Transfer Learning

In the previous chapter, we learned about recognizing the class that an image belongs to in a given image. In this chapter, we will learn about one of the drawbacks of CNN and also about how we can overcome it using certain pre-trained models.

In this chapter, we will cover the following recipes:

• Gender classification of a person in an image using CNNs
• Gender classification of a person in image using the VGG16 architecture-based model
• Visualizing the output of the intermediate layers of a neural network
• Gender classification of a person in image using the VGG19 architecture-based model
• Gender classification of a using the ResNet architecture-based model
• Gender classification of a using the inception architecture-based model
• Detecting the key points within image of a face