Multiple assignments regarding to the Intro to Data Mining course

Working with the following topics:

• Pandas, Numpy (basic Libraries)
• Standard Scaler, MinMax Scaler, Robust Scaler, OneHot Encoder, LabelEncoder, PCA (Data Pre Processing)
• Apriori Algorithm (Association Rule Mining)
• Matplotlib, Seaborn (Data Visualization)
• K-Means, Agglomerative Clustering, DBSCAN (Clustering)
• K-Nearest Neighbors Algorithm (Classifier)
• Decision Tree, Support Vector Machines, Multi-Layer Perceptron (Machine Learning)

DTM logo

Repository:

GitHub link

Basic Libraries:

Intro to Python

Standard Scaler, MinMax Scaler, Robust Scaler, OneHot Encoder, LabelEncoder, PCA:

Data Pre Processing

Apriori Algorithm:

Apriori Algorithm

Data Visualization:

Matplotlib, Seaborn

K-Means, Agglomerative Clustering, DBSCAN:

Clustering

K-Nearest Neighbors Algorithm:

Classifier

Decision Tree, Support Vector Machines, Multi-Layer Perceptron:

Machine Learning