July 2019
Beginner to intermediate
740 pages
16h 52m
English
Content preview from Hands-On Data Analysis with Pandas
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Exercises
Complete the following exercises to practice the skills covered in this chapter. Be sure to consult the Machine learning workflow section in the appendix as a refresher for the process of building models:
- Predict star temperature with elastic net linear regression as follows:
- Using the data/stars.csv file, build a pipeline to normalize the data with the MinMaxScaler and then run elastic net linear regression using all the numeric columns to predict the temperature of the star.
- Run grid search on the pipeline to find the best values for alpha, l1_ratio, and fit_intercept for the elastic net in the search space of your choice.
- Train the model on 75% of the initial data.
- Calculate the R2 of your model.
- Find the coefficients for each ...
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.