Ankit Jain currently works as a senior research scientist at Uber AI Labs, the machine learning research arm of Uber. His work primarily involves the application of deep learning methods to a variety of Uber's problems, ranging from forecasting and food delivery to self-driving cars. Previously, he has worked in a variety of data science roles at the Bank of America, Facebook, and other start-ups. He has been a featured speaker at many of the top AI conferences and universities, including UC Berkeley, O'Reilly AI conference, and others. He has a keen interest in teaching and has mentored over 500 students in AI through various start-ups and bootcamps. He completed his MS at UC Berkeley and his BS at IIT Bombay (India).
I am grateful to the Packt team for giving me the opportunity to share my knowledge. Special thanks to Rhea Henriques for her insights and superb editing skills. Lastly, I would also like to thank my co-authors, Armando and Amita, for their suggestions, and my acquisition editor, Varsha Shetty, for approaching me to write the book.
Armando Fandango creates AI empowered products by leveraging his expertise in deep learning, machine learning, distributed computing, and computational methods and has provided thought leadership roles as Chief Data Scientist and Director at startups and large enterprises. He has been advising high-tech AI-based startups. Armando has authored books titled Python Data Analysis - Second Edition and Mastering TensorFlow. He has also published research in international journals and conferences.
I would like to thank Rhea Henriques for her hard work in getting this book published with the highest quality and also for working closely with all the authors. I am grateful to Amita and Ankit for sharing their experience and knowledge.
Amita Kapoor is an Associate Professor at the Department of Electronics, SRCASW, University of Delhi. She has been teaching neural networks for twenty years. During her PhD, she was awarded the prestigious DAAD fellowship, which enabled her to pursue part of her research work at the Karlsruhe Institute of Technology, Germany. She was awarded the Best Presentation Award at the International Conference on Photonics 2008. Being a member of the ACM, IEEE, INNS, and ISBS, she has published more than 40 papers in international journals and conferences. Her research areas include machine learning, AI, neural networks, robotics, and Buddhism and ethics in AI. She has co-authored the book, TensorFlow 1.x Deep Learning Cookbook, by Packt Publishing.
Special thanks to Narotam Singh, without whose help in establishing the cluster it would not have been possible for me to complete this book. Sincere thanks to the principals, Dr. Payal, Ms. Richa, Dr. Punita, and Ms. Deepali, for sanctioning my leave. I would like to thank Armando and Ankit for their insights. I am also grateful to the team at Packt, with special thanks to Manthan Patel for getting me involved in the project, and Rhea Henriques for her support.
Sujit Pal is a technology research director at Elsevier Labs, an advanced technology group within the Reed-Elsevier Group of companies. His areas of interests include semantic searching, natural language processing, machine learning, and deep learning. At Elsevier, he has worked on several initiatives involving search quality measurement and improvement, image classification and duplicate detection, and annotation and ontology development for medical and scientific corpora. He has co-authored a book on deep learning with Antonio Gulli and writes about technology on his blog, Salmon Run.
Meng-Chieh Ling has a PhD in theoretical physics from the Karlsruhe Institute of Technology. After his PhD, he joined The Data Incubator Reply in Munich, and later became an intern at AGT International in Darmstadt. Six months later, he was promoted to senior data scientist and is now working in the field of entertainment.
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