A neural network is a mathematical function that is used to solve a wide range of problems in different areas of Artificial Intelligence (AI) and deep learning. Hands-On Neural Networks with Keras will start by giving you an understanding of the core concepts of neural networks. You will delve into combining different neural network models and work with real-world use cases, to better understand the value of predictive modelling and function approximation. Moving ahead, you will become well versed with an assortment of the most prominent architectures. These include, but are not limited to, Convolutional Neural Networks (CNNs), recurrent neural networks (RNNs), Long Short-Term Memory (LSTM) networks, autoencoders, and Generative Adversarial Networks (GANs) using real-world training datasets.
We will explore the fundamental ideas and implementational details behind cognitive tasks like computer vision and natural language processing (NLP), using state of the art neural network architectures. We will learn how to combine these tasks to design more powerful inference systems that can drastically improve productivity in various personal and commercial settings. The book takes a theoretical and technical perspective required to develop an intuitive understanding of the inner workings of neural nets. It will address various common use cases, ranging from supervised, unsupervised, an self-supervised learning tasks. Throughout the course of this book, you will learn to use a variety of network architectures, including CNNs for image recognition, LSTMs for natural language processing, Q-networks for reinforcement learning, and many more. We will dive into these specific architectures and then implement each of them in a hands-on manner, using industry-grade frameworks.
By the end of this book, you will be highly familiar with all prominent deep learning models, and frameworks, as well as all the options you have to initiate a successful transition to applying deep learning to real-world scenarios, embedding AI as the core fabric of your organization.
