NAAMII invites you to the second episode of NAAMII Lecture Series 2019:
“Building Industry Scale Machine Learning Applications: An Experience from Silicon Valley”
Dr. Paras Tiwari, Senior Machine Learning Engineer, Williams-Sonoma Inc.
Dr. Paras B. Tiwari is working as a Senior Machine Learning Engineer at Williams Sonoma Inc., a Silicon Valley based Fortune 500 e-commerce company. He received his PhD in Computer Science from Washington University in St. Louis. His doctoral dissertation is in Machine Learning and Mathematical Optimization. He has worked extensively in Machine learning in healthcare and retail domain. At Williams Sonoma , he is leading the e-commerce team to implement and adapt Machine Learning. Besides his role, Dr. Tiwari has been an active member in the wider machine learning community in Silicon Valley.
The popularity of machine learning technology has been rising in recent days. The companies are adopting machine learning technology in their business operations. The knowledge of building a machine learning application and integrating with the existing Enterprise Application is a crucial skill. In this talk, we will demonstrate the use of Statistics, Mathematics and Computer Science skills to build a machine learning application. The first step in building the machine learning application is to gather and understand the data. We will go through the exploratory data analysis tools from the statistics to demonstrate the slicing and dicing of the data. After understanding the data, we need to build the model. The model building requires expertise in Mathematical Optimization to fit the parameters of the model. We will go over the mathematical optimization and use of it in building the model. Finally, object-oriented programming has been widely used in building the Enterprise Application and we will demonstrate the use of the key concept of object-oriented programming in building the scalable machine learning applications. The presentation will provide a general overview of the steps used in building the machine learning application and will provide a further reference for anyone to explore more into the concept.
Date: Friday, November 8
Time: 3:00- 5:00 pm
Venue: GATE College, Mandikhatar, Kathmandu
Free and Open to the public
Facebook event page: https://www.facebook.com/events/3765048263520727/