Salifort Motors is commissioning an external data team to tackle a pivotal request from its Human Resource department.
The primary objective of this project is to implement a robust logistic regression or tree-based machine learning model, with the aim of revolutionizing employee retention strategies within the organization.
The New York City Taxi & Limousine Commission (NYC TLC) has made a business request for a project to develop a viable machine learning model.
The idea is to forecast if passengers in NYC TLC taxi cabs will tip generously. This initiative intends to provide useful insights into how to increase driver earnings and improve the overall passenger experience in the city's busy transportation network.
TikTok, a widely used social media platform, has commissioned an external data team for a machine learning project with the goal of improving the accuracy of claim classification for user submissions on their platform by developing a logistic regression model to forecast the verified status of user accounts,
a significant step toward improving content moderation and increasing user engagement.
This project is related to a Kaggle Machine Learning competition, the objective is to use machine learning to create a model that predicts which passengers survived the Titanic shipwreck.
Then answer the following question: "What sorts of people were more likely to survive the Titanic sinking?"
A demonstration of my web scraping skills using Python to extract data from a Wikipedia page displaying an updated ranking of the top 100 companies in the United States by revenue.
As part of the Waze Data Team, we are embarking on a data analytics project with the objective of enhancing overall growth by reducing monthly user attrition on the Waze app. This initiative is geared towards gaining deeper insights into user behavior,
enabling Waze to implement strategies that will foster user engagement and satisfaction, thereby ensuring a sustained and thriving community of Waze app users.
I leverage TABLEAU to distill valuable insights from diverse data sources, including public records and Kaggle datasets. Additionally, I strive to make the data accessible and understandable to a wide audience, enhancing the project's overall value.