Skip to content
View Olegnv47's full-sized avatar

Block or report Olegnv47

Block user

Prevent this user from interacting with your repositories and sending you notifications. Learn more about blocking users.

You must be logged in to block users.

Please don't include any personal information such as legal names or email addresses. Maximum 100 characters, markdown supported. This note will be visible to only you.
Report abuse

Contact GitHub support about this user’s behavior. Learn more about reporting abuse.

Report abuse

Popular repositories Loading

  1. minimalRL minimalRL Public

    Forked from seungeunrho/minimalRL

    Implementations of basic RL algorithms with minimal lines of codes! (pytorch based)

    Python 1

  2. Deep-Reinforcement-Learning-Hands-On-Second-Edition Deep-Reinforcement-Learning-Hands-On-Second-Edition Public

    Forked from PacktPublishing/Deep-Reinforcement-Learning-Hands-On-Second-Edition

    Deep-Reinforcement-Learning-Hands-On-Second-Edition, published by Packt

    Jupyter Notebook

  3. Popular-RL-Algorithms Popular-RL-Algorithms Public

    Forked from quantumiracle/Popular-RL-Algorithms

    PyTorch implementation of Soft Actor-Critic (SAC), Twin Delayed DDPG (TD3), Actor-Critic (AC/A2C), Proximal Policy Optimization (PPO), QT-Opt, PointNet..

    Jupyter Notebook

  4. Hands-On-Machine-Learning-for-Algorithmic-Trading Hands-On-Machine-Learning-for-Algorithmic-Trading Public

    Forked from PacktPublishing/Hands-On-Machine-Learning-for-Algorithmic-Trading

    Hands-On Machine Learning for Algorithmic Trading, published by Packt

    Jupyter Notebook

  5. hybrid-sac hybrid-sac Public

    Forked from nisheeth-golakiya/hybrid-sac

    Single-file pytorch implementation of hybrid-SAC

    Python

  6. Machine-Learning-for-Algorithmic-Trading-Second-Edition Machine-Learning-for-Algorithmic-Trading-Second-Edition Public

    Forked from PacktPublishing/Machine-Learning-for-Algorithmic-Trading-Second-Edition

    Code and resources for Machine Learning for Algorithmic Trading, 2nd edition.

    Jupyter Notebook