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Hi 👋, I'm Parth Kalkar

Data is my passion and full-stack expertise is my superpower.

parthkalkar

parthkalkar

kalkar_parth

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kalkar_parth parthkalkar 16078720 parthkalkar parth.kalkar erik_phillander erikphil erik_phillander erik_phillander

Languages and Tools:

aws azure bash cplusplus css3 docker gcp git grafana hadoop heroku hive html5 java jenkins kubernetes linux matlab mongodb mssql mysql opencv pandas postgresql python pytorch redis scikit_learn seaborn sqlite tensorflow vagrant

parthkalkar

 parthkalkar

parthkalkar

Parth Kalkar's Projects

ai-art icon ai-art

Implementation of a genetic algorithm to develop some filter for a picture

bird-species-prediction icon bird-species-prediction

In this project, I created a convolutional neural network which predicts the different species of a bird.

bulldozer-price-prediction icon bulldozer-price-prediction

In this notebook, we're going to go through a machine learning project with the goald of predicting the sale price of bulldozers. This involves a time series data which was taken from Kaggle Bluebook Bulldozers competition.

colourizing-b-w-images-with-gans icon colourizing-b-w-images-with-gans

Image Colorization is an interesting gan project to work on. We all have some old photographs and reels which were shot in the times when colored filmography was a talk of the future. Wouldn’t it be amazing if you can colorize those black and white images bringing them back to life? This repository talks about that!

control-theory icon control-theory

Assignments of the course control theory taught at Innopolis University, Spring 2021

covidgameai icon covidgameai

Implementation of AI assignment. It has 2 variants Backtracking searching based on DFS and A* algorithm based on DFS.

data-mining icon data-mining

Tasks solved during the data mining course at Innopolis University

dbms icon dbms

Databases labs - Spring 2021

de_computational_practicum icon de_computational_practicum

Implementation of Numerical methods to solve the differential equation and to compare the errors obtained to check the precision of that method.

digital-signal-processing icon digital-signal-processing

Solutions of assignments solved during the Digital Signal Processing course taken during Spring 2022 at Innopolis University

dog-breed-classification icon dog-breed-classification

In this project, we will see how to use Keras and Tensorflow to build train, and test a Convolutionnal Neural Network capable of identifying the breed of a dog in a custom image. This is a supervised learning problem, specifically a multiclass classification problem.

dsa-bootcamp-java icon dsa-bootcamp-java

This repository consists of the code samples, assignments, and the curriculum for the Community Classroom complete Data Structures & Algorithms Java bootcamp.

face-swapping-application icon face-swapping-application

In this project, I extracted faces of human beings from a given image and then replace the face with other image.

facial-recognition-using-convnet-inception icon facial-recognition-using-convnet-inception

In this notebook, we will build a face recognition system. Many of the ideas presented here are from FaceNet and DeepFace. Face recognition problems commonly fall into two categories: Face Verification - "is this the claimed person?". For example, at some airports, you can pass through customs by letting a system scan your passport and then verifying that you (the person carrying the passport) are the correct person. A mobile phone that unlocks using your face is also using face verification. This is a 1:1 matching problem. Face Recognition - "who is this person?". For example, the video lecture showed a face recognition video (https://www.youtube.com/watch?v=wr4rx0Spihs) of Baidu employees entering the office without needing to otherwise identify themselves. This is a 1:K matching problem. FaceNet learns a neural network that encodes a face image into a vector of 512 numbers. By comparing two such vectors, you can then determine if two pictures are of the same person.

fashion-mnist-gpu-benchmarking-using-ann icon fashion-mnist-gpu-benchmarking-using-ann

This notebook shows code for image classification on the MNIST Fashion dataset using ANN. The main objective here is to compare the performance difference between GPU and CPU runtime. The whole project was ran using Google Colab.

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