sandyy2505 Goto Github PK
Name: Sandeep Shukla
Type: User
Bio: MSc - Data Science & Advanced Computing, University of Reading, UK | PGP-Data Science & Business Analytics , University of Texas, Austin
Location: Reading, United Kingdom
Sandeep Shukla's Projects
airbnb_rental_prediction
Supervised Learning project : Linear Regression model, Linear Reg Assumptions, model performance evaluation
bagging_boosting
Ensemble Techniques : Bagging Classfiier, Boosting Classifiers, AdaBoost, Gradient Boosting, XGBoost, Stacking, Hyperparamter tuning
credit_defaulter_prediction
Credit Defaulter prediction model - Logistic Regression, Confusion Matrix.
eda
Exploratory Data Analysis using python.
eda_statistics_testing
This project used Statistical Analysis and Visualization to leverage customer's health information like smoking habits, BMI, age, gender, etc., and checked statistical evidences to make valuable decisions of insurance businesses like charges for health insurance.
income_group_classification
Income group classification - Logistic Regression, AUC-ROC curve, confusion matrix
life_expectancy
A holistic study of variables affecting Life Expectancy using advanced Machine Learning models.
loan_delinquent_prediction
Risk Analytics - Finance & Banking industries. Classification model to analyze the risk of the customer for loan delinquency. (Decision Tree, Hyperparameter tuning, Cost complexity pruning, Hypothesis testing)
model_tuning
Supervised Machine Learning : Hyperparamter tuning, GridSearchCV, RandomSearchCV
online_purchase_prediction
A model to predict whether a customer will buy a product or not. (Decision Tree, Feature Importance, Cost Complexity Pruning, GridSearchCV hyperparameter tuning
personal-loan-modelling
Supervised Classfication models - Logistic Regression & Decision Tree, AUC-ROC Curve
unsupervised_customer_segmentation
Unsupervised clustering technique - K-Means & Hierarchical clustering to identify different segments in the existing customer based on their spending patterns as well as past interaction with the bank.
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