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Data Science Masterclass: Mastering Credit Card Default Prediction

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Overview

Join us for an immersive workshop on "Predicting Credit Card Defaults with Machine Learning," where you'll dive deep into the world of data science and predictive analytics. Over the course of the workshop, you'll explore various visualization techniques, machine learning algorithms tailored specifically for predicting credit card defaults. Through hands-on exercises and real-world case studies, you'll gain practical skills and insights to excel in this rapidly evolving field.

Topics Covered:

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Introduction to Machine Learning

Understand the fundamentals of machine learning, including supervised learning, unsupervised learning, and model evaluation techniques.

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Data Preprocessing

Learn how to preprocess credit card transaction data, handle missing values, and encode categorical variables effectively.

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Feature Engineering

Discover the importance of feature engineering in credit card default prediction and explore techniques such as feature scaling, transformation, and selection.

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Model Selection and Evaluation

Compare and evaluate various machine learning models for credit card default prediction, including logistic regression, and many more advanced ML techniques

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Hyperparameter Tuning

Learn how to fine-tune model hyperparameters using techniques like grid search and random search to improve model performance.

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Model Interpretability

Explore methods for interpreting and explaining machine learning models to gain insights into credit card default prediction.

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Hands-on Projects

Apply your newfound knowledge to real-world datasets through hands-on projects, where you'll build and evaluate machine learning models for credit card default prediction.

Meet your facilitator

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Neha Gupta

IIT MADRAS 10+ yrs exp in global leading MNC's

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Meet our trainer Neha Gupta, an accomplished professional with over a decade of experience in GenAI, data science and analytics space. A graduate of IIT, Madras, she's transformed industries like Marketing, Telecom, Banking-Insurance, and Sales analytics. Neha's track record includes spearheading projects for Capital Group, American Petroleum Institute, Johnson & Johnson, and other top clients. Her expertise in Python, R, Azure, AWS, and more has driven success in predictive modeling, NLP, machine vision, and AI, cementing her reputation as a dynamic leader in the field.

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