Li Jiang
Li Jiang is a senior software engineer at Microsoft China, where he works on data science and AI/ML. He has experience in developing and deploying automated machine learning, distributed deep learning/machine learning, industry AI solutions, and recommendation systems. He holds two PhD degrees from Beijing Normal University and University Toulouse III, where he conducted research on swarm intelligence.
Sessions
In this session, we will provide an in-depth and hands-on tutorial on Automated Machine Learning & Tuning with a fast python library named FLAML. We will start with an overview of the AutoML problem and the FLAML library. We will then introduce the hyperparameter optimization methods empowering the strong performance of FLAML. We will also demonstrate how to make the best use of FLAML to perform automated machine learning and hyperparameter tuning in various applications with the help of rich customization choices and advanced functionalities provided by FLAML. At last, we will share several new features of the library based on our latest research and development work around FLAML and close the tutorial with open problems and challenges learned from AutoML practice.