I am a Data Scientist passionate about using data to drive business growth and improve operational efficiency. I am well-equipped to extract insights from large and complex data sets. I am a quick learner, always looking to expand my knowledge and stay up-to-date with the latest developments in the field. My strong problem-solving, organizational, and analytical skills make me a valuable addition to any team.
Ask a home buyer to describe their dream house, and they probably won't begin with the height of the basement ceiling or the proximity to an east-west railroad. But this notebook proves what much more influences price negotiations, the number of bedrooms or a white-picket fence. With 79 explanatory variables describing (almost) every aspect of residential homes in Ames, Iowa, this is a challenge to predict the final price of each home.
The sinking of the Titanic is one of the most infamous shipwrecks in history. On April 15, 1912, during her maiden voyage, the widely considered “unsinkable” RMS Titanic sank after colliding with an iceberg. Unfortunately, there weren’t enough lifeboats for everyone onboard, resulting in the death of 1502 out of 2224 passengers and crew. While there was some element of luck involved in surviving, it seems some groups of people were more likely to survive than others. In this challenge, we will build a predictive model that answers the question: “what sorts of people were more likely to survive?”
This case study analyzes smart device fitness data to help unlock new growth opportunities for the Bellabeat company. The insights discovered will help guide a marketing strategy for the company.
This case study analyzes how the two groups of users (members and casual) of Cyclistic use the company services to design a marketing campaign whose goal is to convert casual riders to become annual members.
