This lab is part of a lab series, where you go from exploring a taxicab dataset to training and deploying a high-accuracy distributed model with Cloud ML Engine.
To complete this lab, you need:
In this lab, you will improve the ML model using feature engineering. In the process, you will learn how to:
Start Datalab using the instructions in Launch Datalab and come back to this lab.
In Cloud Datalab, click on the Home icon, and then navigate to training-data-analyst/courses/machine_learning/feateng and open feateng.ipynb.
In Datalab, click on Clear | All Cells. Now read the narrative and execute each cell in turn.
Your instructor will demo notebooks that contain hyper-parameter tuning and training on 500 million rows of data. The changes to the model are minor -- essentially just command-line parameters, but the impact on model accuracy is huge:
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