5 Essential Data Science Projects for Your Portfolio
In this video I walk through the 5 essential data science projects that you should have in your portfolio. Having these 5 different projects will show employers that you have diversity in your data science skillset.
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Project 1: Exploratory data analysis (EDA) - This shows that you can clearly tell a story with your data. It also shows that you can collect, clean, and perform feature engineering. I recommend scraping your data or collecting it from an open api.
Project 2: Classification problem - With these projects you are predicting a binary or categorical outcome. An example would be the titanic dataset where you predict if people would have survived the crash.
Project 3: A regression problem - In these types of analyses, you try to predict a continuous outcome. An example would be predicting how many likes a youtube video would get ;).
Project 4: A clustering problem - With this we use algorithms to understand which data points are related to eachother.
Project 5: An advanced topic (NLP, Computer Vision, Deep Neural Nets) - These projects allow you to specialize and show off your skills!
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0:00 Intro
0:58 Exploratory Data Analysis
1:28 Classification Project
2:58 Regression Project
3:45 Clustering Project
5:05 Advanced Techniques
6:00 How to win GTC Tickets
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