Women in Data Science (WiDS)
  • Home
  • About
    • Blog
    • WiDStory
    • News
    • Sponsors
    • Collaborators
    • Contact
    • Donate
  • Conference
    • Regional Conferences 2022
    • WiDS 2022 Videos
    • Schedule 2022 >
      • In-person Schedule 2022
      • Online Schedule 2022
    • Speakers 2022
    • Ambassadors 2022
    • WiDS Ambassador Program
    • Past Conferences >
      • WiDS 2021
      • WiDS 2020
      • WiDS 2019
      • WiDS 2018
      • WiDS 2017
      • WiDS 2015
    • Conference Committee
  • Datathon
    • Excellence in Research Award 2022
    • Datathon Resources
    • WiDS Datathon Workshops 2022
    • Datathon News
    • Datathon Collaborators
    • Datathon Committee
  • Podcast
    • Podcast Committee
  • Education
    • Workshops >
      • Workshop Instructors
      • Workhop Committee
    • Secondary Schools >
      • Secondary School Resources
      • Education Outreach Committee
      • Education Outreach Student Advisors

Riyanka Bhowal

Senior Data Scientist
Walmart Global Tech
Picture
Riyanka is a Senior Data Scientist at Walmart Global Tech in Bangalore with nearly 6 years of experience in statistical modeling & machine learning. She has a Master's in degree Applied Statistics & Informatics from Indian Institute of Technology, Bombay (IIT Bombay). Presently, as a part of Digital Facilities team, Riyanka is developing scalable anomaly detection algorithms leveraging IoT sensor data to provide insights into store asset lifecycle decisions.
​

Workshop: Natural Language Processing
June 30, 10:15-11:00 am PST
Prerequisite: Basics of Neural Network, RNN/LSTM.
​Please install Anaconda and Jupyter, and download
 this csv file & python notebook prior to the workshop.
​

Natural language processing has direct real-world applications, from speech recognition to automatic text generation, from lexical semantics understanding to question answering. In just a decade, neural machine learning models became widespread, largely abandoning the statistical methods due to its requirement of elaborate feature engineering. Popular techniques include use of word-embeddings to capture semantic properties of words. In this workshop, we take you through the ever-changing journey of neural models while addressing their boons and banes.

The workshop will address concepts of word-embedding, frequency-based and prediction-based embedding, positional embedding, multi-headed attention and application of the same in unsupervised context. ​
Watch Workshop

Back to ​Workshop Instructors

Initiatives

Conference
Ambassador Program
Datathon
Podcast
Workshops for Everyone
Outreach for Secondary Schools

Follow Us

LinkedIn
Twitter
Facebook
Instagram
YouTube
​Blog

connect

LinkedIn Group
Facebook Group
subscribe
donate

© 2022 Women in data science. Women in Data Science is a Registered trademark of Stanford University. 

  • Home
  • About
    • Blog
    • WiDStory
    • News
    • Sponsors
    • Collaborators
    • Contact
    • Donate
  • Conference
    • Regional Conferences 2022
    • WiDS 2022 Videos
    • Schedule 2022 >
      • In-person Schedule 2022
      • Online Schedule 2022
    • Speakers 2022
    • Ambassadors 2022
    • WiDS Ambassador Program
    • Past Conferences >
      • WiDS 2021
      • WiDS 2020
      • WiDS 2019
      • WiDS 2018
      • WiDS 2017
      • WiDS 2015
    • Conference Committee
  • Datathon
    • Excellence in Research Award 2022
    • Datathon Resources
    • WiDS Datathon Workshops 2022
    • Datathon News
    • Datathon Collaborators
    • Datathon Committee
  • Podcast
    • Podcast Committee
  • Education
    • Workshops >
      • Workshop Instructors
      • Workhop Committee
    • Secondary Schools >
      • Secondary School Resources
      • Education Outreach Committee
      • Education Outreach Student Advisors