Stalearn is a handcrafted machine learning library inspired by sklearn, built from scratch using Python. It encapsulates the core essence of traditional algorithms, giving a foundational perspective to machine learning enthusiasts.
- Handcrafted Algorithms: Understand the inner workings of popular machine learning algorithms without the overhead of complex libraries.
- Easy to Understand: Written in simple Python, making it easier for learners and developers to grasp the core concepts.
- Lightweight: No heavy dependencies, making it suitable for lightweight applications and for educational purposes.
- Linear Regression
- Logistic Regression
- Decision Trees
- MLE with fisher information matrix ...
While stalearn is designed to replicate the functionality of popular algorithms in sklearn, it may not achieve the same level of performance or efficiency. The primary goal of this library is to provide a clear and simplified understanding of the algorithms' inner workings, making it especially useful for educational purposes. For production-grade tasks, it is recommended to utilize established libraries like sklearn.