Expertise
- Data Query & Wrangling
- Data Analysis
- Data Visualization
- Machine Learning
- API Development
I'm a
I used Chicago Divvy public data to evaluate users' membership conversion rate, determine trends and theorize what was causing them. I was then able to recommend ways improve future success based on those findings.
I conducted comprehensive web scraping operations. Additionally, I engaged in succinct exploratory and explanatory analyses, extracting valuable insights and proposing strategies to enhance tweet retweeting metrics.
I used Bitcoin's daily closing market price dataset from Jan 2012 to March 2021 Kaggle for this project. This work's main objective includes explaining how to analyze a time series and forecast its values using ARIMA and GARCH models.
Gathered tweets on the Nigeria General 2023 Election, cleaned and refined the dataset, and crafted an insightful dashboard for in-depth analysis and visualization of election dynamics and public sentiments.
In this project, I analyzed the prosper load data, studied the trends and concluded that monthly income, loan amount and borrower's rate significantly affect the prosper rating and a good predictors of delinquency.
In this project, I conducted Exploratory Data Analysis (EDA) and built a linear regression model to gain insights into the superstore data and make informed decisions about marketing and sales strategies.
Performed a comprehensive descriptive analysis of movie datasets, identifying trends, extracting actionable insights, and providing strategic recommendations for optimal practices in new movie releases to enhance mass acceptability
The main aim of the work is to emphasize the various steps needed to build such a model. I also explained the possible methods to deploy the model, including wrapping the model in a function to implement a program.
Employed DAX for advanced measurement calculations. Emphasized analyzing major causes of casualties and identifying vehicles most susceptible to these incidents for informed decision-making and preventive measures.
The main aim of the work is to emphasize the various steps needed to build such a model. I also explained the possible methods to deploy the model, including wrapping the model in a function to implement a program.
In business analysis, the Apriori algorithm can be used to analyze transactional data and identify items frequently purchased together, such as pairs of items. This information can inform marketing strategies, such as cross-selling.
Developed a multi-class classification model to identify and classify faults according to specified categories. The model can be used to flag a device returning faulty data automatically. It helps in the early diagnosis of faulty.
Crafted an insightful HR dashboard focusing on gender distribution, promotion eligibility, retirement projections, and commute distance analysis. It helps for effective workforce management.
Welcome to my SQL research project! I used SQL to analyze and investigate a large dataset to find patterns, trends, and insights that might take time, if not impossible, to discover from the raw data.
I developed a model to predict the severity of earthquakes in Kavrepalanchok. The purpose is to obtain the best model and depth for the prediction and to emphasize the various steps needed to build such a model.
Experienced data scientist and analyst skilled in statistical analysis, data visualization, machine learning. Expertise Python, SQL, Power BI & Excel.
Leveraging data to drive strategic decision-making and business growth!
Lagos, Nigeria
ndabdulsalaam@gmail.com
+2348168874902