Inspired by fast.ai course, we want to build our own Deep Learning framework.
Therefore, we can dive into Deep Learning by implementing papers from scratch.
The main goal of this project is to:
Provide a simple framework for fast prototyping of Deep Learning papers.
Learn from other frameworks and continuously refactor the framework.
Detailed understanding of:
- Parameters initialization
- Normalization techniques: BatchNorm, InstanceNorm, GroupNorm …
- Visualize activations / gradients histograms.