What is Transfer Learning? Transfer Learning in Keras | Fine Tuning Vs Feature Extraction
Channel: CampusX
Date: 2022-10-10

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.

Digital Notes for Deep Learning: https://shorturl.at/NGtXg

Dataset - https://www.kaggle.com/datasets/salader/dogs-vs-cats

Codes 
https://colab.research.google.com/drive/1VxoR4vMmZJAOCsDUnfezPuFQqHdKabcL?usp=sharing
https://colab.research.google.com/drive/1q_INiVDAzhSy1L_A87fBTf2wC3l3MiWy?usp=sharing
https://colab.research.google.com/drive/1mEWfubs2tR0CkqyxqP49cK30n7V5_NCm?usp=sharing

Pretrained Model video - https://www.youtube.com/watch?v=0MVXteg7TB4&ab_channel=CampusX

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⌚Time Stamps⌚

00:00 - Intro
00:50 - problem with training your own model
02:35 - Using Pre-trained 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