This repository is intended for beginners who want to learn about Machine Learning. It contains a collection of ML terminologies and basic ML projects that cover a wide range of topics.
Machine Learning is a rapidly growing field that has many practical applications in various industries. This repository is designed to introduce beginners to the fundamental concepts of Machine Learning.
The following projects are included in this repository:
- Titanic data visualization
- MNIST dataset
- Housing property rate Each project has a detailed explanation of the dataset and the code implementation.
The following terminologies are included in this repository:
- Accuracy
- Precision
- Recall
- F1 Score
- True Positive & True Negative
- Confusion Matrix
- Overfitting
- Underfitting
- Gradient Descent Each terminology has a detailed explanation and code snippets for implementation.
Contributions are welcome! If you have any ML projects or terminologies that you would like to share, feel free to contribute to this repository by submitting a pull request.