holytemple's repositories
DeepReinforcementLearningInAction
Code from the Deep Reinforcement Learning in Action book from Manning, Inc
RLfrombasics
provides all the codes from the book "RLBook(titles will be changed later)"
stable-baselines
A fork of OpenAI Baselines, implementations of reinforcement learning algorithms
softlearning
Softlearning is a reinforcement learning framework for training maximum entropy policies in continuous domains. Includes the official implementation of the Soft Actor-Critic algorithm.
ReinforcementLearningAtoZ
The official code repository of Fastcampus <Reinforcement Learning A-Z> (패스트 캠퍼스 강화학습 A-Z)
deep_rl
PyTorch implementations of Deep Reinforcement Learning algorithms (DQN, DDQN, A2C, VPG, TRPO, PPO, DDPG, TD3, SAC, ASAC, TAC, ATAC)
PracticalSessions2020
Repository for tutorial sessions at EEML2020
Anomaly-ReactionRL
Using RL for anomaly detection in NSL-KDD
Deep-Reinforcement-Learning-Algorithms-with-PyTorch
PyTorch implementations of deep reinforcement learning algorithms and environments
keras-rl
Deep Reinforcement Learning for Keras.
DeepLearning_IDS
Deep learning based Intrusion Detection System
TD3
Author's PyTorch implementation of TD3 for OpenAI gym tasks
minimalRL
Implementations of basic RL algorithms with minimal lines of codes! (pytorch based)
Unity_ML_Agents
Unity ML-agents Project Repository of RLKorea
PPO-Keras
My implementation of the Proximal Policy Optisation algorithm using Keras as a backend
Advance-Instrusion-Detection-system
Intrusion detection system using reinforcement learning
Network-Intrusion-Detection
Network Intrusion Detection KDDCup '99', NSL-KDD and UNSW-NB15
Intrusion-Detection-System
I have tried some of the machine learning and deep learning algorithm for IDS 2017 dataset. The link for the dataset is here: http://www.unb.ca/cic/datasets/ids-2017.html. By keeping Monday as the training set and rest of the csv files as testing set, I tried one class SVM and deep CNN model to check how it works. Here the Monday dataset contains only normal data and rest of the days contains both normal and attacked data. Also, from the same university (UNB) for the Tor and Non Tor dataset, I tried K-means clustering and Stacked LSTM models in order to check the classification of multiple labels.
KUThesis
고려대학교 석·박사학위 논문 TeX 템플릿