Lending Club Data Analysis and Machine Learning скачать в хорошем качестве

Lending Club Data Analysis and Machine Learning

Phd Scholarship: https://www.linkedin.com/posts/school... We examine here loan default prediction using logistic regression, featuring John Hull's renowned materials from the "Machine Learning in Business" textbook. https://www-2.rotman.utoronto.ca/~hul... In this video, we explore the practical application of logistic regression in predicting loan defaults, leveraging a toy dataset from Lending Club, as well as tools and techniques from John Hull's Excel and Python resources. What You'll Learn: Introduction to Logistic Regression: Understand the basics of logistic regression, a powerful tool used for binary classification problems, and its role in predicting loan defaults. Data Exploration: Dive into the Lending Club dataset, which includes features such as home ownership, income, debt-to-income ratio, and credit score, with over 12,000 observations. Model Training: Follow along as we train a logistic regression model using this dataset. We'll split the data into training, validation, and test sets to ensure robust model evaluation. Performance Metrics: Learn how to evaluate model performance with various metrics such as confusion matrices, ROC curves, and AUC scores. We'll demonstrate how to use Python's sklearn library to generate these metrics, alongside traditional Excel analyses provided by John Hull. Decision Criteria: Discover how different decision thresholds impact loan acceptance and rejection, and understand the cost-benefit analysis involved in setting these thresholds. Advanced Insights: Explore the Receiver Operating Characteristic (ROC) curve and Area Under Curve (AUC) as measures of model predictive ability, and see how these metrics guide decision-making in finance. Hands-On Coding: We include a short Python code segment to illustrate how you can implement logistic regression and evaluate its performance using sklearn, enhancing the original insights with contemporary data science practices. This video is ideal for finance professionals, data scientists, and anyone interested in applying machine learning techniques to real-world financial datasets. Whether you're studying John Hull's "Machine Learning in Business" or simply looking to expand your knowledge, this tutorial offers valuable insights and practical skills. Resources: John Hull's official website and textbook resources: John Hull's Website Lending Club dataset and logistic regression workbook Colab link: https://colab.research.google.com/dri...