Deep Q-learning (DQN) for Multi-agent Reinforcement Learning (RL)

💡 All-in-one AI framework for semantic search, LLM orchestration and language model workflows

CoreNLP: A Java suite of core NLP tools for tokenization, sentence segmentation, NER, parsing, coreference, sentiment analysis, etc.

Giant Language Model Test Room

PyTorch implementation of Deep Reinforcement Learning: Policy Gradient methods (TRPO, PPO, A2C) and Generative Adversarial Imitation Learning (GAIL). Fast Fisher vector product TRPO.

This solution presents an accessible, non-trivial example of machine learning (Deep learning) with financial time series using TensorFlow

DeText: A Deep Neural Text Understanding Framework for Ranking and Classification Tasks

Implementation of algorithms for continuous control (DDPG and NAF).

Repo containing code for multi-agent deep reinforcement learning (MADRL).

Tensorflow implementation of Generative Adversarial Imitation Learning(GAIL) with discrete action

An In-Memory Cache Backed by Apache Kafka

Reinforcement learning algorithms implemented for Tensorflow 2.0+ [DQN, DDPG, AE-DDPG, SAC, PPO, Primal-Dual DDPG]

Maxwell's daemon, a mysql-to-json kafka producer

Basic Stock Price Prediction Using KNN Algorithm. #Python

🥑 Kafka connect sink connector for ArangoDB

Adversarial Imitation Via Variational Inverse Reinforcement Learning

The AWS Provider enables Terraform to manage AWS resources.

Deep recurrent Q Learning using Tensorflow, openai/gym and openai/retro

Super easy library for BERT based NLP models

TensorFlow code and pre-trained models for BERT

StarGAN v2 - Official PyTorch Implementation (CVPR 2020)

Deep Residual Learning for Image Recognition

Keras implementations of Generative Adversarial Networks.

A collection of 3 lambda functions that are invoked by Amazon S3 or Amazon API Gateway to analyze uploaded images with Amazon Rekognition and save picture labels to ElasticSearch (written in Kotlin)

Image-to-Image Translation in PyTorch

Pytorch Implementation of Graph Convolutional Kernel Networks

A collection of important graph embedding, classification and representation learning papers with implementations.

Stanford NLP Python library for tokenization, sentence segmentation, NER, and parsing of many human languages

Documentation on how to access and use the Quick, Draw! Dataset.