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Ujwal2910


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Greetings to all šŸ‘‹, I'm Ujwal Tewari.


I have been working in Reinforcement learning, control optimization-based techniques and multi-agent systems. In addition to this, I work in the real world deployment of AI-based models for automated control decision processes using both RL and evolutionary strategies in cases where human intervention would otherwise be difficult.

I have also been working as an AI Ambassador at Intel Corporation, a classroom mentor for the Deep Reinforcement Learning nanodegree at Udacity and a tech blogger at Medium in Analytics Vidhya.

Have worked in ML and Research as Applied Scientists for more than 4 years with good track record of ML papers in reputed conferences. Expertise in model development to deployment lifecycle My Interests are:

Machine Learning, Reinforcement Learning, Knowledge Graphs, Natural Language Processing and Computer Vision

Here is a bit about my interests and how to get in touch:

  • šŸ’¬ I am learning about Model deployment and integration cycles.
  • šŸŒ± Iā€™m currently working on Multi-agent Reinforcement Learning, Dialog systems and Optimization based problems.
  • šŸ’¬ Ask me about NLP, Deep Neural Networks, GAN, Probabilistic Models and let's Collaborate to knock new ideas to code.
  • šŸ“« How to reach me: [email protected]

Ujwal Tewari Github Stats


Ujwal Tewari's Projects

agents icon agents

TF-Agents is a library for Reinforcement Learning in TensorFlow

aima-python icon aima-python

Python implementation of algorithms from Russell And Norvig's "Artificial Intelligence - A Modern Approach"

airgym icon airgym

AirSim with openAI gym and keras-rl integration for autonomous copter RL

airsim-drone-racing-vae-imitation icon airsim-drone-racing-vae-imitation

Code associated with our paper "Learning Controls Using Cross-Modal Representations: Bridging Simulation and Reality for Drone Racing": https://arxiv.org/abs/1909.06993

android_me icon android_me

App that lets you style your own Android! This uses Fragments to create a flexible and responsive UI.

api-samples icon api-samples

Code samples for YouTube APIs, including the YouTube Data API, YouTube Analytics API, and YouTube Live Streaming API. The repo contains language-specific directories that contain the samples.

apps-android-commons icon apps-android-commons

Upload pictures from Android to Wikimedia Commons. Looking for volunteers! Come say hi at https://groups.google.com/d/forum/commons-app-android and install at https://play.google.com/store/apps/details?id=fr.free.nrw.commons

attention-basics icon attention-basics

In this notebook, we look at how attention is implemented. We will focus on implementing attention in isolation from a larger model. That's because when implementing attention in a real-world model, a lot of the focus goes into piping the data and juggling the various vectors rather than the concepts of attention themselves.

baselines icon baselines

OpenAI Baselines: high-quality implementations of reinforcement learning algorithms

chainerrl icon chainerrl

ChainerRL is a deep reinforcement learning library built on top of Chainer.

chat-bot icon chat-bot

Creating a Chatbot using Python libraries.

chatterbot icon chatterbot

ChatterBot is a machine learning, conversational dialog engine for creating chat bots

colorization-1 icon colorization-1

Automatic colorization using deep neural networks. "Colorful Image Colorization." In ECCV, 2016.

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