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Wingify DevFest 2018

Last year, we had the first version of the Wingify DevFest with the aim of bringing developers under one-roof, where they could contribute by giving talks, workshops or by simply attending the event.

The theme for the second DevFest is Data Science and Engineering. Gather together for a day full of talks and activities related Data Science. With new innovations in Data Science/Machine Learning every day, more people across Industry and Academia need to utilise the power of Data. We have a compelling list of speakers to speak on the theme. Keeping with the spirit of the DevFest, we also have several engaging activites scattered throughout the day. You'll realize that data can be beautiful, where Rasagy Sharma will explain how to display your data in the best way possible. Expect to rack your brains too while solving the Data Science competition on Kaggle.

🎙 Speakers

Paras - Keynote Speaker
Rasagy Sharma

Rasagy Sharma

Designer & Data Artist

This session will introduce you to some inspiring data art projects, give a glimpse of how new chart types are created, and get you to make a unique representation based on your own data.

"What can you do with data? "
Rishi Singhal

Rishi Singhal

Customer Engineer, Google Cloud Platform (GCP)

In this session, get an overview of how Google Cloud is democratising AI by creating AI solutions that easily plug into your existing workflows to give your business access to the power of AI. Rishi would be showcasing multiple demos on different customer use cases and scenarios.

"Making AI work for your Business"
Ashutosh

Ashutosh Singh

Open source contributor, speaker, student

Distributed Deep Learning enables both AI researchers and practitioners to be more productive and the training of models that would be intractable on a single GPU server. Ashutosh will introduce different distributed deep learning paradigms, including model-level parallelism and data-level parallelism, and demonstrate how data parallelism can be used for distributed training.

"Distributed System In Deep Learning Machine"
Nirant

Nirant Kasliwal

Lead Maintainer for Github's Official NLP Resource

One of the pressing challenges in machine learning have always been lack of "right" data in the large volumes. We look at recent NLP Progress which allows us to work with laptop-scale compute, with small data and get amazing performance, rivalled only by Google-scale compute.

"NLP for Indic Languages"
Unnam Rohit

Rohit Takhar & Abhishek Unnam

Research Engineers, Aspiring Minds

Abhishek and Rohit will talk about the automated HR interview tool which Aspiring Minds' team has developed. They will discuss the facial and prosody features for detecting human emotions, and the intricacies of data collection and feature engineering.

"Can you detect human emotions automatically?"