Pinned Repositories
build_tools
Used to build ONLYOFFICE DocumentServer-related products
Cancer-Donation-Portal-Python-Flask-App
Flask App for Cancer Donation Portal using basic Python, SQLite3, HTML, CSS and Javascript
COVID-19-Detection-Flask-App-based-on-Chest-X-rays-and-CT-Scans
COVID-19 Detection Chest X-rays and CT scans: COVID-19 Detection based on Chest X-rays and CT Scans using four Transfer Learning algorithms: VGG16, ResNet50, InceptionV3, Xception. The models were trained for 500 epochs on around 1000 Chest X-rays and around 750 CT Scan images on Google Colab GPU. A Flask App was later developed wherein user can upload Chest X-rays or CT Scans and get the output of possibility of COVID infection.
devopslab
Implementaion-of-Private-Cloud-using-ownCloud
Implementation of Private Cloud using ownCloud. ownCloud is a suite of client–server software for creating and using file hosting services. This repository explains implementing ownCloud on an Ubuntu VM running on top of a Windows host for secure cloud storage
Movie-Recommendation-Chatbot
Movie Recommendation Chatbot provides information about a movie like plot, genre, revenue, budget, imdb rating, imdb links, etc. The model was trained with Kaggle’s movies metadata dataset. To give a recommendation of similar movies, Cosine Similarity and TFID vectorizer were used. Slack API was used to provide a Front End for the chatbot. IBM Watson was used to link the Python code for Natural Language Processing with the front end hosted on Slack API. Libraries like nltk, sklearn, pandas and nlp were used to perform Natural Language Processing and cater to user queries and responses.
Online-Food-Ordering-Web-App
Online Food Ordering System Website using basic PHP, SQL, HTML & CSS. You can use any one of XAMPP, WAMP or LAMP server to run the Web App
Python-Shopping-Cart
Shopping Cart created using Python, tkinter package for GUI, sqlite3 package for database, etc
Stock-Market-Prediction-Web-App-using-Machine-Learning-And-Sentiment-Analysis
Stock Market Prediction Web App based on Machine Learning and Sentiment Analysis of Tweets **(API keys included in code)**. The front end of the Web App is based on Flask and Wordpress. The App forecasts stock prices of the next seven days for any given stock under NASDAQ or NSE as input by the user. Predictions are given for three algorithms: ARIMA, LSTM, Linear Regression. The Web App combines the predicted prices for the next seven days with the sentiment analysis of tweets to give recommendation whether the price is going to rise or fall
Stock-Market-Prediction-Web-App-using-Machine-Learning-And-Sentiment-Analysis-1
Stock Market Prediction Web App based on Machine Learning and Sentiment Analysis of Tweets (API keys included in code). The front end of the Web App is based on Flask and Wordpress. The App forecasts stock prices of the next seven days for any given stock under NASDAQ or NSE as input by the user. Predictions are made using three algorithms: ARIMA, LSTM, Linear Regression. The Web App combines the predicted prices of the next seven days with the sentiment analysis of tweets to give recommendation whether the price is going to rise or fall
rupalijaiswal's Repositories
rupalijaiswal/Cancer-Donation-Portal-Python-Flask-App
Flask App for Cancer Donation Portal using basic Python, SQLite3, HTML, CSS and Javascript
rupalijaiswal/Online-Food-Ordering-Web-App
Online Food Ordering System Website using basic PHP, SQL, HTML & CSS. You can use any one of XAMPP, WAMP or LAMP server to run the Web App
rupalijaiswal/Stock-Market-Prediction-Web-App-using-Machine-Learning-And-Sentiment-Analysis
Stock Market Prediction Web App based on Machine Learning and Sentiment Analysis of Tweets **(API keys included in code)**. The front end of the Web App is based on Flask and Wordpress. The App forecasts stock prices of the next seven days for any given stock under NASDAQ or NSE as input by the user. Predictions are given for three algorithms: ARIMA, LSTM, Linear Regression. The Web App combines the predicted prices for the next seven days with the sentiment analysis of tweets to give recommendation whether the price is going to rise or fall
rupalijaiswal/COVID-19-Detection-Flask-App-based-on-Chest-X-rays-and-CT-Scans
COVID-19 Detection Chest X-rays and CT scans: COVID-19 Detection based on Chest X-rays and CT Scans using four Transfer Learning algorithms: VGG16, ResNet50, InceptionV3, Xception. The models were trained for 500 epochs on around 1000 Chest X-rays and around 750 CT Scan images on Google Colab GPU. A Flask App was later developed wherein user can upload Chest X-rays or CT Scans and get the output of possibility of COVID infection.
rupalijaiswal/devopslab
rupalijaiswal/Implementaion-of-Private-Cloud-using-ownCloud
Implementation of Private Cloud using ownCloud. ownCloud is a suite of client–server software for creating and using file hosting services. This repository explains implementing ownCloud on an Ubuntu VM running on top of a Windows host for secure cloud storage
rupalijaiswal/Movie-Recommendation-Chatbot
Movie Recommendation Chatbot provides information about a movie like plot, genre, revenue, budget, imdb rating, imdb links, etc. The model was trained with Kaggle’s movies metadata dataset. To give a recommendation of similar movies, Cosine Similarity and TFID vectorizer were used. Slack API was used to provide a Front End for the chatbot. IBM Watson was used to link the Python code for Natural Language Processing with the front end hosted on Slack API. Libraries like nltk, sklearn, pandas and nlp were used to perform Natural Language Processing and cater to user queries and responses.
rupalijaiswal/Python-Shopping-Cart
Shopping Cart created using Python, tkinter package for GUI, sqlite3 package for database, etc
rupalijaiswal/Stock-Market-Prediction-Web-App-using-Machine-Learning-And-Sentiment-Analysis-1
Stock Market Prediction Web App based on Machine Learning and Sentiment Analysis of Tweets (API keys included in code). The front end of the Web App is based on Flask and Wordpress. The App forecasts stock prices of the next seven days for any given stock under NASDAQ or NSE as input by the user. Predictions are made using three algorithms: ARIMA, LSTM, Linear Regression. The Web App combines the predicted prices of the next seven days with the sentiment analysis of tweets to give recommendation whether the price is going to rise or fall