, code and slides for my session at the live@manning NLP conference, 2020 covering my talk on Deep Transfer Learning for Natural Language Processing
A code challenge in Ruby - move a robot in a table of 5x5