Abhinav tembulkar's repositories

coursera-intro-to-machine-learning-duke-university

Repository with the programming assignments from Introduction to Machine Learning Course of Duke University on Coursera.

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ReactiveSoundBars

A crazy new visualization of songs !

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Freqbars

A song visualisation based on p5.js

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Doctorchatapp

A simple doctor - patient online consultancy prototype

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Eventsmanager

A events manager app built on nodejs

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Facemaskdetector

A ML model for combating corona virus by detecting face masks on peoples faces

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galaxyCNNclassifier

CNN classification task just like MNIST on galaxy images

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LEDcounter

0-9999 counter built in Arduino

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LiveFlightStatus

A flight status tracker app, plots live status on map every 20 seconds. Built using AJAX, JS and HTML/CSS. Data fetched from Lufthansa and aviation stack APIs.Maps plotted using amcharts and bootstrap.

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simple_mask_classifier

A simple mask detector based on Javascript

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burgerbuildersapp

A burger Builder app based on ReactJS

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Certifications

This repository has the links of all the certifications I have earned

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Face-Detection-Using-Open-CV

This is a simple demonstration of face detection using the OpenCV library in python (in a few lines of code). Face detection using Haar cascades is a machine learning based approach where a cascade function is trained with a set of input data. OpenCV already contains many pre-trained classifiers for face, eyes, smiles, etc.. We will be using the face classifier.

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Flight-Price-Prediction-With-Deployment

I have built a simple web app that predicts the price of flights based on inputs such as Departure date and time, Source and destination, etc. The model is trained on "Random Forest Regressor" and deployed using "Streamlit" on Heroku. The accuracy of the model was found out to be 95% on the train data and about 80% on the test data.

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Image-Classification-Using-CNN-in-Pytorch

The aim of this project is to predict the label of the object given the image data using Convolutional Neural Networks(CNN) in Pytorch. The dataset used is CIFAR-10 dataset which is a subset of the 80 million tiny images dataset and consists of 60,000 32x32 color images containing one of 10 object classes, with 6000 images per class.

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needles_and_balloons

Needles and balloon is an amazing single-player game

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ReactQuotesApp

A Daily Quotes App with nested comments facility in React

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Tensorflow-Certificates

A repository to share my progress towards Tensorflow certification

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Titanic-Dataset-EDA-Random-Forest-Algorithm

This is a small ML project on the Titanic dataset. The aim of this project is to perform exploratory data analysis on the data with the help of graphs, processing the data and finally applying the Random Forest algorithm to predict the survival based on the features.

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weatherApp

A weather prediction app built using flask, scikit-learn

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