Projects
Below are the sample Data Analytics projects on SQL, Python, Power BI & ML.
Genomic Selection For Resilient Crop Breeding In South Punjab
This project focuses on using genomic selection techniques to predict key traits in wheat, such as yield and plant height, using genotype and phenotype data. We implemented various machine learning models including Random Forest, XGBoost to select the most important SNPs (genetic markers) for accurate trait prediction.
Tools used include Python, Pandas, Scikit-learn, Matplotlib, Pyplot, Seaborn, Beagle, Plink. The model pipeline includes data cleaning, feature selection using GWAS and ML, imputation using Beagle, and performance comparison across models.
Personalized Job Recommendation System Leveraging TF-IDF and Cosine Similarity
A content-based recommendation system. The project features an interactive Streamlit interface, visualizations, and a machine learning engine for personalized job recommendations.
This system matches job seekers to suitable roles based on job descriptions, helping users find relevant positions efficiently. The model utilizes text processing techniques like TF-IDF and uses cosine similarity to recommend similar roles.
Resume Category Prediction with Machine Learning
I developed a web app using Streamlit that predicts resume categories based on their content, aimed at helping recruiters automate resume classification, and Plotly.
I developed an interactive UI for instant resume category predictions using NLP techniques like tokenization and lemmatization. I trained a KNN classifier with TF-IDF vectorization and deployed the model in a Streamlit app. This project showcases my skills in NLP, machine learning, and interactive web applications using Python and relevant libraries.
Credit Card Revenue Prediction using Python and Machine Learning!
I analyzed customer data from a PostgreSQL database to uncover insights and predict revenue based on demographics.
Key highlights include: Visualizing revenue by expense type with Plotly Treemap Identifying top states by total revenue, average annual fees by age group. Predicting revenue using a Random Forest Regressor model.
Market Sales Analysis Dashboard In Excel
Tool used: Excel
Key Visualizations: Sales trends by category, month, channel, and gender, providing insights into customer demographics, sales patterns, and regional performance for data-driven decision-making. This analysis highlighted key trends, optimizing marketing and inventory strategies.
Super Market Sales Analysis
Tools Used: Power BI
Project Overview: Analyzed and visualized supermarket sales data with key features including cards displaying the sum of quantity, sales, and shipped orders. Implemented year slicers for dynamic filtering. Key visualizations included sales distribution across different markets and detailed profit analysis by product categories and sub-categories.
Credit Card Analysis
Tools Used: PostgreSQL, Power BI
Project Overview: Dashboard for analyzing credit card sales data with key features such as data integration from PostgreSQL to Power BI, and revenue calculations consistent with Python results. Visualizations include revenue trends over time, key sales metrics like total sales, average transaction value, and customer segmentation, along with dynamic filters for deeper insights and analysis.
Contact Me
Below are the details to reach out to me!
Address
Punjab, Pakistan