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Coding Projects by Bhargav Venkat

Applications of Artificial Intelligence

Students have to create a detailed document about any two applications of Artificial Intelligence. It may include any example - Google Translator, Alexa, Self Drive Cars, or Sofia the robot.

K-Means clustering on live selling dataset

Students must implement the K-Means clustering algorithm to the Live selling dataset. Then, try to find out the accuracies by using the different numbers of clusters.

Applications of Unsupervised Learning

Students have to explain in brief the Applications of Unsupervised Learning Algorithms. You can use appropriate images for your ideas and explanations.

Apriori Algorithm on Grocery Store dataset

Students must implement the Apriori Association algorithm to the grocery store dataset and find out the association rule.

DBSCAN clustering analysis

Students must implement the DSCAN clustering algorithm on the customer dataset and make the unique clusters and visualize them.

K-Means clustering for college data

Students must implement the K-Means clustering algorithm on the college dataset and make the clusters based on private and public colleges.

Clustering & Association

Students have to explain in brief three examples of Clustering & Association. Also, you can use appropriate images or graphs for your ideas and explanations.

Best Fitted Algorithm

Students have to implement all the learned Classifier Algorithms on the Water Potability dataset and find out the accuracy of each model.

Airline Passenger Satisfaction Prediction

Students have to implement the Classifier Algorithms on the Airline dataset and find out the accuracy of each model.

Airline Passenger Satisfaction Using Random Forest

Students have to implement the Randon Forest Classifier on the Airline dataset and find out the accuracy of the model.

Identifying Underfitting & Overfitting

Students have to identify underfitting & overfitting conditions in each of the real-life questions given in the document.

Iris Species with Decision Tree

Students have to implement the Decision Tree classifier on the Iris Species dataset and find out the model's accuracy.