Projects

Developed a machine learning model to predict taxi trip durations in New York City using historical data. Automated the workflow using MLOps to ensure continuous integration, model retraining, and deployment. The project incorporates data preprocessing, feature engineering, model development (using algorithms like XGBoost and Random Forest), and a CI/CD pipeline to deploy the model in a production environment, ensuring scalability and reliability.

The domain-specific area of this project is public safety, focusing on crime analysis and prediction within the city of Vancouver. In recent years, the integration of machine learning techniques has proven instrumental in enhancing law enforcement efforts and proactive decision-making. Vancouver, like many urban centers, faces the ongoing challenge of ensuring the safety and security of its residents. Leveraging machine learning, specifically linear regression models, in the analysis of crime data can provide valuable insights for law enforcement agencies, city planners, and policymakers.

I have performed detailed Exploratory data analysis on Airbnb business in New York City of different hotels. I have explored the data and fetch insights and recommend business decisions based on those insights. The thing while makes this analysis unique is that it is performed based on two perspective, cutomer and owner. Further I have performed predictive analysis as wel.

Currently Rental bikes are introduced in many urban cities for the enhancement of mobility comfort. It is important to make the rental bike available and accessible to the public at the right time as it lessens the waiting time. Eventually, providing the city with a stable supply of rental bikes becomes a major concern. The crucial part is the prediction of bike count required at each hour for the stable supply of rental bikes.

I have performed detailed Exploratory data analysis on Airbnb business in New York City of different hotels. I have explored the data and fetch insights and recommend business decisions based on those insights. The thing while makes this analysis unique is that it is performed based on two perspective, cutomer and owner. Further I have performed predictive analysis as wel.

I have performed detailed Exploratory data analysis on covid data and expored the geographical impact of covid, number of deaths, survival rate and much more.

I have performed detailed Exploratory data analysis on machine learning on loan dataset.I have build a decision tree model to predict whether an applicant is eligible for the loan or not based on the given applicant's information?

I have performed detailed Exploratory data analysis on machine learning on loan dataset.I have build a decision tree model to predict whether an applicant is eligible for the loan or not based on the given applicant's information?

Expolred the Road accidents in UK to answer the following question Combined with population data, how do different areas compare? what trends are there for accidents involving different road users eg motorcycles, peds, cyclists are road safety campaigns effective? likelihood of accidents for different groups vehicles

I have performed sales forecasting on telecommunication companies which provides cellular data services here in pakistan.