The Fifth Elephant 2018

The seventh edition of India's best data conference


The power of intuition in data science, and why it will always have a role

Submitted by Avi Patchava (@avipatch) on Wednesday, 4 July 2018

Section: Full talk Technical level: Beginner

View proposal in schedule


Data science, fueled by big and growing datasets, has enabled the rapid discovery of new relationships and predictability in the world. If the algorithm can find the relationships backed by mountains of historical data, why the role of intuition? This seems counter to the purpose and modus operandi of data science. This talk will explain why intuition remains vital to Data science: 1) What it is; 2) How it combines with algorithms; 3) Examples of its impact across data science use cases; 4) Our 7 tip on how to develop it.


  • Context setting: why does a subject driven by data need the notion of intuition? Isn’t intuition akin to black magic?
  • What is intuition: perspectives and definitions
  • Where does intuition come from? What is the science behind it?
  • Why is intuition needed even in data science, where we have abundant data
  • What does it take to develop intuition as a data scientist? Our 7 tips
  • Is intuition the Data scientist’s defence against replacement by machine?


Nothing - will use slides and discuss specific examples

Speaker bio

Avi Patchava is Vice-President of Data Sciences, Machine Learning and Artificial Intelligence at InMobi – a leading Indian company in the world of Mobile AdTech. Previously, he was with McKinsey&Co driving large-scale machine learning initiatives in sectors such as Banking, Automotive, and Manufacturing. His background is in economics and the social sciences, with Masters’ degrees from the University of Oxford and the London School of Economics



  • Avi Patchava (@avipatch) Proposer a year ago

    Will be available after Thursday - when the talk is happening

  • Akshay Sehgal (@akshaysehgal) a year ago

    Hi Avi, great session. Will request you to share the document you presented.

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  • emily isla 5 days ago

    We will usually make quite exact intuition-primarily based selections for situations in which we are familiar, however, our intuition cannot help us with the unfamiliar. Statistics, however, is neutral, but the machines processing information does not have information on what they’re processing. The facts are best an imprint.

  • Denzel Paul (@denzelpaul05) a day ago

    The capacity to acquire information without evidence, proof, or conscious reasoning, or without understanding how the information became acquired. A factor that one knows or considers in all likelihood from instinctive feeling rather than aware reasoning.

  • Gnana Bharathy (@gkbharathy) a year ago

    The idea is sound and that is why we recommend that data scientist be also design thinkers. However, the full article/ talk is not available to view.

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