Weston is a member of the DataCamp team and all-around stats guy. He is passionate about making education efficient and accessible with the help of technology. He holds a degree in statistics from Harvard where he also served as a teaching fellow.
Interested in starting to put your data science skills to work in order to solve some of the world’s biggest social challenges? DrivenData provides that opportunity by hosting challenges where data scientists compete to come up with the best statistical model for difficult predictive problems that make a difference. In this practice challenge, you will be predicting which water pumps throughout Tanzania are functional, which need some repairs, and which do not work at all based on a number of variables. A smart understanding of which waterpoints will fail can improve maintenance operations and ensure that clean, potable water is available to communities across Tanzania.
1 Intro to DrivenData Water Pumps
In this first chapter, you will be introduced to DataCamp’s interactive interface and the DrivenData Water Pumps data set. You will then evaluate the structure of the data by visualizing some the data’s important features.
- How it works 100 xp
- Data Mining the Water Table 100 xp
- Understanding your data 50 xp
- Water table() 100 xp
- Explore and Visualize 100 xp
- Which Well Quantities are Funtional? 50 xp
- Continuous Variable Viz 100 xp
- Mapping Well Locations 100 xp
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2 Predict and Measure
In this chapter we will use a common machine learning technique to make and evaluate predictions.
- First Prediction 100 xp
- Evaluating the Random Forest 50 xp
- Variable Importance 50 xp
- Adding Features 100 xp
- Predict, Submit and Next Steps 100 xp
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