projects by Nathan George
Data Science Bookcamp Projects
Are you ready to work out with the Data Science Bookcamp? This series of liveProjects takes you hands-on with fun and engaging data science challenges from the bestselling book by Leonard Apeltsin. It features Discovering Disease Outbreaks from News Headlines, which he co-created with Will Koehrsen, Nate George’s Decoding Data Science Job Postings to Improve Your Resume, and three original projects by Emre Rencberoglu. Each challenge stretches your data science muscles and teaches you useful new skills through practice, such as using NumPy and SciPy for mathematical operations, clustering with scikit-learn, and analyzing and visualizing network datasets with NetworkX. Tackle them individually or all of them for an intensive workout of your data capabilities!
Predicting Loan Defaults Using scikit-learn and H2O
The Python data science ecosystem is a powerful and open-source toolset utilized daily by thousands of data scientists and machine learning engineers. But with so many Python machine learning libraries to choose from, which tool works best for your needs?
In this liveProject, you’ll go hands-on with the scikit-learn and H2O frameworks, using them both to build working machine learning classifiers. You’ll use raw financial data and the tried-and-true random forest model to predict the chance of financial loan defaults. Once you’ve built your models, you'll compare implementations to find out which works best and evaluate your results against existing hard-coded tools.
Decoding Data Science Job Postings to Improve Your Resume
In this liveProject, you’ll step into the life of a budding data scientist looking for their first job in the industry. There are thousands of potential roles being advertised online, but only a few that are a good match to your skill set. Your challenge is to use data science tools to automate the process of trawling through job listings, to save time as you optimize your resume, identify the most in-demand skills, and find jobs that are a good fit for you. To do this you’ll use Python to perform Natural Language Processing and text analysis on pre-scraped data from jobs posting websites.
