From the course: Artificial Intelligence Foundations: Machine Learning
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Demo: Designing and building a pipeline
From the course: Artificial Intelligence Foundations: Machine Learning
Demo: Designing and building a pipeline
- [Instructor] Let's see the steps needed to implement pipelines in our code. First, let's review the normal machine learning code used to train a model. This is code you've seen before, which is used to train a model to predict the cost of a home. First, you obtain and load your data. Then we go through the preparation process where we understand missing data, we impute that missing data, we use visualizations to understand the relationships, we use histograms, we also use heat maps to understand the correlation. Then we did a bit of feature engineering to remove the highly correlated fields, then we encoded our categorical data, and then we trained the model. And the most important piece that I want you to understand here, when we trained our model, we used three different learning algorithms. We had a section for linear regression, We trained the model, we ran the predictions, we evaluated the model, and…
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