A Tensorial Perspective to Deep Learning

This chapter introduces the foundational concepts of deep learning, emphasizing the critical role of tensors. It begins with a definition of deep learning and its importance, followed by a historical overview of neural networks. The basics of neural networks, including neurons, layers, and forward and backward propagation, are discussed. The chapter also delves into representing data as tensors, explaining tensor notation and basic tensor operations. Practical examples, such as image and sequence data processing using tensors, are provided to illustrate these concepts.