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Automatic-Essay-Scoring
Created a web app that can automatically score essays. The grading model was trained using HP Essays Dataset from Kaggle. Used Long Short Term Memory (LSTM) network and machine learning algorithms to train model. WebApp was created using Flask framework.Sign-Language-Recognition
A project to recognize sign language using OpenCV and Convolutional neural network. Created our own dataset of 19200 images to train the neural networkQuakeReport
Android app to display 10 latest earthquakes in the world using USGS APITicTacToe
Flower-Species-Classifier
Trained an image classifier to identify a total of 102 flower species. Data Augmentation was used to bring variety in the dataset. I also made a command-line interface for training and testing our model with various parameters using the ArgumentParser library in Python. Transfer Learning with VGG16 and Densenet121 was used to train our neural network using PyTorch.web_course
Webtech course coding assignment -2Motion-Detection
Motion Detection in python using OpenCVMovieLens-MapReduce-Analysis
MapReduce approach to analyse MovieLens data along with Python code to visualize our dataFinger-Count-Recognition
Python script to detect number of fingers in webcam feed using OpenCV. Used the concept of contours and convexity defects to achieve finger count.IEEE-CIS-Fraud-Detection
Detect Fraud from customer transactions. This project is part of the IEEE CIS Fraud Detection competition available on Kaggle.Face_Detection
A python program to detect faces in a webcam feedTask-Manager-API
ToDo-App
sankalpjain99
My personal repositoryTitanic-Survivor-Prediction
Data analysis to predict Titanic survivorsJS-MiniProjects
Some easy mini projets made using JavaScriptIris-Dataset-Analysis
Predict the species of a flower on the basis of their petal and sepal height/widthLeetCode-May-Challenge
Solutions for May Leetcoding challenge in C++Identifying-Customer-Segments
Project on real-time proprietary data for Bertelsmann Arvato Analytics to identify customer segments that form the core customer base of the company using unsupervised learning techniques. Data cleaning was an integral part of the project since the data used here was real-world. Techniques like Principal Component Analysis were also used for Dimensionality ReductionMovie-recommendation-system
Different takes at creating a content based movie recommendation system using MovieLens dataset. One approach focuses on finding the correlation between different attributes to recommend movie. Another approach make use of the bag of word model along with machine learning algorithms.Twitter-Sentiment-Analysis
Python code to perform sentiment analysis of twitter data. Used TermFrequencyInverseDocumentFrequency(TFIDF) model along with Machine Learning algorithms to make predictionsLoan-Approval-Prediction
Classify wheather a loan will be approved or notRocksDB-Reader
A plug n play service to quickly view contents from your RocksDB. All you need is the column family name and the key to fetch the value!Love Open Source and this site? Check out how you can help us