27 lines
		
	
	
		
			726 B
		
	
	
	
		
			Markdown
		
	
	
	
	
	
		
		
			
		
	
	
			27 lines
		
	
	
		
			726 B
		
	
	
	
		
			Markdown
		
	
	
	
	
	
|   | --- | ||
|  | title: Transfer learning | ||
|  | --- | ||
|  | 
 | ||
|  | ### What is Transfer Learning ?
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|  | Transfer learning is the re-use of the pre-trained models on a different problem. It is very popular in Deep Learning as features learnt by one model trained on a Huge dataset can be re-used for another problem which as a small dataset to train on. | ||
|  | 
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|  | ### Pretrained models
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|  | 
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|  | Some of the pretrained models that are widely used are : | ||
|  | * VGG16 | ||
|  | * Xception | ||
|  | * VGG19 | ||
|  | * ResNet50 | ||
|  | * InceptionV3 | ||
|  | * InceptionResNetV2 | ||
|  | * MobileNet | ||
|  | * DenseNet | ||
|  | * NASNet | ||
|  | * MobileNetV2 | ||
|  | 
 | ||
|  | ### More Information
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|  | * Keras Pretrained Models https://keras.io/applications/ | ||
|  | * Pre Trained Model depot https://modeldepot.io/ | ||
|  | * Datacamp article https://www.datacamp.com/community/tutorials/transfer-learning  |