All Projects → awjuliani → Rl Cc

awjuliani / Rl Cc

Licence: mit
Web-based Reinforcement Learning Control Center

Projects that are alternatives of or similar to Rl Cc

Image Outpainting
🏖 Keras Implementation of Painting outside the box
Stars: ✭ 1,106 (+1743.33%)
Mutual labels:  jupyter-notebook
Pose Guided Image Generation
Implementation of NIPS 2017 paper "Pose Guided Person Image Generation" in PyTorch. https://arxiv.org/abs/1705.09368
Stars: ✭ 60 (+0%)
Mutual labels:  jupyter-notebook
Cats Dogs Cortex Redux
Kaggle Cats & Dogs Redux with Cortex and Resnet50
Stars: ✭ 60 (+0%)
Mutual labels:  jupyter-notebook
Kdd2020multimodalities
KDD Cup 2020 Challenges for Modern E-Commerce Platform: Multimodalities Recall
Stars: ✭ 60 (+0%)
Mutual labels:  jupyter-notebook
Pytorchintro
An Absolute Beginners Guide to Machine Learning with PyTorch
Stars: ✭ 60 (+0%)
Mutual labels:  jupyter-notebook
Data scientist nanodegree
Stars: ✭ 59 (-1.67%)
Mutual labels:  jupyter-notebook
Feedinlib
This repository contains implementations of photovoltaic models to calculate electricity generation from a pv installation based on given solar radiation. Furthermore it contains all necessary pre-calculations.
Stars: ✭ 59 (-1.67%)
Mutual labels:  jupyter-notebook
Vehicle Detection And Tracking
Udacity Self-Driving Car Engineer Nanodegree. Project: Vehicle Detection and Tracking
Stars: ✭ 60 (+0%)
Mutual labels:  jupyter-notebook
Pyeis
PyEIS: A Python-based Electrochemical Impedance Spectroscopy simulator and analyzer
Stars: ✭ 60 (+0%)
Mutual labels:  jupyter-notebook
Instapy Research
📄 Research repository for InstaPy
Stars: ✭ 60 (+0%)
Mutual labels:  jupyter-notebook
Memory Efficient Maml
Memory efficient MAML using gradient checkpointing
Stars: ✭ 60 (+0%)
Mutual labels:  jupyter-notebook
Fraud detection techniques
Stars: ✭ 60 (+0%)
Mutual labels:  jupyter-notebook
Ml Dl Projects
Personal projects using machine learning and deep learning techniques
Stars: ✭ 60 (+0%)
Mutual labels:  jupyter-notebook
Analytics vidhya
Codes related to activities on AV including articles, hackathons and discussions.
Stars: ✭ 1,106 (+1743.33%)
Mutual labels:  jupyter-notebook
Useful Python
Python code and notebooks for reference
Stars: ✭ 60 (+0%)
Mutual labels:  jupyter-notebook
Soccer xg
A Python package for training and analyzing expected goals (xG) models in soccer.
Stars: ✭ 60 (+0%)
Mutual labels:  jupyter-notebook
Kaggle challenge live
This is the code for "Kaggle Challenge (LIVE)" by Siraj Raval on Youtube
Stars: ✭ 60 (+0%)
Mutual labels:  jupyter-notebook
Bayesian Linear Regression
A python tutorial for a Bayesian treatment of Linear Regression: https://zjost.github.io/bayesian-linear-regression/
Stars: ✭ 60 (+0%)
Mutual labels:  jupyter-notebook
Embedded gcnn
Embedded Graph Convolutional Neural Networks (EGCNN) in TensorFlow
Stars: ✭ 60 (+0%)
Mutual labels:  jupyter-notebook
Pycon Ua 2018
Talk at PyCon UA 2018 (Kharkov, Ukraine)
Stars: ✭ 60 (+0%)
Mutual labels:  jupyter-notebook

Reinforcement Learning Control Center

A d3.js web interface that allows a user to view their RL agent's performance during training.

RL Control Center

Current version displays:

  • Reward over time
  • Episode length over time
  • Animated gif of agent behavior during sample episodes
  • Agent's DDDQN activation during sample episodes

To try a live verion on an already trained network, go here.

The control center works by reading csv logs and animated gifs generated during the training process. For an example implementation, see Double-Dueling-DQN-Central.ipynb. The current interface is relatively dependent on the particular nature of the environment and agent used, but feel free to fork this project and adapt it to your own reinforcement learning needs.

See this Medium post for more information on how to use the control center, and the motivation behind it's creation.

Note that the project description data, including the texts, logos, images, and/or trademarks, for each open source project belongs to its rightful owner. If you wish to add or remove any projects, please contact us at [email protected].