accel-brain-code
The purpose of this repository is to make prototypes as case study in the context of proof of concept(PoC) and research and development(R&D) that I have written in my website. The main research topics are Auto-Encoders in relation to the representation learning, the statistical machine learning for energy-based models, adversarial generation networks(GANs), Deep Reinforcement Learning such as Deep Q-Networks, semi-supervised learning, and neural network language model for natural language processing.
accel-brain/accel-brain-code
View on GitHub ↗The purpose of this repository is to make prototypes as case study in the context of proof of concept(PoC) and research and development(R&D) that I have written in my website. The main research topics are Auto-Encoders in relation to the representation learning, the statistical machine learning for energy-based models, adversarial generation networks(GANs), Deep Reinforcement Learning such as Deep Q-Networks, semi-supervised learning, and neural network language model for natural language processing.
accel-brain-code grew +0.0% in the last 30 days, ranks 173rd of 346 in Training Toolkits, last commit 1,034 days ago.
Star trajectory
115 days tracked+0.0% in 30d, below the Training Toolkits median of +0.0%.
Last commit 1,034 days ago, staler than the median of 227d.
How it compares in Training Toolkits
Ranked 173rd of 346 by stars.
- Language
- Python
- License
- GNU General Public License v2.0
- Contributors
- 7
- Forks
- 94
- Watchers
- 18
- Open issues
- 1
- Releases
- 0
- Created
- 2017-09-15
- Stars this week
- -1
You've seen where accel-brain-code stands today.
Get the moves before everyone else: the 5 Training Toolkits repos climbing fastest, every Tuesday.
Free weekly digest. Double opt-in, unsubscribe anytime.