bhasfe / ml-algorithms

Implementation of most commonly used machine learning algorithms

Hi there 👋

This is Barış from Istanbul, Turkey. I am a Software Engineer who is looking forward to collaborating with you :)

• 🔭 I’m currently working as a Sofware Engineer
• 💬 Ask me about anything.
• 📫 How to reach me: [email protected]

ml-algorithms's Issues

DBSCAN Clustering

DBSCAN Clustering is needed to be added.

1. It should be implemented in a single Jupyter Notebook. Algorithm. The notebook should be in a proper folder, it should contain Introduction, explanation, EDA, FE (if necessary), and the model sections. You can look at other notebooks that I added to the repository.
2. If you need a dataset that is not in the repository. You can upload it to ml-algorithms/datasets/. Don't forget to give the source of the dataset in Sources.txt

Principal Component Analysis (PCA)

Principal Component Analysis (PCA) is needed to be added.

1. It should be implemented in a single Jupyter Notebook. Algorithm. The notebook should be in a proper folder, it should contain Introduction, explanation, EDA, FE (if necessary), and the model sections. You can look at other notebooks that I added to the repository.
2. If you need a dataset that is not in the repository. You can upload it to ml-algorithms/datasets/. Don't forget to give the source of the dataset in Sources.txt

Apriori Algorithm

Apriori Algorithm is needed to be added.

1. It should be implemented in a single Jupyter Notebook. Algorithm. The notebook should be in a proper folder, it should contain Introduction, explanation, EDA, FE (if necessary), and the model sections. You can look at other notebooks that I added to the repository.
2. If you need a dataset that is not in the repository. You can upload it to ml-algorithms/datasets/. Don't forget to give the source of the dataset in Sources.txt

K-modes

K-means algorithm is needed to be added.

1. It should be implemented in a single Jupyter Notebook. Algorithm. The notebook should be in a proper folder, it should contain Introduction, explanation, EDA, FE (if necessary), and the model sections. You can look at other notebooks that I added to the repository.
2. If you need a dataset that is not in the repository. You can upload it to ml-algorithms/datasets/. Don't forget to give the source of the dataset in Sources.txt

Linear Discriminant Analysis

Linear Discriminant Analysis is needed to be added.

1. It should be implemented in a single Jupyter Notebook. Algorithm. The notebook should be in a proper folder, it should contain Introduction, explanation, EDA, FE (if necessary), and the model sections. You can look at other notebooks that I added to the repository.
2. If you need a dataset that is not in the repository. You can upload it to ml-algorithms/datasets/. Don't forget to give the source of the dataset in Sources.txt

K-means algorithm

K-means algorithm is needed to be added.

1. It should be implemented in a single Jupyter Notebook. Algorithm. The notebook should be in a proper folder, it should contain Introduction, explanation, EDA, FE (if necessary), and the model sections. You can look at other notebooks that I added to the repository.
2. If you need a dataset that is not in the repository. You can upload it to ml-algorithms/datasets/. Don't forget to give the source of the dataset in Sources.txt

Hierarchical Clustering

Hierarchical Clustering is needed to be added.

1. It should be implemented in a single Jupyter Notebook. Algorithm. The notebook should be in a proper folder, it should contain Introduction, explanation, EDA, FE (if necessary), and the model sections. You can look at other notebooks that I added to the repository.
2. If you need a dataset that is not in the repository. You can upload it to ml-algorithms/datasets/. Don't forget to give the source of the dataset in Sources.txt