Abstract: Advances in Computer Vision are the leading indicator of progress in the current AI resurgence. Applied Computer Vision is used today by hundreds of millions of users on a daily basis via mobile devices. Many of these applications have been made possible by revival of Convolution Neural Networks powered by advances in machine learning notably deep learning. Popular use cases of Computer Vision are image classification, object detection, scene segmentation and visual question answering. In this session, you will learn how to get started on your Computer Vision journey by learning the fundamental concepts and applications via both the theory and code. We will walk through examples of Image Classification and Object Detection in TensorFlow Keras learning to train and deploy computer vision models. The session will conclude with challenges in training and deploying computer vision models and a brief discussion on the latest in Computer Vision.
Bio: Mo Patel is an independent deep learning consultant advising individuals, startups, and enterprise clients on strategic and technical AI topics. Mo has successfully managed and executed data science projects with clients across several industries, including cable, auto manufacturing, medical device manufacturing, technology, and car insurance. Previously, he was practice director for AI and deep learning at Think Big Analytics, a Teradata Company, where he mentored and advised Think Big clients and provided guidance on ongoing deep learning projects, as well as a management consultant and a software engineer earlier in his career. A continuous learner, Mo conducts research on applications of deep learning, reinforcement learning, and graph analytics toward solving existing and novel business problems and brings a diversity of educational and hands-on expertise connecting business and technology. He holds an MBA, a master’s degree in computer science, and a bachelor’s degree in mathematics.
