about this book networks to handle classification and regression tasksand you'll have solid idea of what' happening in the background as you train them explores the canonical machine-learning workflow you'll also learn about common pitfalls and their solutions part takes an in-depth dive into practical applications of deep learning in computer vision and natural-language processing many of the examples introduced in this part can be used as templates to solve problems you'll encounter in the real-world practice of deep learning examines range of practical computer-vision exampleswith focus on image classification gives you practice with techniques for processing sequence datasuch as text and timeseries introduces advanced techniques for building state-of-the-art deeplearning models explains generative modelsdeep-learning models capable of creating images and textwith sometimes surprisingly artistic results is dedicated to consolidating what you've learned throughout the bookas well as opening perspectives on the limitations of deep learning and exploring its probable future softwarehardware requirements all of this book' code examples use the keras deep-learning framework (keras io)which is open source and free to download you'll need access to unix machineit' possible to use windowstoobut don' recommend it appendix walks you through the complete setup also recommend that you have recent nvidia gpu on your machinesuch as titan this isn' requiredbut it will make your experience better by allowing you to run the code examples several times faster see section for more information about setting up deep-learning workstation if you don' have access to local workstation with recent nvidia gpuyou can use cloud environmentinstead in particularyou can use google cloud instances (such as an -standard- instance with an nvidia tesla add-onor amazon web services (awsgpu instances (such as xlarge instanceappendix presents in detail one possible cloud workflow that runs an aws instance via jupyter notebooksaccessible in your browser source code all code examples in this book are available for download as jupyter notebooks from the book' websitewww manning com/books/deep-learning-with-pythonand on github at licensed to