About

Umang Sharma is a Senior Data Scientist and Deep Learning Engineer with a passion for the mathematics behind Deep Learning. He is well-versed in Probability, Statistics, and Calculus, and has worked on a number of problems in Computer Vision and NLP. Umang is the author of a book on Deep Learning with TensorFlow, published by Wiley Publications, and has been featured in Google's machine learning crash course magazine multiple times. Umang works at the intersection of data and machine learning to build and deploy ML systems that redefine products. He is a visiting faculty member at IITs/IIMs, teaching subjects like Linear Algebra, Statistical Modelling, AI Strategy, and AI Product Management. Umang is known for his ability to ship data science and ML systems (end-to-end) for products and deliver results using multiple training and deployment strategies, including Kubernetes, Databricks, and cloud platforms. He is also an open source contributor to Google Colab and an official speaker of Google's ML crash course. Umang has worked as a Senior Data Scientist at TomTom, where he worked on projects such as search ranking improvement of Point of Interests using various features with NLP and ML, semantic and panoptic segmentation of multiple image sources on a highly background imbalanced data, MLOps on Deep Learning models, and PyTorch-based highly optimized distributed training. He is currently working as a Tech Reviewer at O'Reilly Media, where he reviewed the book Essential Math for AI and was featured on the first page of the book. Umang has a Bachelor of Technology degree in Information Technology from Guru Gobind Singh Indraprastha University and has relevant experience of 7.45 years. His tech stack includes Deep Learning, Research Scientist, Data Scientist, ML, TensorFlow, AI, Python, Computer Vision, NLP, AWS, Object Detection, Product Manager, Databricks, Kubernetes, Neural Networks, Azure, CNN, Big Data, Docker, SQL, GCP, Video Classification, Text Classification, Reinforcement Learning, Naive Bayes, Keras, Hadoop, Spring Boot, Spring, Search, PyTorch, Web, Django, and Apache Hive.