softlearning
awesome-deep-trading
softlearning | awesome-deep-trading | |
---|---|---|
4 | 37 | |
1,157 | 1,390 | |
2.7% | - | |
0.0 | 0.0 | |
5 months ago | 9 months ago | |
Python | ||
GNU General Public License v3.0 or later | MIT License |
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softlearning
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Problem with Truncated Quantile Critics (TQC) and n-step learning algorithm.
# see https://github.com/rail-berkeley/softlearning/issues/60
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Infinite Horizon problem with SAC and custom environment
Found relevant code at https://github.com/rail-berkeley/softlearning + all code implementations here
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SAC: Enforcing Action Bounds formula derivation
Code for https://arxiv.org/abs/1812.05905 found: https://github.com/rail-berkeley/softlearning
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DDPG not solving MountainCarContinuous
You may read - issue with SAC (https://github.com/rail-berkeley/softlearning/issues/76 ), solution: use large OU noise or use other type of exploration like gSDE
awesome-deep-trading
What are some alternatives?
deep-RL-trading - playing idealized trading games with deep reinforcement learning
OctoBot - Open source crypto trading bot
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.
tmrl - Reinforcement Learning for real-time applications - host of the TrackMania Roborace League
wolfinch - Wolfinch is your friendly trader Bot written in Python
rl-baselines3-zoo - A training framework for Stable Baselines3 reinforcement learning agents, with hyperparameter optimization and pre-trained agents included.
awesome-quant - A curated list of insanely awesome libraries, packages and resources for Quants (Quantitative Finance)
LiDAR-Guide - LiDAR Guide
Awesome-System-for-Machine-Learning - A curated list of research in machine learning systems (MLSys). Paper notes are also provided.
trax - Trax — Deep Learning with Clear Code and Speed
senza - Experiments with drone control and reinforcement learning.