Transfer learning is a research problem in machine learning that focuses on storing knowledge gained while solving one problem and applying it to a different but related problem. For example, knowledge gained while learning to recognize cars could apply when trying to recognize trucks.

Dataset https://www.kaggle.com/datasets/salad...

Codes
https://colab.research.google.com/dri...
https://colab.research.google.com/dri...
https://colab.research.google.com/dri...

Pretrained Model video    • Pretrained models in CNN | ImageNET D...  

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⌚Time Stamps⌚

00:00 Intro
00:50 problem with training your own model
02:35 Using Pretrained Model
07:01 Using Transfer Learning
13:54 Why Transfer Learning Works?
17:41 Ways of doing Transfer Learning
20:54 Code Example using KERAS