Anthill Inside Miniconf – Pune
Machine Learning, Deep Learning and Artificial Intelligence: concepts, applications and tools.
Nov 2017
20 Mon
21 Tue
22 Wed
23 Thu
24 Fri 10:00 AM – 05:50 PM IST
25 Sat
26 Sun
##About the event
When it comes to Machine Learning (ML), Deep Learning (DL) and Artificial Intelligence (AI), three aspects are crucial:
Anthill Inside Miniconf will provide understanding on each of these fronts.
##Format
This miniconf is a full day event consisting of:
We are accepting proposals for:
##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
##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:
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:
##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 support@hasgeek.com or call 7676332020.
Hosted by
Swapnil Dubey
@swapnildubey
Submitted Nov 14, 2017
With the increase in data size for running DS models,it is important to look into possible infrastructure options which provide enough scalability to run DS algo successfully.Optimal use of infrastructure in terms of cost is the need of hour.For example,running task using multiple GPU for finite amount of time. Almost all the Cloud vendors(AWS,Google,Microsoft) provide different kind of services for this situation.This talk will primarily make a comparison into advantages and disadvantes of such services provided by cloud providers.It will also look into various options for running tasks in a particular cloud provider.
The presentation is purely on the basis of study which we did in the past.
Data scince on Cloud:
Importance of running DS on Cloud?
Options for running ML on cloud platform
- Using native compute and storage only.
- Hosted Data platfrom
- Machine Learning Services
- Congnitive API Services.
Demo : Using Cognitive Services of Google Cloud Platform- GCP vision API.
Options for running scalable DS models on Cloud:(Advantage, Disadvantage, Pricing)
- AWS
- Azure Machine learning
- Google Cloud ML
Other providers: IBM bluemix vs Sense.io vs Domino datalab vs Datajoy
Demo: Running DS models using Tensorflow on Google Cloud ML(Using GPUs).
Hosted by
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