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Introduction to Transfer Learning

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About this Course

Transfer learning is a very popular form of learning today. It aims to use a p[re-trained model to work on an entirely different dataset to see if meaningful results can be extracted when the machine learning algorithm is exposed to new data. Transfer learning is extremely popular because of the efficiency that is portrayed by the domain when working on really large datasets. In this course, you will learn all of the foundational concepts that are necessary for you to get started with and understand the working of transfer learning.

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Introduction to Transfer Learning

This chapter, to begin with, explains the HDF format and then discusses the formation of convolution layers and fully connected neural layers. 

 

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Introduction to Transfer Learning

4.5
average rating

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1.5 Hrs

Learning hours

Beginner

Level

1.7K+

Learners

10 Million+ learners

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