{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/practical-deep-learning-for-cloud-mobile-and","title":"Practical Deep Learning for Cloud, Mobile, and Edge","arxiv_id":null,"date":"2019-10-01","proceeding":null,"authors":["Anirudh Koul","Siddha Ganju","Meher Kasam"],"abstract":"Whether you’re a software engineer aspiring to enter the world of deep learning, a veteran data scientist, or a hobbyist with a simple dream of making the next viral AI app, you might have wondered where to begin. This step-by-step guide teaches you how to build practical deep learning applications for the cloud, mobile, browsers, and edge devices using a hands-on approach.\r\n\r\nRelying on years of industry experience transforming deep learning research into award-winning applications, Anirudh Koul, Siddha Ganju, and Meher Kasam guide you through the process of converting an idea into something that people in the real world can use.\r\n​\r\nTrain, tune, and deploy computer vision models with Keras, TensorFlow, Core ML, and TensorFlow Lite\r\nDevelop AI for a range of devices including Raspberry Pi, Jetson Nano, and Google Coral\r\nExplore fun projects, from Silicon Valley’s Not Hotdog app to 40+ industry case studies\r\nSimulate an autonomous car in a video game environment and build a miniature version with reinforcement learning\r\nUse transfer learning to train models in minutes\r\nDiscover 50+ practical tips for maximizing model accuracy and speed, debugging, and scaling to millions of users","url_abs":"https://www.practicaldeeplearning.ai/","url_pdf":"https://www.practicaldeeplearning.ai/","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"practical-deep-learning-for-cloud-mobile-and","repo_url":"https://github.com/practicalDL/Practical-Deep-Learning-Book","is_official":1,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"tf","reach":null}],"tasks":[{"task_slug":"deep-learning","task_name":"Deep Learning"},{"task_slug":"transfer-learning","task_name":"Transfer Learning"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}