End To End Machine Learning Project Implementation With Dockers,Github Actions And Deployment

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In this video we will be implementing an end to end ML project implementation with Dockers And Github Action
Time stamps:
Understanding the dataset 00:00:00
Preparing Dataset And Basic Analysis 00:08:14
Preparing Dataset For Model Training 00:22:10
Training The Model 00:36:54
Performance Metrics 00:52:41
Prediction Of New Data 00:55:33
Pickling the model file 00:59:45
Setting Up Github And VS Code 01:04:40
Tools And Software Required 01:12:00
Creating A New Environment 01:18:35
Setting up Git 01:26:07
Creating A FLASK Web Application 01:39:04
Running An Testing our application 01:53:14
Prediction From Front End Application 02:01:08
Procfile for Heroku Deployment 02:11:35
Deploying The App To Heroku 02:16:39
Deploying The App Using Dockers 02:23:20
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