Data Scientist | Machine Learning Engineer -> A detail oriented problem solver aiming to make an impact. Open and eager to learn, unlearn & grow.
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Assessing your cultural and operational fit
PRODIGY_DS_04
December 13, 2023 – December 13, 2023
Analyze and visualize sentiment patterns in social media data to understand public opinion and attitudes towards specific topics or brands
View ProjectPRODIGY_DS_03
December 6, 2023 – December 13, 2023
Build a decision tree classifier to predict whether a customer will purchase a product or service based on their demographic and behavioral data. Use a dataset such as the Bank Marketing dataset from the UCI Machine Learning Repository.
View ProjectPRODIGY_DS_02
December 1, 2023 – December 6, 2023
Analysis on data, exploring characteristics within and the relationships between variables to find trends and patterns.
View ProjectPRODIGY_DS_01
November 21, 2023 – November 21, 2023
Visualizations of Kenya's population and some of it's demographic using python and Tableau.
View Projectcraigslist_used_vehicles_TSA
October 23, 2023 – November 2, 2023
craigslist_used_vehicles_TSA — repository
View ProjectTeleco_customer_churn_prediction
September 29, 2023 – November 3, 2023
Sprint, one of the biggest telecom companies in the USA are keen on figuring out how many customers might decide to leave them in the coming months. Create a machine learning model that can predict if someone's going to leave or not?
View ProjectKPMG_Virtual_Internship
September 10, 2023 – September 20, 2023
Data Analysis task to find patterns in the customer detail. Thus determining the best marketing strategy to use and the best customers to target for Sprocket Central Pty Ltd, a company dealing with bikes and bike accessories.
View ProjectAirbnb_Project
September 6, 2022 – September 20, 2022
Build a recommendation system for Airbnbs.
View ProjectCultural Fit Analysis
The candidate shows initiative through numerous personal projects, indicating a self-starter attitude. The diversity of project topics suggests adaptability and a willingness to explore different data science domains. However, without team-based projects or work experience, assessing collaboration and broader cultural fit is challenging.
Soft Skills & Operational Fit
Insufficient data to assess soft skills and operational fit. The candidate's project descriptions are brief, limiting insight into collaboration or problem-solving approaches.