Artificial Intelligence and its Applications

-- This is a FREE event--

Bangalore AI/ML Meetup invites you to this special meetup to get you started with Artificial Neural Network and Deep Learning.

Detailed Agenda:

10:15 AM - 10:30 AM: Registration & Welcome / Introduction

10:30 AM –11:15 AM: Talk 1 by Piyush Makhija, Machine Learning Engineer at Vahan Inc.,(https://www.linkedin.com/in/piyushmakhija/, http://piyushmakhija.com/)

Talk 1 Details:
Logistics companies, both old and new, have invested heavily in building an efficient frontline workforce to provide swift and convenient services to their users. Timely delivery is often a critical deciding factor for the ever-impatient customers to choose service A over service B. Hence, operations/logistics team is a key enabler. The attrition rate in large frontline teams is high, close to 75 percent annually. Yet most companies have aggressive growth targets, necessitating recruitment of high volumes of workers constantly. High-growth companies in this domain like Zomato and Swiggy, grew by more than 50-60 percent by the end of 2018, recruited tens of thousands of delivery boys every month. Vahan Inc. has developed an AI-driven virtual assistant that helps logistics companies scale and automate their hiring process by leveraging the common addiction of messaging applications like WhatsApp and FB messenger. In this talk, the speaker will cover in detail how they developed a complete data collection and natural language processing pipeline for Indian languages and built a chatbot over Whatsapp which is currently connecting companies like Dunzo, Zomato, Swiggy & Rapido Express with potential frontline workers and fulfilling the hiring requirements of this industry in a scalable and autonomous fashion.

11:15 AM - 12:00 Noon: Talk 2 by Ashay Tamhane, Staff Data Scientist at Swiggy,(https://www.linkedin.com/in/ashaytamhane)

Talk 2 Details:
Understanding nuances in user behaviour is critical for solving any user-centric Data Science problem. In this talk, the speaker will show examples of such nuances and how they lead to critical inputs in the core data science algorithm that one works with. We will look at real Data Science use cases from different domains and understand how user behaviour fundamentally impacts the respective algorithms.

12:00 Noon – 12:15 PM: Tea Break

12:15 PM - 1:15 PM - Talk 3 by Narasimha Medeme, Director Data Science,MakeMyTrip.com(https://www.linkedin.com/in/narasimhamedeme/)

Talk 3 Details:
Ranking is one of the many interesting problems we work on. While there is a diverse set of ranking frameworks, ranging from collaborative filtering to context/content-based recommenders or reinforcement learning-based recommenders, one of the common thematic framework is learning-to-rank. There are interesting literature and wide application of this framework at Microsoft, LinkedIn, AirBnb to name a few.
This talk will introduce the theory, journey of MakeMyTrip using multiple methods, evaluation metrics, loss functions, and a couple of NN architectures, a few important aspects to solve beyond model form. Based upon time availability we might touch upon a few example codes via PyTorch.

Please do not RSVP / Waitlist here. Please register in the konfhub page: https://konfhub.com/cm21sep

Heartiest thanks to Citrix for hosting / sponsoring this meetup.