rlsotlr01

2D-GD-and-CG-code

Gradient Descent and Conjugate Gradient Code for 2D plane

3_hours_RL_Practice

Implementing the RL practical code by using baselines3 library in OpenAI

aaa

Application-of-Bayesian-Optimization-Gaussian-Process-in-Stock-market

Application of Bayesian Optimization (Gaussian Process) in Stock market

backjoon

backjoon2

Bayesian_Optimization_for_MPC_tuning

Apply the Bayesian Optimization for tuning the MPC Controller's hyperparameters

Big12TeamProject

TeamProject (비밀번호 및 개인정보 같은 경우는 보안을 위해서 개인컴퓨터에다가 적어주세요.)

cssPhoneBookWithPaging

start to make the paging function in the css web application.

safety-gym

Tools for accelerating safe exploration research.

rlsotlr01/Bayesian_Optimization_for_MPC_tuning

Apply the Bayesian Optimization for tuning the MPC Controller's hyperparameters

rlsotlr01/Big12TeamProject

TeamProject (비밀번호 및 개인정보 같은 경우는 보안을 위해서 개인컴퓨터에다가 적어주세요.)

rlsotlr01/safety-gym

Tools for accelerating safe exploration research.

rlsotlr01/2D-GD-and-CG-code

Gradient Descent and Conjugate Gradient Code for 2D plane

rlsotlr01/3_hours_RL_Practice

Implementing the RL practical code by using baselines3 library in OpenAI

rlsotlr01/aaa

rlsotlr01/Application-of-Bayesian-Optimization-Gaussian-Process-in-Stock-market

Application of Bayesian Optimization (Gaussian Process) in Stock market

rlsotlr01/cssPhoneBookWithPaging

start to make the paging function in the css web application.

rlsotlr01/Deep_Learning_with_Python

Practicing the all coding in the book of "Deep Learning with Python"

rlsotlr01/deepreach

rlsotlr01/easy-rl

强化学习中文教程（蘑菇书），在线阅读地址：https://datawhalechina.github.io/easy-rl/

rlsotlr01/LQ_Controller_Active_Suspension

Apply the LQ controller in the active suspension, and check the stability using Kharitinov stability theory

rlsotlr01/MachineLearning-DeepLearning

Studying machine learning and deep learning skills.

rlsotlr01/MPC-and-MHE-implementation-in-MATLAB-using-Casadi

This is a workshop on implementing model predictive control (MPC) and moving horizon estimation (MHE) on Matlab. The implementation is based on the Casadi Package which is used for numerical optimization. A non-holonomic mobile robot is used as a system for the implementation. The workshop video recording can be found here https://www.youtube.com/p

rlsotlr01/neural_clbf

Toolkit for learning controllers based on robust control Lyapunov barrier functions

rlsotlr01/PPO_practice

rlsotlr01/PPO_with_Mario_Game

Apply PPO Reinforcement Learning algorithm to learn the Mario game in Gym environment

rlsotlr01/ReinforcedLearningPractice

ReinforcedLearningPractice

rlsotlr01/RL_algorithm_practice

rlsotlr01/rlsotlr01.github.io

Github Pages template for academic personal websites, forked from mmistakes/minimal-mistakes

rlsotlr01/safe-control-gym

PyBullet CartPole and Quadrotor environments—with CasADi symbolic a priori dynamics—for learning-based control and RL

rlsotlr01/Safe-Reinforcement-Learning-Baselines

The repository is for safe reinforcement learning baselines.

rlsotlr01/safety_rl

rlsotlr01/SpringPractice

Practicing Spring tools

rlsotlr01/Stock_cur_collector

Collecting the current stock information by using Creon API.

rlsotlr01/stock_daily_collector

collecting the stock data for each day from the day to go public to the latest day by using Creon API

rlsotlr01/Stock_LSTM_Analysis_samsung

Analyize the stock movement of Samsung company in Korea with LSTM method

rlsotlr01/stocking_financial_data_merge

rlsotlr01/Udacity_Self_driving_practice

Practicing the multiple self-driving technology from Udacity Self Driving Car Engineering Nanodegree lecture

rlsotlr01/webdev

practicing to make a repository