iLearnNN

This repository is part of my machine learning learning journey inspired by the Coursera Machine Learning Specialization. It contains projects related to decision trees, machine learning advice, and neural network implementations for binary and multiclass classification tasks.

Project Structure

The repository is organized into the following directories:

1. Decision-Trees

• Project: Decision_Tree.ipynb
• Description: Implementation of a decision tree from scratch and application to the task of classifying whether a mushroom is edible or poisonous.

2. ML-Advice

• Project: ML_Advice.ipynb
• Description: Exploration of techniques to evaluate and improve machine learning models.

3. NeuralNet-HDR-Binary

• Project: NN_HDR_Binary.ipynb
• Description: Using a neural network to recognize hand-written digits zero and one.

4. NeuralNet-HDR-Multiclass

• Project: NN_HDR_Multiclass.ipynb
• Description: Using a neural network to recognize hand-written digits 0-9.

Coursera Machine Learning Specialization

This repository draws inspiration from the Coursera Machine Learning Specialization as part of my ongoing machine learning journey.

Feel free to explore the projects and learnings shared in each directory!

Contributing

If you'd like to contribute to this repository, follow these steps:

1. Fork the repository.
2. Create a new branch for your changes: git checkout -b feature/new-feature.
3. Make your changes and commit them: git commit -m "Add new feature".
4. Push to your forked repository: git push origin feature/new-feature.
5. Create a pull request to merge your changes into the main repository.