To work on the project of YouTube data harvesting and warehousing, the first step is to extract information from a specific YouTube channel using the YouTube channel ID. Subsequently, this data can be analyzed in response to a set of user-provided questions. || Python, Pandas,MongoDb,Build,Mysql,Streamlit,Plotly ||

Here, I worked with the product data Golbally and used useContext to access all of its components, demonstrating my understanding of how React useContext manages State within a React application.

A ML model to predict whether the clients will subscribe to insurance or not.

In this project, which involves the MongoDB Atlas sample Airbnb dataset, our objective is to conduct Exploratory Data Analysis (EDA) by performing data cleaning. Ultimately, we aim to represent the insightful findings in a visually compelling format through storytelling using Power BI.

Codekatas typically involve writing code to solve a specific problem, and the goal is to write efficient, working code that meets the requirements of the problem statement. In this repository you can find the python programs which is related to arrays.

Guvi Day 8 task for call backs

This web application was created according to the software requirements given in the Problem Statement on GUVI - Intern for web developer role.

Traveling Landing page

food landing page

Here, I Understand how React Router works to manage navigation within a React application

Collection of DSA questions from competitive coding websites and simple and basic data structures to ace the coding interview!

Customer Insights & Recommendation System: Harnessing Decision Tree, Logistic Regression, and Random Forest models for behavior analysis. Utilizing EasyOCR and Python Imaging Library for image information extraction. Employing NLTK for sentiment analysis on textual data

To work on the project of YouTube data harvesting and warehousing, the first step is to extract information from a specific YouTube channel using the YouTube channel ID. Subsequently, this data can be analyzed in response to a set of user-provided questions. Python, Pandas,MongoDb,Build,Postgresql,Streamlit.

PhonePe Pulse: Data Visualization and Exploration—a User-Friendly Tool using MySQL, Streamlit, and Plotly.

Collecting YouTube data using google API and storing the data in MongoDB(NoSQL) and Migrating the stored data from MongoDB into SQL and creating a user friendly Streamlit web app for the visualization and to get a better understanding of the YouTube channels and video details. All with the help of Python and Python libraries.

MERN Stack Project

This folder contains the internship assessment for Akaike Technologies, comprising assignments related to Data Science and NLP.

This project aims to predict customer conversion for an insurance company. Using historical data, we will develop a machine learning model that can identify which customers are most likely to purchase a policy. By understanding the patterns and behaviors of previous customers, the model can make predictions and provide valuable insight to company.