Shobhit Sinha's repositories
Fake_news_detector
A fake news dectector application
Named-Entity-Recognition-with-Bidirectional-LSTM-CNNs
Named-Entity-Recognition-with-Bidirectional-LSTM-CNNs
Streamlit_project_coursera
This is a hands down project that I discovered during my project course on Stream-lit. It helps to build ML dasboards/Apps with ease.
AI_Shop_bot
AI shop bot using Pytorch, Deep Learning and Natural Language Processing
Covid19_DataAnalysis
COVID 19 Analysis of Indian data using basic Data Science fundamentals. More segments of Analysis to be added and then post this to be hosted using Streamlit.
Developer_Page
A page for Developers to connect with other developers and create their profiles for recruitment.
DNA-classification-using-ML-NLP
DNA classification using NLP (BoW) and naive Bayes
Smart-India-Hackathon-
Front End: Project Smart Farming
TwitterSentimentDataAnalysis
Hello everyone this repository is all about tweet sentiment analysis. In particularly you can do sentiment analysis on any text.
AI-basketball-analysis
:basketball::robot::basketball: AI web app and API to analyze basketball shots and shooting pose.
automin-2021
The data for the shared task AutoMin 2021 is available in the following Github repository. More task-specific details to use the data would be provided in due time .
Invisibility_Cloak
An invisibility cloak using openCV.
LifeSavers-HackJaipur
Our official work in HackJaipur
ML-For-Beginners
12 weeks, 25 lessons, 50 quizzes, classic Machine Learning for all
Resume-Ranking
Automatic system to rank resume's based on Job Description
Run_application_using_commands
It's a project/repository where you can run any application in your system using commands.
Stumble_upon_classification
StumbleUpon is a user-curated web content discovery engine that recommends relevant, high quality pages and media to its users, based on their interests. While some pages we recommend, such as news articles or seasonal recipes, are only relevant for a short period of time, others maintain a timeless quality and can be recommended to users long after they are discovered. In other words, pages can either be classified as "ephemeral" or "evergreen". The ratings we get from our community give us strong signals that a page may no longer be relevant - but what if we could make this distinction ahead of time? A high quality prediction of "ephemeral" or "evergreen" would greatly improve a recommendation system like ours.
Topic_Classification-
Topic Classification
Windowstore_analysis
Windows Store Dataset of the apps in the Microsoft Windows Store.