deep-RL-trading VS awesome-deep-trading

Compare deep-RL-trading vs awesome-deep-trading and see what are their differences.

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deep-RL-trading awesome-deep-trading
14 37
342 1,388
- -
0.0 0.0
almost 3 years ago 9 months ago
Python
MIT License MIT License
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

deep-RL-trading

Posts with mentions or reviews of deep-RL-trading. We have used some of these posts to build our list of alternatives and similar projects.

awesome-deep-trading

Posts with mentions or reviews of awesome-deep-trading. We have used some of these posts to build our list of alternatives and similar projects.

What are some alternatives?

When comparing deep-RL-trading and awesome-deep-trading you can also consider the following projects:

muzero-general - MuZero

OctoBot - Open source crypto trading bot

TradingView-Machine-Learning-GUI - Embark on a trading journey with this project's cutting-edge stop loss/take profit generator, fine-tuning your TradingView strategy to perfection. Harness the power of sklearn's machine learning algorithms to unlock unparalleled strategy optimization and unleash your trading potential.

wolfinch - Wolfinch is your friendly trader Bot written in Python

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.

awesome-quant - A curated list of insanely awesome libraries, packages and resources for Quants (Quantitative Finance)

Note - Easily implement parallel training and distributed training. Machine learning library. Note.neuralnetwork.tf package include Llama2, Llama3, CLIP, ViT, ConvNeXt, SwiftFormer, etc, these models built with Note are compatible with TensorFlow and can be trained with TensorFlow.

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

Awesome-System-for-Machine-Learning - A curated list of research in machine learning systems (MLSys). Paper notes are also provided.

DeepRL-TensorFlow2 - 🐋 Simple implementations of various popular Deep Reinforcement Learning algorithms using TensorFlow2

deep-q-learning - Minimal Deep Q Learning (DQN & DDQN) implementations in Keras