Data Mining using Python LAB_IV_2021-22_R20_IT_LBRCE

 Syllabus

Lesson Plan - A Section

Lesson Plan - B Section

Experiment - 1 

1. Download Dataset from Kaggle
2. Loading the Dataset
3. Dealing with missing data

Experiment - 2 

• Dealing with Categorical Data, Feature Scaling, Splitting dataset into Training and Testing Sets

Experiment - 3

• Similarity and Dissimilarity Measures using python 
• Pearson’s Correlation, Cosine Similarity, Jaccard Similarity, Euclidean Distance, Manhattan Distance

Experiment - 4 - Build a model using a linear regression algorithm on any dataset.

 

Experiment - 5 - Decision Tree

Experiment - 6 - Naive Bayes Classifier

Experiment - 7 - Apriori Algorithm

Experiment - 8,9,10 - Clustering - K - means, Hierarchical, DBSCAN

D2D A-Section   B-Section