Pinned Repositories
Acharya-Aditya-Pratap
Config files for my GitHub profile.
Blue-Bus-Application
An application using MEAN stack for online bus booking system using Firebase authentication, stateful behavior and offering features such as choosing bus according to rates, route, charges and ratings, dynamically displaying current location on map view during journey, printing ticket pdf. It has several stateful views - the website has different features and functionalities and looks different for the admin, for the bus drivers, for the employees and for the users.
Chat
A multi-user chat app
data
hostel
LeetCode
Important leetcode questions and approaches
Paint
My version of the classic paint app with my take on some of the classic features and some new modifications.
Stock-Trend-Prediction-using-Twitter-Sentiment-Analysis
This project was part of my 3rd year PD lab project. In this project, raw tweets data were mined. Raw tweets are in random unorganised format. The mined raw tweets were formatted such that the date of posting could be extracted from them along with the accurate time of posting, the tweet id and the twitter handle of the user who posted it. Two text files were prepared from words with known sentiments - positive.txt and negative.txt, containing words,their types and respective sentiment scores. This was followed by tokenization using whitespace as delimiter, removal of standard stopwords, filtering out invalid financial terms and stemming the tokens to their base form. Using the above obtained tokens, their cooresponding counts and TF-IDF scores were obtained as the feature vector. This concludes the sentiment analysis part of the project. A neural network prediction model was trained with 500 hidden neurons using the above extracted features against the DJIA stock trend of the concerned company. The designed model was tested with another set of DJIA stock prices with a minimum of 10 guaranteed epochs and a maximum of 500 epochs.
Acharya-Aditya-Pratap's Repositories
Acharya-Aditya-Pratap/Acharya-Aditya-Pratap
Config files for my GitHub profile.
Acharya-Aditya-Pratap/Blue-Bus-Application
An application using MEAN stack for online bus booking system using Firebase authentication, stateful behavior and offering features such as choosing bus according to rates, route, charges and ratings, dynamically displaying current location on map view during journey, printing ticket pdf. It has several stateful views - the website has different features and functionalities and looks different for the admin, for the bus drivers, for the employees and for the users.
Acharya-Aditya-Pratap/Chat
A multi-user chat app
Acharya-Aditya-Pratap/data
Acharya-Aditya-Pratap/hostel
Acharya-Aditya-Pratap/LeetCode
Important leetcode questions and approaches
Acharya-Aditya-Pratap/Paint
My version of the classic paint app with my take on some of the classic features and some new modifications.
Acharya-Aditya-Pratap/Stock-Trend-Prediction-using-Twitter-Sentiment-Analysis
This project was part of my 3rd year PD lab project. In this project, raw tweets data were mined. Raw tweets are in random unorganised format. The mined raw tweets were formatted such that the date of posting could be extracted from them along with the accurate time of posting, the tweet id and the twitter handle of the user who posted it. Two text files were prepared from words with known sentiments - positive.txt and negative.txt, containing words,their types and respective sentiment scores. This was followed by tokenization using whitespace as delimiter, removal of standard stopwords, filtering out invalid financial terms and stemming the tokens to their base form. Using the above obtained tokens, their cooresponding counts and TF-IDF scores were obtained as the feature vector. This concludes the sentiment analysis part of the project. A neural network prediction model was trained with 500 hidden neurons using the above extracted features against the DJIA stock trend of the concerned company. The designed model was tested with another set of DJIA stock prices with a minimum of 10 guaranteed epochs and a maximum of 500 epochs.