Projects
Because of my skills, I am confident that I will be an excellent analyst. You can view those projects that I have carried out.
SQL Projects
Bank Nifty Stock Analysis
Created Stock Analysis of 11 datasets of bank stocks which is under the nifty bank index, comparing and analyzing them by their volume, and open and close price, and created some solutions to understand the historical and present condition of those stocks. Survey all the stocks to calculate their past and present prices
Fifa World Cup 2022 Analysis
Using SQL, analyze every match of FIFA World Cup 2022 and compare every player's goal and every point to see what happens in each match.
Excel Projects
NFT Sales Analysis
Analysis of 250 collections and their all-time statistics such as sales, transactions, ownership and buyers A sample EDA performed by me and creating a chart and Dashboard in Microsoft Excel.
IMDB TV Shows analysis
Analysis IMDB shows which are published in OTT platforms like NetXix, Amazon Prime, Hotstar etc, and creating charts and Dashboard in Microsoft Excel.
PowerBI Projects
Hospitality Domain Revenue Analytics
Analysis of property location, room information, revenue, etc, then comparing and analyzing the data and creating an insight dashboard.
Amazon Sales Insights using Power BI
I will be showcasing my latest Power BI project which focuses on Amazon sales analysis in the E-commerce domain. The project utilizes Power BI's interactive visualizations to provide a comprehensive analysis of Amazon's sales data, including product-wise and category-wise sales trends, top-performing products, and revenue distribution by every Category.
Machine Learning Projects
Movie Recommender System
•Build an unsupervised machine learning project for a content-based recommender system, and deploy and customize it using Streamlit.
•Process: Preprocessed data, selected the best model, evaluated performance, and added features for an enhanced user experience.
Car Price Prediction
•Conducted data analysis and feature engineering to prepare the car selling price dataset for modeling, then built a linear regression model to predict car selling price.
•Created a pipeline that includes feature selection, label encoding, and model fitting, and saved it using pickle. •Deployed the pipeline on a Flask web application to create a user-friendly interface for predicting car selling prices
SMS spam Classifier
• Conducted EDA(Exploratory data analysis) to spam SMS dataset, then built a classifier model to predict whether the SMS is Spam or not.
• I created a classifier model using CountVectorizer for feature extraction and tested multiple classifiers on preprocessed data.
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