Projects

Power Bi Projects

The main objective of this project is to understand the sales performance of the company.
This report unveils the client segments of the company and identifies the segment that generates the highest revenue.
This report aids the organization in gauging how frequently a client has placed orders for high-priority products.
This report helps the organization comprehend the demand for products across different markets.
This report helps the organization identify products that are resulting in losses.

Our college's Capstone project revolved around this endeavor.
The purpose of this project was to gain insights into the preferred visualization tools among users.
The primary data source for this report consisted of personal interviews, which I conducted along with two classmates. These interviews aimed to enhance our understanding of visualization tool preferences.
Based on the survey findings, the majority of individuals favor Excel for data visualization.
Additionally, the report indicates that as users' experience level increases, their preference tends to shift towards Tableau or Power BI.

The primary objective of this project is to comprehend the internet retail operations of a company.
This project was undertaken as part of the TATA Forage course.
The information presented in this report helped the organization gain insights into its monthly sales during the year 2011.
Additionally, this report facilitates the analysis of the top ten customers of the company.
By examining the data provided in this report, the company can identify the countries generating significant revenue.
This study also aids the organization in pinpointing nations with growing demand, providing valuable guidance for potential expansion opportunities.

This project involves a Python-based machine learning endeavor.
The initial phase involved data cleansing, followed by exploratory data analysis.
The best-performing model in terms of accuracy was subsequently identified.
The chosen machine learning algorithm for this project was the random forest, achieving an impressive 97% accuracy.
To enable the creation of a web application, the model was saved as a pickle file.
The web application was designed to allow users to input their own variables into the model, enabling them to forecast the penguin species.

This project is a Python-based machine learning initiative.
The initial steps involved data cleaning followed by exploratory data analysis.
The model with the highest accuracy was subsequently identified.
For this project, the chosen machine learning algorithm was Adaboosting, achieving an accuracy of 96%.
To facilitate the creation of a web application, the model was saved as a pickle file.
The web application was designed to allow users to input their own variables into the model, enabling them to predict whether they have diabetes or not.

This project involves a Python-based machine learning endeavor.
The initial step involved cleaning the data, followed by conducting exploratory data analysis.
The model with the highest accuracy was subsequently identified.
For this project, the chosen machine learning algorithm was the random forest, achieving an impressive accuracy of 97.8%.
To facilitate the creation of a web application, the model was saved as a pickle file.
The web application was designed to enable users to input their own variables into the model, allowing them to forecast whether they will develop heart disease in the next 10 years.

This project served as the end-of-term assessment for the MySQL course.
In this project, our task was to design a database from scratch and subsequently load various datasets into it.
Upon loading the data, the next step involved creating specific calculated columns that were essential for the project's objectives.
Following the creation of these calculated columns, the final step was to establish views within the database, which would allow us to address specific questions or queries related to the project's requirements.