Bank Customers Exit Prediction In Python EP1 | Solution with Source Code | Machine Learning Project
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This is the second part of the BANK CUSTOMER EXIT PREDICTION Project where we create a complete project on Kaggle Community Platform regarding prediction of exit chances of customers of a bank based on their credentials. We use data cleaning, Artificial Neural Network from Keras and Sequential models for getting the best prediction accuracy. This is a Deep Learning algorithm that we have used here for prediction of the requirements.
Artificial Neural Networks work like the human brain with many functionalities that can be extended using Keras. In the next part we Deploy the model and the project so look up to that as well.
Chapters:
00:00 Getting Started With Bank Customers Exit Prediction
02:50 Libraries
07:50 Dataset Loading
12:35 Train test Split Data
19:12 Artificial Neural Network
37:04 Prediction
39:47 Save Model
43:44 Plotting curves
See you in the next video with project deployment. Below are the mentioned links:
Code of Project: https://www.kaggle.com/code/shivamaga...
Code of Deployment: https://colab.research.google.com/dri...
Dataset : https://www.kaggle.com/datasets/filip...
Kaggle platform : https://kaggle.com
Google Colab : https://colab.research.google.com
Documentation Mentioned : https://keras.io/api/optimizers/
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