Abhimanyu Katyayan Leads the Machine Learning team at Ugam and has been involved with the development of their distributed Machine Learning platform. He is experienced in the field of ML and Computer Vision and has been doing it on scale for quitesome time now. His current role is to solve the complex problems of online retail domain while building this distributed platform. Apart from being ML/CV expert he has also been involved extensively with the Big-Data and web application development with Java/Python/Node stacks. He has around 9 years of experience spread across both the halves of engineering and data-science. His areas of interest include architectural design, performance, scalability and availability of distributed machine learning platforms.
Session: Transforming unstructured web into actionable insights using AI
The volume of data is practically exploding by the day. Online retail world is really struggling to stay afloat in this new turbulent big data environment. There are billions of products listed by various online retailers and the depth of product information across retailers varies. Data mining of unstructured data at this scale makes it a very grueling task. With thousands of new products being added every minute, the competitive landscape changes very quickly. It is a daunting task for retailers to keep track of the competition and take any informed decision about their business. The core of the problem is to have the knowledge-base of ‘Matching Products’ across retailers and it is a very complex problem to solve. This session is about our efforts in utilizing Machine Learning on Big-Data to solve this problem.
- ML in product classification
- NLP/ML in Attribute Extraction
- CV in Image processing