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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

live-resume icon live-resume

:anchor: Stand out of the crowd by showing a professional website/resume. :necktie: :briefcase: Build fast :rocket: and easy the best Personal Web Application resume!

lstm_gots7e6_script_generator icon lstm_gots7e6_script_generator

Using Lstm-rnn tp generate Game of thrones S7E6 script. May not be precise and will be based on the data recieved in episode 6.Machine version of Episode6

magent icon magent

A Platform for Many-agent Reinforcement Learning

make_a_neural_network icon make_a_neural_network

This is the code for the "Make a Neural Network" - Intro to Deep Learning #2 by Siraj Raval on Youtube

mlnd icon mlnd

A Wiki containing helpful information for new and existing students of the Machine Learning Nanodegree at Udacity. Written by students of the Nanodegree.

open_spiel icon open_spiel

OpenSpiel is a collection of environments and algorithms for research in general reinforcement learning and search/planning in games.

openlabeling icon openlabeling

Open Source labeling tool to generate the training data in the format YOLO requires.

playground icon playground

PlayGround: AI Research into Multi-Agent Learning.

reward-learning-rl icon reward-learning-rl

[RSS 2019] End-to-End Robotic Reinforcement Learning without Reward Engineering

rl-examples icon rl-examples

Examples of published reinforcement learning algorithms in recent literature implemented in TensorFlow

rl-reliability-metrics icon rl-reliability-metrics

The RL Reliability Metrics library provides a set of metrics for measuring the reliability of reinforcement learning (RL) algorithms, as well as statistical tools for comparing algorithms and for computing confidence intervals on these metrics.

rlenv.directory icon rlenv.directory

Explore and find reinforcement learning environments in a list of 100+ open source environments.

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