Anthill Inside Miniconf – Pune

Machine Learning, Deep Learning and Artificial Intelligence: concepts, applications and tools.

##About the event

When it comes to Machine Learning (ML), Deep Learning (DL) and Artificial Intelligence (AI), three aspects are crucial:

  • Clarity of fundamental concepts.
  • Insights and nuances when applying concepts to solve real-world problems.
  • Knowledge of tools for automating ML and DL.

Anthill Inside Miniconf will provide understanding on each of these fronts.


This miniconf is a full day event consisting of:

  1. 3-4 talks each, on concepts, applications and tools.
  2. Birds of Feather (BOF) sessions on focussed topics.

We are accepting proposals for:

  • 10 to 40-minute talks, explaining fundamnetal concepts in math, statistics and data science.
  • 20 to 40-minute talks on case studies and lessons learned when applyng ML, DL and AI concepts in different domains / to solve diverse data-related problems.
  • 10 to 20-minute talks on tools on ML and DL.
  • Birds of a Feather (BOF) sessions on failure stories in ML, to what problems / use cases should you use ML and DL, chatbots.
  • 3-6 hour hands-on workshops on concepts and tools.

##Hands-on workshops

Hands-on workshops for 30-40 participants on 25 November will help in internalizing concepts, and practical aspects of working with tools.
Workshops will be announced shortly. Workshop tickets have to be purchased separately.

##Target audience, and why you should attend this event

  1. ML engineers who want to learn about concepts in maths, stats and strengthen foundations.
  2. ML engineers wanting to learn from experiences and insights of others.
  3. Senior architects and decision-makers who want to quick run-through of concepts, implementation case studies, and overview of tools.
  4. Masters and doctoral candidates who want to bridge the gap between academia and practice.

##Selection process

Proposals will be shortlisted and reviewed by an editorial team consisting of practitioners from the community. Make sure your abstract contains the following information:

  1. Key insights you will present, or takeaways for the audience.
  2. Overall flow of the content.

You must submit links to videos of talks you have delivered in the past, or record and upload a two-min self-recorded video explaining what your talk is about, and why is it relevant for this event.

Also consider submitting links to the following along with your proposal:

  1. A detailed outline, or
  2. Mindmap, explaining the structure of the talk, or
  3. Draft slides.

##Honorarium for selected speakers; travel grants

Selected speakers and workshop instructors will receive an honorarium of Rs. 3,000 each, at the end of their talk. We do not provide free passes for speakers’ colleagues and spouses.

Travel grants are available for domestic speakers. We evaluate each case on its merits, giving preference to women, people of non-binary gender, and Africans.
If you require a grant, mention this in the field where you add your location. Anthill Inside Miniconf is funded through ticket purchases and sponsorships; travel grant budgets vary.

##Important dates

Anthill Inside Miniconf – 24 November, 2017.
Hands-on workshops – 25 November, 2017.

##Contact details:
For more information about speaking, Anthill Inside, sponsorships, tickets, or any other information contact or call 7676332020.

Hosted by

Anthill Inside is a forum for conversations about Artificial Intelligence and Deep Learning, including: Tools Techniques Approaches for integrating AI and Deep Learning in products and businesses. Engineering for AI. more

Harshad Saykhedkar


Bayesian methods in data analysis, an introduction

Submitted Oct 12, 2017

If you are in a sector where the outcome of your data analysis and machine learning work has significant monetory impact, then you should learn bayesian data analysis!

Bayesian methods in data analysis have been around for a long time. They are immensely helpful in solving complex decision analysis problems. Bayesian analysis is intuitively simple to understand and is computationally tractable
thanks to modern softwares like stan and pymc. On the other hand, they are rarely covered in introductory data analytics courses or even in engineering/college syllabus.

The purpose of this talk is to,

  • Answer ‘why should you care about bayesian methods for data analysis?’
  • Show their applicability and usefulness.
  • Cover few interesting and fun examples (through code).


  1. Start with basics of bayesian methods, few historical anecdotes about the multiple interpretations of probability.
  2. Cover practical examples and problem statements which are best analysed with bayesian methods.
  3. Show some live coding examples using open source government datasets from fields like econometrics or agriculture or healthcare.
  4. Scratch the surface about algorithmic implementations: how the famous ‘markov chain monte carlo’ MCMC methods work.
  5. Quick review of libraries/tools (pymc).
  6. If you are excited with the idea, how can you study further?


A basic understanding of probability will help to understand the talk. The code examples will be in Python so some familiarity with Python is good too.

Speaker bio

I work as head of data science at, an advertising technology startup based out of Pune. I have 7+ years of experience in data science and started in the field before it was a buzzword :-P. I have built multiple products, handled consulting assignments and delivered solutions using machine learning, R and Python. I hold a Master’s degree in Operations Research from Indian Institute of Technology, Mumbai.

Bayesian methods have been my area of interest for a long time. Over the years, I have formed few opinions about their usefulness and tried my best to understand the underlying theory, that I would like to share through this talk.



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Hosted by

Anthill Inside is a forum for conversations about Artificial Intelligence and Deep Learning, including: Tools Techniques Approaches for integrating AI and Deep Learning in products and businesses. Engineering for AI. more