Releases: jaywyawhare/C-ML
Releases · jaywyawhare/C-ML
v0.0.1
C-ML v0.0.1-pre Release
We're excited to announce the first pre-release of C-ML, version 0.0.1-pre! This release marks a significant milestone in the development of our lightweight machine learning library in C. While still in its early stages, this version provides a foundation for building and experimenting with neural network components.
What's Included
This pre-release includes the following core modules:
- Layers:
- Dense
- Dropout
- Activations:
- ReLU
- Sigmoid
- Tanh
- Softmax
- ELU
- Leaky ReLU
- Linear
- Loss Functions:
- Mean Squared Error
- Binary Cross-Entropy
- Focal Loss
- Mean Absolute Error
- Mean Absolute Percentage Error
- Root Mean Squared Error
- Reduce Mean
- Optimizers:
- SGD
- Adam
- RMSprop
- Preprocessing:
- Label Encoding
- One-Hot Encoding
- Standard Scaler
- Min-Max Scaler
- Regularizers:
- L1
- L2
- Combined L1-L2
Important Notes
- This is a pre-release, so expect potential bugs and incomplete features.
- Your feedback is highly appreciated to guide further development!
Changes Since Initial Commit
- Workflow Added: CI workflow added for automated testing and deployment.
- MkDocs Support: Integrated MkDocs for documentation generation and deployment.
- Documentation: Added comprehensive documentation for all modules.
- Testing: Added unit tests for all modules to ensure code correctness and robustness.
- Makefile: Streamlined the build process with automated source directory inclusion.
- Licensing: Added the "Don't Be a Jerk" Non-Commercial Care-Free License (DBaJ-NC-CFL).
- Example Usage: Provided a basic example in
main.c
to demonstrate library usage. - Code Refactoring: Improved code structure and readability.
- Bug Fixes: Patched minor bugs and memory allocation issues.
- Spelling and Comment Updates: Fixed spelling mistakes and removed unnecessary comments.
- Logo Added: Added a logo to the project.
- Header File Migration: Migrated from a single header file to separate header files for better organization.