"Solving Challenging e-Commerce Problems Using Different Aspects of Data Science"

"This talk will show how we leveraged different aspects of data science (machine learning, NLP, statistical analysis, computer vision, ..etc) to solve challenging problems in e-commerce. The talk aims to clarify that data science is NOT just machine learning."

"Khalifeh AlJadda holds Ph.D. in computer science from the University of Georgia (UGA), with a specialization in machine learning. He has experience implementing large-scale, distributed machine learning algorithms to solve challenging problems in domains ranging from Bioinformatics to search and recommendation engines. He is a Sr. Manager Data Science at Home Depot, which is the largest home improvement company in the world. He is currently leading the recommendation data science team at Home Depot which is in charge of building the new generation of Home Depot's recommendation engine. Before joining Home Depot he was in charge of the data science initiative to design and implement the backend of CareerBuilder’s language-agnostic semantic search engine leveraging NLP, Apache Spark and the Hadoop ecosystem. He also led the team on building a new AI-based recommendation engine using cutting-edge technologies for CareerBuilder."