Considerations for Machine Learning in the Wild

Moving any technology from theory to practice involves surprises, and machine learning (ML) is no exception. In this presentation, we will share lessons from applying ML in consumer, health care, manufacturing, and industrial applications. We will set the stage with a quick review of the ML pipeline. The remainder of the talk will focus sequentially on each step in the pipeline discussing practical considerations, common mistakes, and relevant tips.

Presenters: Saber Taghvaeeyan & Hamid Mokhtarzadeh

Saber has expertise in machine learning, time-series analysis, and sensor fusion. He enjoys developing end-to-end solutions involving data acquisition, analysis, and visualization. He has led projects in different industries including medical devices, wearable devices, intelligent consumables, food safety, and manufacturing.

Hamid is passionate about navigation systems, estimation, and sensor fusion. He has academic, industry, and teaching experiences all in the area of positioning and navigation, sensor fusion, and software for scientific and engineering applications.