This is the fifth post in a series of posts on how to build a Data Science Portfolio. If you like this and want to know when the next post in the series is released, you can subscribe at the bottom of the page.
If you’ve ever worked on a personal data science project, you’ve probably spent a lot of time browsing the internet looking for interesting datasets to analyze. It can be fun to sift through dozens of datasets to find the perfect one, but it can also be frustrating to download and import several csv files, only to realize that the data isn’t that interesting after all. Luckily, there are online repositories that curate datasets and (mostly) remove the uninteresting ones.
In this post, we’ll walk through several types of data science projects, including data visualization projects, data cleaning projects, and machine learning projects, and identify good places to find datasets for each. Whether you want to strengthen your data science portfolio by showing that you can visualize data well, or you have a spare few hours and want to practice your machine learning skills, we’ve got you covered.
Datasets for Data Visualization Projects
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