Presentations of the PyData Delhi Conference 2019

Date: 9 August 2019

Thank you for being a part of PyData Delhi 2019 Conference.

In order to make the most out of the keynotes, talks and workshops held at PyData Delhi ‘19, we share with you the exceptional presentations by our speakers.

If you use the content, please make sure to credit the original speaker.

Find below the link to each presentation.

DAY 1 (3rd August 2019)

• The Power of Data Science to Measure Unmeasured Parameters in Emerging Markets

  By: Prukalpa Sankar, Co-founder - Atlan

• Fundamental Results in ML and How to Use Them

  By: Jaidev Deshpande,Senior Data Scientist - Gramener

• Intelligent recruitment using NLP and machine learning to identify the most suitable candidates

  By: Victor Robin, Data Science Director - Dunnhumby

• Quantitative Finance with R

  By: Harshit Joshi, Vedant Bonde

• How GPU Computing literally saved me at work

  By: Abhishek Mungoli, Data Scientist

• The Magic of Numpy

  By: Sarah Masud, Software Engineer

• Auria Kathi - The power of Multi Model Machine Learning Pipelines

  By: Sleeba Paul, Machine Learning Engineer - Perleybrook Labs

• Understanding Opacity in Machine Learning Models

  By: Ankit Rathi, Yatin Bhatia

• Research@IIITD

  Hitkul (Link will be updated soon)

• Deepening Democracy through Data: Learnings from Indian Politics and Policy

  By: Roshan Shankar

• Transfer Learning in Natural Language Processing

  By: Janu Verma, Machine Learning Scientist - cure.fit

• Automating Data Pipeline using Apache Airflow

  By: Mridu Bhatnagar, Software Engineer - Goibibo

• Python for Data Science /Machine Learning at Barclays (Sponsored Talk)

  By: Rachita Das, Vice President - Barclays

• Tips, Tricks and Topics in Text Analysis

  By: Bhargav Srinivasa Desikan, Graduate Student - University of Chicago

• Predicting Real-Time Transaction Fraud Using Python and spark (Sponsored Talk)

  By: Mayank Jain, Quantitative Analytics team - Barclays

• Generating tabla note sequences with Markov Chains and Processing/p5.js

  By: Keshav Joshi, Ex-ocean physics researcher -Georgia Tech

DAY 2 (4th August 2019)

• Differentiable Programming: An Exciting Generalization of Deep Neural Networks

  By: Dr. Viral B. Shah, Co-founder and CEO - Julia Computing

• Deep Sequence Models for Attribute Extraction from Product Titles

  By: Deepak Sharma, Senior Data Scientist - Clustr

• Automated Large Scale Forecasting for 1000+ products

  By: Aanish Singla, Nikita Sharma, Data Scientist - Nagarro

• Advance ML- On Improving Performance of Machine Learning Models by Optimizing Hyper-parameters

  By: Anubav kesari, Deep Learning Engineer - Exzeo , Tanay Agrawal, Deep Learning Researcher - Curl Analytics

• Improving Model Lifecycle Management for Machine Learning Models

  By: Pankaj Gupta, Senior Vice President - Barclays

• Building robust AI models against adversarial attacks: Python libraries Cleverhans and Foolbox

  By: Deya Chatterjee, Final-Year Computer Science major

• Using NLP for disaster management

  By: Kaustabh Hiware, SWE - Mercari, Japan

• Building interactive data visualisations with Altair & Django

  By: Rajesh Golani

• Understanding user churn in GoPay (Sponsored Talk)

  By: Karthik Vijayakumar, Sruthi S, Data Scientist - GoPay

• Automating Deep Learning Workflows (Sponsored Talk)

  By: Joinal Ahmed

• Knowledge Graph made simple using NLP and Transfer Learning

  By: Suyog Swami, Senior Data Scientist - dunnhumby

• How I Used Data Visualization in My Quest for the Perfect Wine

  By: Pranav Suri, Research Consultant - WorldQuant LLC

• Machine Learning Security - The Data Scientist’s Guide to Hardening ML Models

  By: Arjun Bahuguna, Cryptography Researcher - Next Tech Lab

• Image Manipulation Detection using Neural Networks

  By: Sonal Kukreja, PhD Research Scholar

Hope this helps.

Regards,

PyData Delhi Team

Written by Aditi Tibarewal, Khushal Vyas and Mayank Singh