Deep learning doesn’t have to be intimidating. Until recently, this machine-learning method required years of study, but with frameworks such as Keras and Tensorflow, software engineers without a background in machine learning can quickly enter the field.
With the recipes in this cookbook, you’ll learn how to solve deep-learning problems for classifying and generating text, images, and music.Each chapter consists of several recipes needed to complete a single project, such as training a music recommending system. Examples are written in Python with code available on GitHub as a set of Python notebooks.You’ll learn how to:Create applications that will serve real usersUse word embeddings to calculate text similarityBuild a movie recommender system based on Wikipedia linksLearn how AIs see the world by visualizing their internal stateBuild a model to suggest emojis for pieces of textReuse pretrained networks to build an inverse image search serviceCompare how GANs, autoencoders and LSTMs generate iconsDetect music styles and index song collections
