How GPU Computing literally saved me at work

Jul 2019

22 Mon

23 Tue

24 Wed

25 Thu 09:15 AM – 05:45 PM IST

26 Fri 09:20 AM – 05:30 PM IST

27 Sat

28 Sun

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Accepting submissions till 15 Jun 2019, 01:00 PM

NIMHANS Convention Centre, Bengaluru

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The Fifth Elephant Winter edition starts at 9:30 am; live stream for members This update is for participants only

##The eighth edition of The Fifth Elephant will be held in Bangalore on 25 and 26 July. A thousand data scientists, ML engineers, data engineers and analysts will gather at the NIMHANS Convention Centre in Bangalore to discuss:

Model management, including data cleaning, instrumentation and productionizing data science.
Bad data and case studies of failure in building data products.
Identifying and handling fraud + data security at scale
Applications of data science in agriculture, media and marketing, supply chain, geo-location, SaaS and e-commerce.
Feature engineering and ML platforms.
What it takes to create data-driven cultures in organizations of different scales.

##Highlights:

1. Meet Peter Wang, co-founder of Anaconda Inc, and learn about why data privacy is the first step towards robust data management; the journey of building Anaconda; and Anaconda in enterprise.
2. Talk to the Fulfillment and Supply Group (FSG) team from Flipkart, and learn about their work with platform engineering where ground truths are the source of data.
3. Attend tutorials on Deep Learning with RedisAI; TransmorgifyAI, Salesforce’s open source AutoML.
4. Discuss interesting problems to solve with data science in agriculture, SaaS perspective on multi-tenancy in Machine Learning (with the Freshworks team), bias in intent classification and recommendations.
5. Meet data science, data engineering and product teams from sponsoring companies to understand how they are handling data and leveraging intelligence from data to solve interesting problems.

##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, model management and versioning data
Demo your ideas in the demo session
Join Birds of Feather (BOF) sessions to have productive discussions on focussed topics. Or, start your own Birds of Feather (BOF) session.

##Full schedule published here: https://hasgeek.com/fifthelephant/2019/schedule

##Contact details:
For more information about The Fifth Elephant, sponsorships, or any other information call +91-7676332020 or email info@hasgeek.com

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How GPU Computing literally saved me at work

Submitted Jun 6, 2019

Session type: Short talk of 20 mins

Distributed/Parallel computing is at the heart of new technology. Every company, big or small want to make most of the technology available to them. One such niche technology is GPU computing. If used cautiously can save a lot of computing efforts and time across the applications. Business, with the boom in Machine learning/Deep learning techniques, are on the way to leverage this technology in their day to day work. Here, I present to you a real time application on how GPU can save computing efforts and reduce the computation time from 2 days to 20 seconds. Talk will cover the best case scenarios and use case for using the GPU for implementing recommendations at scale. The talk will start with the task overview, comparison between CPU and GPU and how and when to utilise GPU for the task in hand and other similar tasks.

Here’s the blog details, I wrote and the talk will be based on it
https://medium.com/walmartlabs/how-gpu-computing-literally-saved-me-at-work-fc1dc70f48b6

Outline

Here’s the blog details, I wrote and the talk will be based on it
https://medium.com/walmartlabs/how-gpu-computing-literally-saved-me-at-work-fc1dc70f48b6

Speaker bio

A seasoned Data Scientist having 3+ years of experience in ML field, with Computer Science background, spanning over various domains and problem-solving mindset. Excelled in various Machine learning and Optimization problems specific to Retail with key interests in Markdowns, Price-elasticity, Item-embeddings, Item-linkage and Price Investment. Enthusiastic about implementing Machine Learning models at scale and knowledge sharing via blogs, talks, and meetups, etc..
Love to explore new places and working out in leisure time.
Medium ~ https://medium.com/@mungoliabhishek81