kaleabtessera Goto Github PK
Name: Kale-ab Tessera
Type: User
Company: University of Edinburgh
Bio: PhD Student, focusing on Multi-Agent Reinforcement Learning.
Twitter: KaliTessera
Location: Edinburgh, United Kingdom
Blog: kaleabtessera.com
Name: Kale-ab Tessera
Type: User
Company: University of Edinburgh
Bio: PhD Student, focusing on Multi-Agent Reinforcement Learning.
Twitter: KaliTessera
Location: Edinburgh, United Kingdom
Blog: kaleabtessera.com
A library of reinforcement learning components and agents
An open source, Geographical based, Augmented Reality library
A categorised list of Multi-Agent Reinforcemnt Learning (MARL) papers
A collection of MARL benchmarks based on TorchRL
📋 📘 The missing one page markdown feature cheat sheet for Boostnote
Bayesian optimization in PyTorch
High-quality single file implementation of Deep Reinforcement Learning algorithms with research-friendly features (PPO, DQN, C51, DDPG, TD3, SAC, PPG)
Dive into Deep Learning: an interactive deep learning book with code, math, and discussions, based on the NumPy interface.
This is the Watson Discovery Service Demo
Deep Q-Learning (DQN) implementation for Atari pong.
Ardrone flight using PID.
PyTorch implementation of "Efficient Neural Architecture Search via Parameters Sharing"
A set of examples around pytorch in Vision, Text, Reinforcement Learning, etc.
Implementing a gridworld from scratch and configuring it as a Markov decision process.
IcoOmen, a machine learning model which will predict the value of an ICO token after 6 months. This uses historic data that has been aggregated from various public websites and APIs (Application programming interfaces), as well as data that has been manually collected and calculated.
API layer behind IcoOmen.
Image Convolution Using CUDA C
KNN in C, comparing performance of serial and parallel implementations (implemented in OpenMp).
Deep Learning for humans
Knapsack Problem implemented in Python. This includes a Linear Greedy and Quadratic Knapsack Implementation.
Code for visualizing the loss landscape of neural nets
Machine Learning with Scikit-Learn and TensorFlow
Monte Carlo and Temporal Difference implementation from Chapter 5 and Chapter 6 of Reinforcement Learning: An Introduction Book by Andrew Barto and Richard S. Sutton.
Implementation of SARSA Semi-Gradient Method on the Mountain Car Open AI Environment.
Implementation of greedy, E-greedy and Upper Confidence Bound (UCB) algorithm on the Multi-Armed-Bandit problem.
An implementation of a Fully-connected Neural Network build from Scratch - only using Numpy.
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.