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:
- Model management, including data cleaning, instrumentation and productionizing data science.
- Bad data and case studies of failure in building data products.
- Identifying and handling fraud + data security at scale
- Applications of data science in agriculture, media and marketing, supply chain, geo-location, SaaS and e-commerce.
- Feature engineering and ML platforms.
- What it takes to create data-driven cultures in organizations of different scales.
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?
- Network with peers and practitioners from the data ecosystem
- Share approaches to solving expensive problems such as cleanliness of training data, model management and versioning data
- Demo your ideas in the demo session
- 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
For more information about The Fifth Elephant, sponsorships, or any other information call +91-7676332020 or email firstname.lastname@example.org
JSFoo:VueDay 2019 sponsors:
Machine learning to save lives on the road
Session type: Full talk of 40 mins Session type: Full talk of 40 mins
Every year over 1.3M people die on roads. In recent years the rates of fatality and collisions have increasingly gone upward, reversing a several decade long downward trend.
At Zendrive, we use smartphone data to understand and decode unsafe driving behaviours like aggression, non- adherence to the rules of the road and distraction. Using sophisticated machine learning techniques and massive amounts of data (150B miles of data over 50M users), we have built the world’s leading driving behaviour analysis platform that has already helped save hundreds of lives.
A core component of this platform is an algorithm to detect vehicular collisions. In this talk, we aim to take you on the fascinating journey of building this algorithm through myriads of challenges - smartphone sensors, data acquisition, detection of rare events, testing, and so on. The talk will highlight how these challenges were overcome through a combination of creative problem-solving and sophisticated ML techniques.
Why have a collision detection algorithm?
- Saving lives by speeding up emergency response
- Measure of risk on the road
High level challenges
- Rare event (1 per million miles)
- Mix of time-scales
- Smartphones - no custom hardware
Building an MVP
- Where is the data?
– OEMs, Being creative with misuse!
– Handling 3 phases
– Ensemble of ensembles
- Roller coasters, bumping into bins, skydiving!
Data - More and more and more
- Customer feedback
- Manual review - label noise
Algorithm - sophistication
- Physics + Data + Machine learning
- Largest repository of collision data
- Most widely used smartphone based algorithm
- Deep learning
Looking back - what have we learnt?
[The sequence appears in the talk attached below (timestamp from 6 min to 27 mins)]
Aditya Karnik is Director of Data Science at Zendrive. He has 14+ years of experience in academic and industrial research labs. His interests are in Mathematical modeling, Optimization & control and Predictive modeling.