Visiting Prof. Ed Raff’s forthcoming book Inside Deep Learning

Congratulation to Dr. Edward Raff for his forthcoming book Inside Deep Learning being published by Manning. The first three chapters are now available free online via Manning’s Early Access Program, with more to come. Dr. Raff is a Chief Scientist at Booz Allen Hamilton and both an alumnus of and visiting assistant professor in the UMBC CSEE department. 

He describes the target audience for his book as “the middle between “give me a tool” and ‘CS/Stats/ML Ph.D. graduate book’ that gives utility and understanding.” He gives thanks to his UMBC students in his Computer Science and Data Science classes who have been “guinea pigs for this book/course material.”

Here’s how the publisher describes the book: “Inside Deep Learning is a fast-paced beginners guide to solving common technical problems with deep learning. Written for everyday developers, there are no complex mathematical proofs or unnecessary academic theory. You’ll learn how deep learning works through plain language, annotated code, and equations as you work through dozens of instantly useful PyTorch examples. As you go, you’ll build a French-English translator that works on the same principles as professional machine translation and discover cutting-edge techniques just emerging from the latest research. Best of all, every deep learning solution in this book can run in less than fifteen minutes using free GPU hardware!”

Ed Raff received a Ph.D. in Computer Science in 2018 with a dissertation on “Malware Detection and Cyber Security via Compression.” He is currently a Chief Scientist at Booz Allen Hamilton. He has done research on deep learning, malware detection, reproducibility in machine learning, detecting fairness and bias in machine learning models and data analytics, and high-performance computing. He has also been a visiting Assistant Professor at UMBC since 2018 and taught in both the Computer Science and Data Science programs. Dr. Raff has over 40 peer-reviewed publications, three best paper awards, and has presented at many major conferences.