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
DP
Dileep Patchigolla
@dileep31
Contextual Autocomplete suggestions in Realtime
Submitted May 29, 2020
Autocomplete is a predominant feature in e-commerce search. By being relevant, Autocomplete should help users quickly find the query they intended to type with minimal keystrokes. This talk presents an approach on how this is achieved by considering the users context as a signal. This context is built in real-time using a series of models & fed into a ranking model which re-ranks suggestions accordingly.
Outline
This talk is about how we have improved Autocomplete suggestions at Target using session context. The sequence of ideas will be as follows:
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How Autocomplete is implemented at Target. We will also see the underlying Architecture involved.
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We will then introduce what context is and how it can enhance a user’s shopping experience.
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Implementing context can be done in various ways. We will take an overview of various approaches we can use, with their merits and drawbacks.
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We will then talk about the modeling approach we have taken. We also cover how our model and the underlying architecture support low latency, which is critical for a good Autocomplete experience.
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We will also discuss the various challenges we encountered while doing this.
Requirements
Basic understanding of Deep Learning
Speaker bio
Dileep Kumar is a Lead Engineer at Target, working on various Data Science problems in e-commerce search. Dileep has a decade of experience in the field of Data Science and Data Analytics. He has worked on various problems.
Prior to his current role, he has 10 years of experience solving problems using data science across various industries - friend recommendations & content ranking in social networking, user segmentation & marketing campaign optimization in mobile games, and supply prediction in commodity markets.
His academic background is MS in Analytics from Georgia Tech, and BTech in Mechanical Engineering from IIT Madras.
Links
- Speaker Bio: https://www.linkedin.com/in/dileep-kumar-a747371b/
- Presenter at Haystack 2020: https://haystackconf.com/us2020/context-sensitive-autocomplete/
- ML Expert at GoPrac (a platform to help Engineering students prepare for interviews): https://www.goprac.com/expertlist
- BlogPosts:
- Classification models: https://dpatchigolla.github.io/ai_bytes/classification/index.html#1
- BERT Architecture: https://medium.com/analytics-vidhya/understanding-bert-architecture-3f35a264b187
- Reinforcement Learning https://medium.com/analytics-vidhya/a-gentle-intro-to-reinforcement-learning-4f925b42f31c?source=friends_link&sk=8e349e27eab26282cebc729eb187a224
Slides
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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