Chapter 1, Getting Started, introduces the basics of deep learning and makes the readers familiar with the vocabulary. The readers will install the software packages necessary to follow the rest of the chapters.
Chapter 2, Image Classification, talks about the image classification problem, which is labeling an image as a whole. The readers will learn about image classification techniques and train a deep learning model for pet classification. They will also learn methods to improve accuracy and dive deep into variously advanced architectures.
Chapter 3, Image Retrieval, covers deep features and image retrieval. The reader will learn about various methods of obtaining model visualization, visual features, inference using TensorFlow, and serving and using visual features for product retrieval.
Chapter 4, Object Detection, talks about detecting objects in images. The reader will learn about various techniques of object detection and apply them for pedestrian detection. The TensorFlow API for object detection will be utilized in this chapter.
Chapter 5, Semantic Segmentation, covers segmenting of images pixel-wise. The readers will earn about segmentation techniques and train a model for segmentation of medical images.
Chapter 6, Similarity Learning, talks about similarity learning. The readers will learn about similarity matching and how to train models for face recognition. A model to train facial landmark is illustrated.
Chapter 7, Image Captioning, is about generating or selecting captions for images. The readers will learn natural language processing techniques and how to generate captions for images using those techniques.
Chapter 8, Generative Models, talks about generating synthetic images for various purposes. The readers will learn what generative models are and use them for image generation applications, such as style transfer, training data, and so on.
Chapter 9, Video Classification, covers computer vision techniques for video data. The readers will understand the key differences between solving video versus image problems and implement video classification techniques.
Chapter 10, Deployment, talks about the deployment steps for deep learning models. The reader will learn how to deploy trained models and optimize for speed on various platforms.
