The Fifth Elephant 2020 edition
On data governance, engineering for data privacy and data science
The ninth edition of The Fifth Elephant will be held in Bangalore on 16 and 17 July 2020.
The Fifth Elephant brings together over one thousand data scientists, ML engineers, data engineers and analysts to discuss:
- Data governance
- Data privacy and engineering for privacy including engineering for Personal Data Protection (PDP) bill.
- Data cleaning, annotation, instrumentation and productionizing data science.
- Identifying and handling fraud + data security at scale
- Feature engineering and ML platforms.
- What it takes to create data-driven cultures in organizations of different scales.
**Event details:
Dates: 16-17 July 2020
Venue: NIMHANS Convention Centre, Dairy Circle, Bangalore
Why you should attend:
- Network with peers and practitioners from the data ecosystem.
- Share approaches to solving expensive problems such as cleanliness of training data, annotation, model management and versioning data.
- Demo your ideas in the demo sessions.
- Join Birds of Feather (BOF) sessions to have productive discussions on focussed topics. Or, start your own Birds of Feather (BOF) session.
Contact details:
For more information about The Fifth Elephant, call +91-7676332020 or email sales@hasgeek.com
Hosted by
The Fifth Elephant - known as one of the best data science and Machine Learning conference in Asia - has transitioned into a year-round forum for conversations about data and ML engineering; data science in production; data security and privacy practices. more
IK
Imaad Mohamed Khan
@imaadmkhan1
Finding high propensity users for Delivery Jobs
Submitted May 31, 2020
At Vahan, we’re helping 300M+ low-skilled workers in India find jobs using WhatsApp. One of the major categories of jobs where we help find people is Delivery jobs. For our marketing campaigns, we wanted to be able to identify the users that have a high propensity towards taking up Delivery Jobs. We will talk about how we iterated over the process of building models and feature engineering to come up with different versions of our model in a limited period of time.
This talk will benefit Data Analysts, Data Scientists and other professionals looking to build propensity models.
Key Learnings for participants: End to end data science project flow, what is propensity modeling, is propensity modeling = causality?, feature engineering, feature engineering techniques, model selection, model evaluation, convert a business problem to data problem.
Outline
Introduction
Company Introduction - Talk about what we do as a company here
Speaker Introduction - Talk a little about what I have done so far
Problem we’re solving - Propensity of users - Why is it important to solve for us?
Introduction to Propensity Modeling - Introduce various propensity modeling techniques in the literature
Propensity Modeling and Causality, are they related? - Related discussion to compare propensity modeling with causality
Data Collection
Understanding the data - Describe the process of collecting our data
Label Selection - process of selection - Describe the process of arriving at how we selected our label
Missing data imputation - Talk about techniques used to impute missing data
Modeling
Iteration
First version - Clustering with some features
Second version - Better Feature Engineering (explain different techniques of feature engineering here) with a Supervised Learning approach
Evaluation
Metrics for each approach - Custom Metric to evaluate clustering, F1-Score, Precision, Recall for the supervised learning approach
Deployment
Release of the cohorts to the marketing teams
Requirements
A basic understanding of Machine Learning concepts - Supervised, Unsupervised Learning, Evaluation Metrics
Speaker bio
Imaad Mohamed Khan is a Data Scientist, Content Creator and an Educator. He graduated with a Masters in Internet Technologies and Information Systems from TU Braunschweig, Germany. He did his Bachelors in Electronics and Communication from M S Ramaiah Institute of Technology, Bangalore. He is currently working as a Data Scientist at Vahan. Earlier, he was the co-founder and CTO of Recreate.ai. Prior to that, he was working as a Data Scientist at Indegene where he worked on multiple Data Science and NLP projects. He is also a Content Creator on LinkedIn and writes on topics related to Data Science, Machine Learning and Artificial Intelligence.
Links
Slides
https://docs.google.com/presentation/d/1vie2EQfZFSQVxY40nk73jw-Uwqph0_EhYRXALWMkFC4/edit?usp=sharing
Comments
Hosted by
The Fifth Elephant - known as one of the best data science and Machine Learning conference in Asia - has transitioned into a year-round forum for conversations about data and ML engineering; data science in production; data security and privacy practices. more
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