Python Tutorial : School Budgeting with Machine Learning in Python
Key Takeaways
Uses machine learning to predict school budgeting in Python
Original Description
Want to learn more? Take the full course at https://learn.datacamp.com/courses/case-study-school-budgeting-with-machine-learning-in-python at your own pace. More than a video, you'll learn hands-on coding & quickly apply skills to your daily work.
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Hello DataCampers! How's it going? Really glad you've decided to join us for this course. We have an exciting journey ahead of us through some real data and some incredibly useful tips and tricks from expert data scientists. I'm Peter Bull, a data scientist and a co-founder of DrivenData. Our mission is to bring the power of data science to social impact organizations. One of the ways we do that is by running online data science challenges for non-profits, NGOs, and social enterprises. In our challenges, a global community of data scientists--like you!--competes to solve a particular problem. We'll work through one of these competitions as a case-study, and we'll show you how the winner achieved the best score. In the course, we'll do some natural language processing, some feature engineering, and boost our computational efficiency. In addition to these pro-tips, we'll look at one of the ways in which we can use data to have a social impact.
School budgets in the United States are incredibly complex, and there are no standards for reporting how money is spent. Schools want to be able to measure their performance--for example, are we spending more on textbooks than our neighboring schools, and is that investment worthwhile? However to do this comparison takes hundreds of hours each year in which analysts hand-categorize each line-item. Our goal is to build a machine learning algorithm that can automate that process. For each line item, we have some text fields that tell us about the expense--for example, a line might say something like "Algebra books for 8th grade students". We also have the amount of the expense in dollars. This line item then has a set of labels attached to it. For example, this one might have labe
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