Krishna Aswani (kaswani29)

kaswani29

Geek Repo

Company:Amazon

Location:San Jose, CA

Home Page:linkedin.com/in/kaswani29

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Krishna Aswani's repositories

Self_Driving_Car_Model

This repo uses model architecture of Nvidia end to end deep learning to drive car in Udacity simulator

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Mouse_Click_Skip_lesson_Survey

Simple script that clicks a button on page after some duration to skip pages. Helps you complete lessons where you need to give certificates at the end.

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Advanced_Lane_Detection

In this project we try to identify lanes using advanced computer vision techniques

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Bloomberg_Mba_College_Rank_Crawler_Webscraper

This crawler is written in python. It is used to grab MBA college attributes which are spread over 100's of pages (educational purpose only). It uses packages beautifulsoup, urllib and csv. It can crawl data from various pages

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challenge-interviewcake

various solutions to the interviewcake problems

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configs

config file for vim etc.

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deep-latent-sequence-model

Pytorch implementation of "A Probabilistic Formulation of Unsupervised Text Style Transfer" by He. et. al. at ICLR 2020

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DenverCrimeVsPopulation

In this project we try to find out correlation between denver crime type vs various attributes of population.To take it even further the role of weather on crime is also explored. The code is written in python while using sqlite package for executing sql queries.

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detectron2

Detectron2 is FAIR's next-generation platform for object detection and segmentation.

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EverybodyDanceNow

Motion Retargeting Video Subjects

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ffhq-dataset

Flickr-Faces-HQ Dataset (FFHQ)

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gan_course

GAN Specialization by deeplearning.ai

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ImageNet-Sketch

ImageNet-Sketch data set for evaluating model's ability in learning (out-of-domain) semantics at ImageNet scale

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RestaurantRevenuePrediction

Predict annual restaurant sales based on objective measurements

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SimSwap

The official project of SimSwap (ACM MM 2020)

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tf_code

Tensorflow practice script

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touchstream

lightweight mouse/keyboard network sharing utility

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utility_scripts

Daily drivers

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Vehicle-Detection

In this project we try to identify lanes using advanced computer vision techniques

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