A conference on data, machine learning, and distributed and parallel computing
Jul 2015
13 Mon
14 Tue
15 Wed
16 Thu 08:30 AM – 06:35 PM IST
17 Fri 08:30 AM – 06:30 PM IST
18 Sat 09:00 AM – 06:30 PM IST
19 Sun
Submissions are closed for this project
NIMHANS Convention center
Harnessing the power of the Erlang VM at Housing
Abhijit Pratap Singh
Keeping Moore's law alive: Neuromorphic computing
Anand Chandrasekaran
The many ways of parallel computing with Julia
Viral B. Shah
Revolutionizing travel with ML & Analytics – An insight into business optimization using Machine Learning and Advanced Analytics
Raghu Kashyap
Keynote: "Thinking Machines"
Shailesh Kumar
Making a contextual recommendation engine using Python and Deep Learning at ParallelDots
Muktabh Mayank
Keynote: Future patterns in data processing (sponsored)
Amod Malviya
Using Modes for Time Series Classification
Rohit Chatterjee
Deep Learning for Natural Language Processing
Devashish Shankar
Escher - democratizing beautiful visualizations
Shashi Gowda
Visualising Multi Dimensional Data
Amit Kapoor
Recommendation System beyond traditional Collaborative filtering
Gagandeep Juneja
Building Recommender system
Swaroop Krothapalli
Building a E-commerce search engine: Challenges, insights and approaches (sponsored)
Vinodh Kumar R
Hardware Accelerated Big Data Processing
Reetinder Sidhu
Two Years Wiser: The Nilenso Experiment
Steven Deobald
Processing large data with Apache Spark
Venkata Naga Ravi
Building tiered data stores using Aesop to bridge SQL and NoSQL systems
Regunath Balasubramanian
Deploying Batch and Streaming Architectures on AWS (sponsored)
Russell Nash
Call me maybe: Jepsen and flaky networks
Shalin Mangar
HawkEye: A Real-Time Anomaly Detection System
Satnam Singh, PhD
Search at Petabyte scale
Anup Nair
Instrumenting your kafka & storm pipeline
Bhasker Kode
Keynote: Data Comes in Shapes
Tim Poston
Dead Simple Scalability Patterns
Vedang Manerikar
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