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Mrityunjay Kumar

Hello there 👋

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About Mrityunjay

(Current) Software Engineer @Microsoft, California

I am a passionate software engineer working at Microsoft in the PowerPoint team. My primary focus is on writing scalable backend code and contributing to the development of complex distributed systems. I specialize in areas such as resiliency and scalability.

Research :

  • Rolis: A software approach to efficiently replicating multi-core transactions Paper
  • Learning to Fingerprint the Latent Structure in Question Articulation Paper

Learn more at web

Misc

  • 💬 Ask me about ... fault-tolerant storage and database systems
  • How to reach me: ... [email protected]

PPT Live in action

PPT Live in Action

Blogs & misc


Fun Facts:

  1. I am enjoying learning spanish. My favorite word is "recipiente."
  2. When I am away from the keyboard, you can find me either listening to audiobooks or exploring hiking trails.

How to pronounce my name ?

Phonetics : MRIT-yen-jay

Mrityunjay Kumar's Projects

algorithms icon algorithms

Minimal examples of data structures and algorithms in Python

algorithms-2 icon algorithms-2

This repository is for learning and understanding how algorithms work.

awesome-deep-learning-resources icon awesome-deep-learning-resources

Rough list of my favorite deep learning resources, useful for revisiting topics or for reference. I have got through all of the content listed there, carefully. - Guillaume Chevalier

awesome-nlp icon awesome-nlp

:book: A curated list of resources dedicated to Natural Language Processing (NLP)

awesome-scalability icon awesome-scalability

High Scalability, High Availability, High Stability, High Performance, and High Intelligence Back-End Design Patterns

code icon code

Code for the book "Mastering OpenCV with Practical Computer Vision Projects" by Packt Publishing 2012.

data-science-ipython-notebooks icon data-science-ipython-notebooks

Recently updated with 50 new notebooks! Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.

dsa icon dsa

This repo is to maintain all implemented algorithmic code at codechef and hackerrank.

elephas icon elephas

Distributed Deep learning with Keras & Spark

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