Bank Loan Approval Prediction With Artificial Neural Nets

Overview

Unlock the future of banking with our comprehensive online course titled "Bank Loan Approval Prediction With Artificial Neural Nets" available on Coursera. This project-based course is specifically designed to teach you how to construct and train a straightforward deep neural network to accurately predict personal loan approvals.

Delve into a range of critical features such as age, experience, income, family size, education level, existing mortgages, and credit card details to assess eligibility.

By the conclusion of this engaging course, participants will gain valuable insights into:

• The pivotal role of Artificial Intelligence and Machine Learning in revolutionizing the banking sector.
• A foundational understanding of Deep Neural Networks and their underlying principles.
• How to leverage key Python libraries, analyze datasets, and conduct exploratory data analysis effectively.
• Mastering data visualization techniques with Seaborn to present findings clearly.
• Best practices for data standardization and division into training and testing datasets.
• Creating a robust deep learning model utilizing Keras, powered by TensorFlow 2.0.
• Evaluating your model's success and enhancing its generalizability with essential Key Performance Indicators (KPIs).

This course is most beneficial for learners located in the North America region, with efforts underway to extend this enriching learning experience to other areas soon. Categories:

Machine Learning Courses, Deep Learning Courses, Neural Networks Courses, Data Visualization Courses, Seaborn Courses.

Taught by

Ryan Ahmed

Subjects