Popular GitHub Repositories for Markov Gps

Machine learning, in numpy

Gathers machine learning and deep learning models for Stock forecasting including trading bots and simulations

VIP cheatsheets for Stanford's CS 221 Artificial Intelligence

Gaussian processes in TensorFlow

Master Reinforcement and Deep Reinforcement Learning using OpenAI Gym and TensorFlow

State Space Models library in JAX

Retentioneering: product analytics, data-driven CJM optimization, marketing analytics, web analytics, transaction analytics, graph visualization, process mining, and behavioral segmentation in Python. Predictive analytics over clickstream, AB tests, machine learning, and Markov Chain simulations.

MDPs and POMDPs in Julia - An interface for defining, solving, and simulating fully and partially observable Markov decision processes on discrete and continuous spaces.

Python code, PDFs and resources for the series of posts on Reinforcement Learning which I published on my personal blog

Machine learning algorithms for many-body quantum systems

State of the art autonomous navigation scripts using Ai, Computer Vision, Lidar and GPS to control an arducopter based quad copter.

DGMs for NLP. A roadmap.

Extensible Combinatorial Optimization Learning Environments

This is a repo for my master thesis research about the Fusion of Visual SLAM and GPS. It contains the research paper, code and other interesting data.

ACL 2018: Hybrid semi-Markov CRF for Neural Sequence Labeling (http://aclweb.org/anthology/P18-2038)

Statistical Rethinking (2nd Ed) with Tensorflow Probability

A framework to build and solve POMDP problems. Documentation: https://h2r.github.io/pomdp-py/

Bayes-Newton—A Gaussian process library in JAX, with a unifying view of approximate Bayesian inference as variants of Newton's method.

LexRank algorithm for text summarization

A QoE-Oriented Computation Offloading Algorithm based on Deep Reinforcement Learning (DRL) for Mobile Edge Computing (MEC) | This algorithm captures the dynamics of the MEC environment by integrating the Dueling Double Deep Q-Network (D3QN) model with Long Short-Term Memory (LSTM) networks.