Pinned Repositories
certi-ml
Chatbot for certification platform using open source machine learning framework
100_Days_of_Coding_Challenge
100_Days_of_Coding_Challenge_Part-2
Ardiuno
Basic Ardiuno Programs
Capgemini-Tech-Challenge-2021
Insight-for-Cab-Investment-firm
After studying the historical data of the major cab services in major US cities, providing actionable advice to XYZ private firm for cab investment so that it can make an informed decision.
Iris-ML
A Flask-based Machine Learning Web App deployed on Heroku that uses API to classify the type of Iris flower based on its sepal length, sepal width, petal length, and petal width.
Person_Detection
Person Detection using Tensorflow pre-trained model.
resume_extraction_team_zeros
This capstone project was created as part of the Data Glacier internship, in which we (Team ZeRoS) produced a Resume Extractor using Named Entity Recognition with Spacy in Natural Language Processing. The dataset was in JSON format, which we transformed to a text file after exhaustively analyzing and cleaning it to train our model. This project is built with Flask, and it allows a user to upload a resume (in pdf or docx format) and receive entities categorized by our model, such as the person's name, college name, academic information, relevant experiences, skill set, and so on.
snapcartt
Python, Flask, Postgres-database, jQuery, and Bootstrap were used to create an E-Commerce Web App. The app provides a large number of jerseys to choose from, each with an image, a description, a price, and a simple form to add the item to your cart. The information about the shirt is kept in a Postgres database and shown with Bootstrap's card class. The application includes a set of filters that use Postgres queries to show just shirts that meet specific criteria, such as shirts by area, clubs vs. national teams, shirts on sale, IPL, and so on. If a user is not logged in and tries to add something to their shopping cart, a warning message (implemented with jQuery) will appear, requesting that they log in. The user can add shirts to their purchasing cart once they have registered and logged in. At the top right of the screen is a link to the shopping cart, which displays the number of products in the cart as well as the sub-total in rupees. The shopping cart link launches a Bootstrap modal window with further information about the shopping cart. You can click the Buy button to go to the full version of the shopping cart and make changes, such as adding one more item or removing a shirt. Because the payment method has not yet been deployed, the cart gets reset once you check out. Simply click the Purchased button to view your buy history, which will show you all of the shirts you've ever purchased. You'll also see a Buy Again option, which will take you to the product page if you wish to purchase it again. The project is complete and ready for production use, having been developed from the ground up and deployed on the Heroku cloud platform.
swapnilvishwakarma's Repositories
swapnilvishwakarma/Iris-ML
A Flask-based Machine Learning Web App deployed on Heroku that uses API to classify the type of Iris flower based on its sepal length, sepal width, petal length, and petal width.
swapnilvishwakarma/Person_Detection
Person Detection using Tensorflow pre-trained model.
swapnilvishwakarma/100_Days_of_Coding_Challenge
swapnilvishwakarma/100_Days_of_Coding_Challenge_Part-2
swapnilvishwakarma/Capgemini-Tech-Challenge-2021
swapnilvishwakarma/Insight-for-Cab-Investment-firm
After studying the historical data of the major cab services in major US cities, providing actionable advice to XYZ private firm for cab investment so that it can make an informed decision.
swapnilvishwakarma/resume_extraction_team_zeros
This capstone project was created as part of the Data Glacier internship, in which we (Team ZeRoS) produced a Resume Extractor using Named Entity Recognition with Spacy in Natural Language Processing. The dataset was in JSON format, which we transformed to a text file after exhaustively analyzing and cleaning it to train our model. This project is built with Flask, and it allows a user to upload a resume (in pdf or docx format) and receive entities categorized by our model, such as the person's name, college name, academic information, relevant experiences, skill set, and so on.
swapnilvishwakarma/snapcartt
Python, Flask, Postgres-database, jQuery, and Bootstrap were used to create an E-Commerce Web App. The app provides a large number of jerseys to choose from, each with an image, a description, a price, and a simple form to add the item to your cart. The information about the shirt is kept in a Postgres database and shown with Bootstrap's card class. The application includes a set of filters that use Postgres queries to show just shirts that meet specific criteria, such as shirts by area, clubs vs. national teams, shirts on sale, IPL, and so on. If a user is not logged in and tries to add something to their shopping cart, a warning message (implemented with jQuery) will appear, requesting that they log in. The user can add shirts to their purchasing cart once they have registered and logged in. At the top right of the screen is a link to the shopping cart, which displays the number of products in the cart as well as the sub-total in rupees. The shopping cart link launches a Bootstrap modal window with further information about the shopping cart. You can click the Buy button to go to the full version of the shopping cart and make changes, such as adding one more item or removing a shirt. Because the payment method has not yet been deployed, the cart gets reset once you check out. Simply click the Purchased button to view your buy history, which will show you all of the shirts you've ever purchased. You'll also see a Buy Again option, which will take you to the product page if you wish to purchase it again. The project is complete and ready for production use, having been developed from the ground up and deployed on the Heroku cloud platform.
swapnilvishwakarma/COVID-19_Diagnosis
swapnilvishwakarma/Data-Structures-And-Algorithms-Hacktoberfest18
List of data structures and algorithms. Feel free to contribute under Hacktoberfest '18!
swapnilvishwakarma/DataVisualisation
new
swapnilvishwakarma/EDA_Amazon_Top_50_Bestselling_Books
Exploratory Data Analysis on Amazon's Top 50 Bestselling Books from 2009 - 2019.
swapnilvishwakarma/Emotion-Detector
A streamlit app based on a text dataset that predicts anger, disgust, fear, joy, neutral, sadness, shame, and surprise from the input text.
swapnilvishwakarma/Fake-News-Classifier
swapnilvishwakarma/File-Ingestion-and-Schema-Validation
swapnilvishwakarma/flexbox
Learning Flexbox & Grid
swapnilvishwakarma/GeoSpatial-Data-Analysis
swapnilvishwakarma/Gourmet-Burgers
Learning Bootstrap
swapnilvishwakarma/Grid
swapnilvishwakarma/Javascript
Learning Javascript
swapnilvishwakarma/ML-X-0
swapnilvishwakarma/Predict-Car-Price
A Flask-based Machine Learning Web App that uses Heroku to forecast the price of an automobile based on numerous characteristics.
swapnilvishwakarma/sign-lang
swapnilvishwakarma/Song-Finder
swapnilvishwakarma/SwapnilPortfolio
My Personal Portfolio
swapnilvishwakarma/swapnilvishwakarma
swapnilvishwakarma/Tech-Store
Learning Web Dev
swapnilvishwakarma/Twitter_Sentiment_Dashboard
Using Streamlit and Python, I created interactive data dashboards and used Pandas to manipulate data in data science workflows. I also used Plotly to create interactive graphs.
swapnilvishwakarma/US-Airlines-Sentiment-Analysis
swapnilvishwakarma/VC