Make a submission

Accepting submissions till 15 Jun 2019, 01:00 PM

NIMHANS Convention Centre, Bengaluru

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:

  1. Model management, including data cleaning, instrumentation and productionizing data science.
  2. Bad data and case studies of failure in building data products.
  3. Identifying and handling fraud + data security at scale
  4. Applications of data science in agriculture, media and marketing, supply chain, geo-location, SaaS and e-commerce.
  5. Feature engineering and ML platforms.
  6. 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?

  1. Network with peers and practitioners from the data ecosystem
  2. Share approaches to solving expensive problems such as cleanliness of training data, model management and versioning data
  3. Demo your ideas in the demo session
  4. 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

Anatta

Community Sponsors

Salesforce Ericsson freshworks
databricks

Exhibition Sponsors

Sapient Atlassian GO-JEK
Bayer

Bronze Sponsor

Sumologic Walmart Labs Atlan
Simpl Great Learning

Community Sponsors

Elastic Anaconda Aruba Networks

Hosted by

The Fifth Elephant - known as one the best #datascience and #machinelearning conference in Asia - is transitioning into a year-round forum for conversations about data and ML engineering; data science in production; data security and privacy practices. more

Soma Dhavala

@soma

Building Enterprise grade ML Apps : Tools and Architectures

Submitted Apr 13, 2019

ML Products are unfinished by design. ML Centric quality attributes such as MSE and F1-score etcc are necessary but not sufficient. How do we address this fundamentally unsettling characteristic? And the existing Data Science practices are not scalable beyond the confines. In the first part of the talk, an axiomatic framework is provided to address these issues.

In the secon part of the talk, few architecture patterns, along with their corresponding complementary open source implementations will be discussed, each focusing on a specific aspect.

Specifically,
1) DAGGIT: We will look at a refernce architecture of an ML-As-A-Serice platofrm, wherein much of responsibilty is delegated to the tools, and the developer is only accountable. For example, mundane things such as versioning code, data and runtime are delegated to the tool. Every App is provided as a configuration so that running multiple experiments is akin to changing few options in the configuraiton file. In addition, every App comes with an API. A developer can trigger it on-demand or it can be triggered via an API with a call back – so going from development to deployment or running multuple experiments and monitering them is a breeze.

2) GraphRover: It is not uncommon to see both business use cases and the core telemery structures changing rapidly. It is a double whammy for ML Apps – they have to deal with changing data and evolving use cases. In a reference architecture, we treat every intent as a query, powered by graph engines.

3) IMLY: Data Scientist writing in code in Python and reading csv files and Production Engineer re-writing it in Scala and reading data from Cassandra is not uncommon either. How do we deal with two language problem. We need interporability at two levels: at Data and at Models. We will look at IMLY, an source project aims at making models written in the Pythone ecosytem to many run time environments, including a browser.

4) PAPA: On the data side, we will look at isomorphism between Graph and Relational Data and demonstrate the interporability between them via common interfaces and look at Spark both as an OLAP engine as well an Orchestrator

Outline

Part-1
- Anotomy of an ML App and its life cycle
- Scaling Data Science: issues and challanges
- An axiomatic framework
Part-2
- daggit: ML-As-A-Serice reference platform. Delegate repsonsibility to tools
- GraphRover: Every ML intent is a query. Outsource coding to graph and db engines
- imly: exploit the power of deep learning to achieve ML model interoparability
- papa: make database hopping a reality. abtract out the database details – only focus on the intent.

Speaker bio

Soma S Dhavala is freelance consultant operating at the interface of Statistics, Machine Learning, Computing, and Internet of Things. His interests are in Graphs, Meta Machine Learning and their application in representing, and reasoning with information. Since last few years, he has been working on ML-as-Infrastructure.

Soma currently consults for Framewirk, is a member of the Design Council at EkStep. Since 2014 and is leading the efforts in designing Machine Learning Infrastructure and developing various DataProducts concerned with Learning such as Recommendation Engines, Auto-Tagging Content. He designed and ran a Deep Learning and Natural Language Processing immersive bootcamp for NIIT. He is also working on Deep Variational Inference with his collaborators in the academia. He is also a co-founder of VitalTicks Pvt Ltd, a start-up in the digital health care space.

In the past, Soma worked with Dow AgroSciences in the area of ML applications in Systems Biology and with General Electric Global Research Center in the area of Information Theory and Parallel Computing.

Soma obtained his Ph.D (TAMU, 2010) in Statistics where he worked on applying Bayesian Nonparametrics to systems biology (2010), has a Masters (IIT-M, 2000) in EE and a B.E (SRKREC-Andhra University, 1997) in ECE. He also worked as a post-doc close to a year in the area of Dynamical Systems at TAMU. He has over 10+ publications and multiple patents.

Slides

https://docs.google.com/presentation/u/1/d/1OBc5aqAMTtb9ZrBWOlTCVAN9SbO5q7wzlUmYx_ywjqM/edit?usp=sharing

Comments

{{ gettext('Login to leave a comment') }}

{{ gettext('Post a comment…') }}
{{ gettext('New comment') }}
{{ formTitle }}

{{ errorMsg }}

{{ gettext('No comments posted yet') }}

Make a submission

Accepting submissions till 15 Jun 2019, 01:00 PM

NIMHANS Convention Centre, Bengaluru

Hosted by

The Fifth Elephant - known as one the best #datascience and #machinelearning conference in Asia - is transitioning into a year-round forum for conversations about data and ML engineering; data science in production; data security and privacy practices. more