Includes index.

Introduction --
Part 1: Discovering deep learning. Introducing deep learning ; Introducing the machine learning principles ; Getting and using Python ; Leveraging a deep learning framework --
Part 2: Considering deep learning basics. Reviewing matrix math and optimization ; Laying linear regression foundations ; Introducing neural networks ; Building a basic neural network ; Moving to deep learning ; Explaining convolutional neural networks ; Introducing recurrent neural networks --
Part 3: Interacting with deep learning. Performing image classification ; Learning advanced CNNs ; Working on language processing ; Generating music and visual art ; Building generative adversarial networks ; Playing with deep reinforcement learning --
Part 4: The part of tens. Ten applications that require deep learning ; Ten must-have deep learning tools ; Ten types of occupations that use deep learning.

"Deep learning provides the means for discerning patterns in the data that drive online business, medicine, research, social media outlets, and many elements of daily life. This book gives you the information you need to take the mystery out of the topic--and all of the underlying technologies associated with it. In no time, you'll make sense of those increasingly confusing algorithms, and find a simple and safe environment to experiment with deep learning"--Page 4 of cover.

College of Engineering and Computer Studies Bachelor of Science in Computer Science

Text in English