ML-Tina

ML-Tina's Stars

• Unity-Technologies/ml-agents

  The Unity Machine Learning Agents Toolkit (ML-Agents) is an open-source project that enables games and simulations to serve as environments for training intelligent agents using deep reinforcement learning and imitation learning.

  Language:C#17.5k5552.9k4.2k

• Vay-keen/Machine-learning-learning-notes

  周志华《机器学习》又称西瓜书是一本较为全面的书籍，书中详细介绍了机器学习领域不同类型的算法(例如：监督学习、无监督学习、半监督学习、强化学习、集成降维、特征选择等)，记录了本人在学习过程中的理解思路与扩展知识点，希望对新人阅读西瓜书有所帮助！

  7.4k211101.9k

• eclipse-sumo/sumo

  Eclipse SUMO is an open source, highly portable, microscopic and continuous traffic simulation package designed to handle large networks. It allows for intermodal simulation including pedestrians and comes with a large set of tools for scenario creation.

  Language:C++2.7k6915.4k1.5k

• openai/evolution-strategies-starter

  Code for the paper "Evolution Strategies as a Scalable Alternative to Reinforcement Learning"

  Language:Python1.6k24022278

• tobegit3hub/advisor

  Open-source implementation of Google Vizier for hyper parameters tuning

  Language:Jupyter Notebook1.6k5233260

• keon/deep-q-learning

  Minimal Deep Q Learning (DQN & DDQN) implementations in Keras

  Language:Python1.3k6424453

• louisnino/RLcode

  Language:Python90628287

• agrimgupta92/sgan

  Code for "Social GAN: Socially Acceptable Trajectories with Generative Adversarial Networks", Gupta et al, CVPR 2018

  Language:Python84219112265

• benfulcher/hctsa

  Highly comparative time-series analysis

  Language:MATLAB7514946321

• NourozR/Stock-Price-Prediction-LSTM

  OHLC Average Prediction of Apple Inc. Using LSTM Recurrent Neural Network

  Language:Python5822313215

• atgambardella/pytorch-es

  Evolution Strategies in PyTorch

  Language:Python352181137

• 007gzs/meeting

  开源会议室预约小程序+Django服务端后台

  Language:Python348724115

• CasiaFan/time_seires_prediction_using_lstm

  Time series prediction using LSTM classifier

  Language:Python280182153

• brain-research/guided-evolutionary-strategies

  Guided Evolutionary Strategies

  Language:Jupyter Notebook26815127

• minepy/minepy

  minepy - Maximal Information-based Nonparametric Exploration

  Language:C21893646

• dotah88/Vehicle-Trajectory-Prediction-on-NGSIM

  Language:Jupyter Notebook1794848

• gliese581gg/DQN_tensorflow

  Tensorflow implementation of deep Q networks in paper 'Playing Atari with Deep Reinforcement Learning'

  Language:Python16311350

• jmeubank/tdm-gcc-src

  GCC sources for the TDM GCC releases

  14013824

• minepy/mictools

  A practical tool for Maximal Information Coefficient (MIC) analysis

  Language:Python12991224

• federicovergallo/SUMO-changing-lane-agent

  Implementation of a reinforcement learning agent able to do autonomous changing lane using Sumo

  Language:Python722816

• ShangtongZhang/DistributedES

  Distributed implementation of popular evolutionary methods

  Language:Python646318

• cemsaz/NGSIM-trajectories

  NGSIM I-80 dataset Leader - Follower Vehicle Trajectory Pairs

  Language:MATLAB562112

• PatientEz/Multidimensional-time-series-prediction-

  Multidimensional Time Series Prediction by using LSTM

  Language:Python563018

• cathywu/flow

  Computational framework for reinforcement learning in traffic control

  Language:Python433012

• jvmncs/ParamNoise

  A comparison of parameter space noise methods for exploration in deep reinforcement learning

  Language:Python27313

• ritchie-xl/Stock-Prediction-via-SVM-Matlab

  Predict the stock price using SVM regression in a daily basis ( LibSVM pre-installed needed)

  Language:Matlab20409

• wangjiwu/BreastTissue_classify_matlab

  使用libsvm进行分类

  Language:MATLAB18109

• dansbecker/evolution

  Minimal framework for Reinforcement Learning with Evolutionary Strategies (ES)

  Language:Python7100

• aspk/Tensorflow_Deep_RL

  Tensorflow implementation of Deep Reinforcement learning algorithms: Parameter Space Noise for Exploration

  Language:Python4401

• ML-Tina/evolution-strategies-starter

  Code for the paper "Evolution Strategies as a Scalable Alternative to Reinforcement Learning"

  Language:Python1000