AIbox is a laboratory for exploring, testing, and visualizing various AI and machine learning methods.
Main goal is to create a sandbox environment for experiments with different algorithms.
Repository might be also helpful for new learners with their journey into AI/ML.
Project combines ideas from statistical learning, mathematical modeling and deep learning.
- Regression: Implementing and comparing linear regression, ridge regression, and lasso regression on synthetic and real datasets.
- Classification: Exploring logistic regression, support vector machines, and decision trees for binary and multi-class classification tasks.
- SVM: Implementing support vector machines with different kernels and visualizing decision boundaries.
- Knowledge Distillation: Experimenting with teacher-student models to transfer knowledge from a larger model to a smaller one.
- Pipelines: Building end-to-end machine learning pipelines for data preprocessing, model training, and evaluation.
- Boosting: Implementing boosting algorithms like Gradient Boosting for improving model performance.
To setup the environment, follow these steps:
- Clone the repository
- Create a virtual environment:
uv sync- Experiment with different notebooks