Jayabharathi Hari

Machine Learning Projects

Listed below are my ML projects, please click and know more on project desc and to view the project...

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Breast cancer is one of the most common cancer types among women, and early detection can be a lifesaving health concern. This study aims to explore the potential of an artificial intelligence-based approach in breast cancer diagnosis.

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Goal: The classification goal is to predict the likelihood of a liability customer buying personal loans.

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Developed a classification model aimed at enhancing the bank's services to prevent customers from canceling their credit cards.

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Objective: • Statistical Analysis of Business Data. Explore the dataset and extract insights from the data. The idea is for you to get comfortable with doing statistical analysis in Python.

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Practice Exercise inferential statistics

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Analyze the data and come up with a predictive model to determine if a customer will leave the credit card services or not and the reason behind it.

Machine Learning Projects

Breast Cancer Classification
Accuracy: 99.1
Using Decision Tree, Random Forest, Logistic Regression with Dimension reduction

Personal Loan Campaign Purchase Prediction
Using classification techniques(Logistic regression, KNN, Naive Bayes).

Credit Card Users Churn Prediction
Using • Logistic Regression • Decision Tree Classifier • Random Tree Classifier • Bagging Classifier • Gradient Boosting Classifier • AdaBoost Classifier • XGBoost Classifier • Hyperparameter Tuning

Statistical Analysis of Business Data

Problems on Probability

Travel Package Purchase
Using • Decision Tree Classifier • Random Forest Classifier • Bagging Classifier • AdaBoost Classifier • Gradient Boosting Classifier • XGBoost Classifier • Stacking Models

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Breast Cancer Classification Accuracy: 99.1 Using Decision Tree, Random Forest, Logistic Regression with Dimension reduction

Personal Loan Campaign Purchase Prediction Using classification techniques(Logistic regression, KNN, Naive Bayes).

Credit Card Users Churn Prediction Using • Logistic Regression • Decision Tree Classifier • Random Tree Classifier • Bagging Classifier • Gradient Boosting Classifier • AdaBoost Classifier • XGBoost Classifier • Hyperparameter Tuning

Statistical Analysis of Business Data

Problems on Probability

Travel Package Purchase Using • Decision Tree Classifier • Random Forest Classifier • Bagging Classifier • AdaBoost Classifier • Gradient Boosting Classifier • XGBoost Classifier • Stacking Models

Breast Cancer Classification
Accuracy: 99.1
Using Decision Tree, Random Forest, Logistic Regression with Dimension reduction

Personal Loan Campaign Purchase Prediction
Using classification techniques(Logistic regression, KNN, Naive Bayes).

Credit Card Users Churn Prediction
Using • Logistic Regression • Decision Tree Classifier • Random Tree Classifier • Bagging Classifier • Gradient Boosting Classifier • AdaBoost Classifier • XGBoost Classifier • Hyperparameter Tuning

Travel Package Purchase
Using • Decision Tree Classifier • Random Forest Classifier • Bagging Classifier • AdaBoost Classifier • Gradient Boosting Classifier • XGBoost Classifier • Stacking Models