The last mile problem in ML

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

Tickets

##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

#Sponsors:

Sponsorship Deck.
Email sales@hasgeek.com for bulk ticket purchases, and sponsoring 2019 edition of JSFoo:VueDay.

JSFoo:VueDay 2019 sponsors:

#Platinum Sponsor

#Community Sponsors

#Exhibition Sponsors

#Bronze Sponsor

#Community Sponsors

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The Fifth Elephant

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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The last mile problem in ML

Submitted Apr 10, 2019

“We have built a machine learning model, What next?”

There is quite a bit of journey that one needs to cover from building a model in Jupyter notebook to taking it to production.
I would like to call it as the “last mile problem in ML” , this last mile could be a simple tread if we embrace some good ideas.

This talk covers some of these opinionated ideas on how we can get around some of the pitfalls in deployment of ML models in production.

We would go over the below questions in detail think about solutions for them.

How to fix the zombie models apocalypse, a state when nobody knows how the model was trained ?
In Science, experiments are found to be valid only if they are reproducible. Should this be the case in Datascience as well ?
Training the model in your local machine and waiting for an eternity to complete is no fun. What are some better ways of doing this ?
How do you package your machine learning code in a robust manner?
Does an ML project have the luxury of not following good Software Engineering principles?

Outline

Discussion on some of the issues with deploying ML models to production.
Discussion about mlflow including a quick demo.
Discussion about sagemaker BYO algorithms training.
Discussion about packagining ML code in a robust manner.

Requirements

Highlevel understanding of machine learning.

Speaker bio

Hello World,

My name is Krishna Sangeeth. I am currently working as a DataScientist @ Ericsson Global AI Accelerator (GAIA) . Prior to Ericsson, I was working @ Indix as an ML Engineer. I am a passionate programmer always on the look out for learning something new. I am an opensource enthusiast and have been able to make successful contributions to some of my favorite projects such as scikit-learn , mlflow, sagemaker etc.

Github : @whiletruelearn
Twitter : @whiletruelearn