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:
- 3-4 talks each, on concepts, applications and tools.
- 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 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
- ML engineers who want to learn about concepts in maths, stats and strengthen foundations.
- ML engineers wanting to learn from experiences and insights of others.
- Senior architects and decision-makers who want to quick run-through of concepts, implementation case studies, and overview of tools.
- Masters and doctoral candidates who want to bridge the gap between academia and practice.
Proposals will be shortlisted and reviewed by an editorial team consisting of practitioners from the community. Make sure your abstract contains the following information:
- Key insights you will present, or takeaways for the audience.
- 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:
- A detailed outline, or
- Mindmap, explaining the structure of the talk, or
- 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.
Anthill Inside Miniconf – 24 November, 2017.
Hands-on workshops – 25 November, 2017.
For more information about speaking, Anthill Inside, sponsorships, tickets, or any other information contact email@example.com or call 7676332020.
Applied Machine Learning for realtime #FairPlay against Fraud
For any firm processing online transactions, ensuring a strong shield against fraud is of top priority. And for platforms hosting fantasy sports and online gaming, ensuring a fair play from all users and real-time fraud detection is a first line of defence. Traditionally, rule based engines formed the crux of anomaly and fraud detection. But maintaining a rule engine and adapting to new patterns of abuse are tedious tasks. We’ll see how Machine learning can help us ensure fair play on the platform using user and system finger printing.
- Challenges at Dream11, India’s largest fantasy sports platform
- Referral and promotional events, user registration and game play.
- User data collection and preparing training data
- Regression and Gradient Boosted Models
- Scaling up for real-time decision making
- Business impact and key takeaways
Beginner to Intermediate level of M/L basics
Aditya Prasad Narisetty is a Sr. Data Scientist @Dream11 building data driven products from fraud prevention, User & Revenue estimation, marketing attribution, data pipelines and real-time M/L intelligence. Earlier, he was heading the Data Science team at Craftsvilla building recommendation systems, Data Platform, Search, Autosuggestion, real-time inventory profiling, and Fashion Recognition using CNNs.
He’s an avid speaker in the Mumbai machine learning community presenting at GDG Mumbai‘17, AWS conf‘16, DataNativesX, HYSEA IIT-H, Mumbai AI meetup and a couple of other meetups in Mumbai.