Keras
High-level multi-backend deep learning API (TensorFlow, JAX, PyTorch) focused on ergonomics and fast iteration.
Why it is included
Still one of the most approachable on-ramps to neural nets and a stable choice for teaching and rapid prototypes.
Best for
Learners and teams that want a thin API over a chosen backend without hand-rolling training loops.
Strengths
- Simple API
- Multi-backend
- Huge tutorial corpus
Limitations
- Advanced customization often drops to backend-specific code
Good alternatives
PyTorch Lightning · fast.ai · native PyTorch
Related tools
AI & Machine Learning
TensorFlow
End-to-end platform for machine learning and deployment.
AI & Machine Learning
PyTorch
Deep learning framework with strong research-to-production paths.
AI & Machine Learning
JAX
Composable transformations (grad, vmap, pmap) plus NumPy-like API for high-performance ML research on accelerators.
AI & Machine Learning
TinyLlama
1.1B-parameter Llama-architecture model trained on ~3T tokens—Apache-2.0 weights for fast experiments and teaching.
AI & Machine Learning
GPT-2 (Hugging Face)
Historic decoder-only LM family (124M–1.5B) under `openai-community` on the Hub—still a default tutorial and pipeline test target.
AI & Machine Learning
MLflow
Open platform for the ML lifecycle: experiment tracking, model registry, packaging, evaluation, and production monitoring.