This is an open repo of all the best practices of writing PySpark that the author has learnt from working with the Framework.
A collection of tools for Explainable AI (XAI). It’s based on shared principles and simple grammar for exploration, explanation and visualisation of predictive models.
Pytorch classification experiments template
A pytorch based classification experiments template
Simple Easy-to-use Tensorflow Cookbook
Simple and ready-to-use tutorials for TensorFlow
Python script to generate fake datasets optimized for testing machine learning/deep learning workflows
Build machine learning applications faster
Latex code for making neural networks diagrams
Process hexagonally sampled data with PyTorch
Interactive Visual Analysis for Big Data
data mining for Materials Science
Deep Planning Network
Control from pixels by latent planning with learned dynamics
Code for the paper “Language Models are Unsupervised Multitask Learners”
Implementation of RobustSTL: A Robust Seasonal-Trend Decomposition Algorithm for Long Time Series (AAAI 2019)
Reinforcement learning in Keras. Deep Reinforcement Learning mini-library with the aim of clear implementation of some algorithms.
A framework for deep reinforcement learning focused on research and fast prototyping