TulasiNND's repositories
Industrial-Copper-Modeling-Project
The copper industry faces challenges in predicting selling prices and lead classification. However, by utilizing advanced techniques such as data normalization, outlier detection and handling, and using tree-based models such as the decision tree algorithm, we can provide accurate predictions and optimize pricing decisions and leads classification
Text-Extraction-From-Business-Card-Using-OCR
This code is an OCR application that extracts text from images uploaded by users, using the EasyOCR library. The extracted text is then processed to extract information such as email, phone number, pin code, address, and website URL, and displayed on a Streamlit web app interface.
PhonePe-Pulse-Data-2018-2022-Analysis
I have created a dashboard to visualize Phonepe pulse Github repository data(https://github.com/PhonePe/pulse) using Streamlit and Plotly in Python. The Link for Dashboard: https://tulasinnd-phonepe-pulse-data-2018-2022-phonepe-dashboard-2drsrt.streamlit.app/
Social-Metric-Insight-Projects
This repository features a range of projects related to social media. The first project, 'Twitter Sentiment Analysis', 'Ratings of Guvi Courses' and Instagram Influences, to know more go through readme file and repository
Twitter-scraping-with-snscrape-and-streamlit
This application basically scrapes information from twitter. User will be able to scrape data by entering any key word or hashtag
Predict-Your-Body-Weight-Category-with-DL
Predict-Your-Body-Weight-Category-with-DL is an application that uses Artificial Neural Networks (ANNs) to predict the weight category of an individual based on their age, height, weight, lifestyle, and habits.
Basic-Registration-using-Python
This program will validate the input given by user based on some specific rules. Basic user inputs are Email ID and Password
Population-Prediction-System
Population Prediction System will predict the population of any country in the world for a given year. The Basic inputs of the system are Country name and Year. I have used Polynomial regression Algorithm to build this model
MongoDB-with-Python
Performing CRUD operations on MongoDB using Python
Numpy_Basic_Functions
It consists of Basic to Advanced level Numpy Questions, that covers all the important methods in numpy