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sweetice/Deep-reinforcement-learning-with-pytorch
PyTorch implementation of DQN, AC, ACER, A2C, A3C, PG, DDPG, TRPO, PPO, SAC, TD3 and ....
4.6k 899 +0/wk
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a2c a3c actor-critic actor-critic-algorithm algorithm alphago deep-learning deep-reinforcement-learning dqn policy-gradient ppo pytorch
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| Metric | Deep-reinforcement-learning-with-pytorch | nccl | datascience | cracking-the-data-science-interview |
|---|---|---|---|---|
| Stars | 4.6k | 4.6k | 4.6k | 4.6k |
| Forks | 899 | 1.2k | 708 | 1.2k |
| Weekly Growth | +0 | +6 | -1 | +0 |
| Language | Python | C++ | N/A | Jupyter Notebook |
| Sources | 1 | 1 | 1 | 1 |
| License | MIT | NOASSERTION | CC0-1.0 | N/A |
Capability Radar vs nccl
Deep-reinforcement-learning-with-pytorch
nccl
Maintenance Activity 0
Last code push 1111 days ago.
Community Engagement 98
Fork-to-star ratio: 19.5%. Active community forking and contributing.
Issue Burden 70
Issue data not yet available.
Growth Momentum 30
No measurable growth in the current period (first-day cold start expected).
License Clarity 95
Licensed under MIT. Permissive — safe for commercial use.
Risk scores are computed from real-time repository data. Higher scores indicate healthier metrics.