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Name: Dushyant Rai Tara

Type: User

Company: MiQ Digital

Bio: A senior Data Scientist, building products using petabytes of structured and unstructured data to improve customer targeting methodologies in Adtech domain.

Location: Bangalore, India

Dushyant Rai Tara's Projects

applied-ml icon applied-ml

Curated papers, articles & videos on data science & machine learning applied in production, with results.

asr_sd icon asr_sd

Automatic Speech Recognition and speaker diarization

autograd icon autograd

Efficiently computes derivatives of numpy code.

awesome-datascience icon awesome-datascience

:memo: An awesome Data Science repository to learn and apply for real world problems.

bsuite icon bsuite

bsuite is a collection of carefully-designed experiments that investigate core capabilities of a reinforcement learning (RL) agent

chainerrl icon chainerrl

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

deepmind-research icon deepmind-research

This repository contains implementations and illustrative code to accompany DeepMind publications

densepose icon densepose

A real-time approach for mapping all human pixels of 2D RGB images to a 3D surface-based model of the body

detect-parkinsons-disease icon detect-parkinsons-disease

Parkinson's disease is a neurodegenerative, progressive disorder of the central nervous system that affects movement and causes tremors and stiffness. This affects dopamine-producing neurons in the brain and every year, it affects more than 1 million individuals in India.

detectron icon detectron

FAIR's research platform for object detection research, implementing popular algorithms like Mask R-CNN and RetinaNet.

dhs-19 icon dhs-19

Contains the material I presented in Data Hack Summit 2019

dhs2019 icon dhs2019

Video encoding & classification using tensorflow 2.0

edgeml icon edgeml

This repository provides code for machine learning algorithms for edge devices developed at Microsoft Research India.

gru4rec icon gru4rec

GRU4Rec is the original Theano implementation of the algorithm in "Session-based Recommendations with Recurrent Neural Networks" paper, published at ICLR 2016 and its follow-up "Recurrent Neural Networks with Top-k Gains for Session-based Recommendations". The code is optimized for execution on the GPU.

hungabunga icon hungabunga

HungaBunga: Brute-Force all sklearn models with all parameters using .fit .predict!

hyperopt icon hyperopt

Distributed Asynchronous Hyperparameter Optimization in Python

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