Project 3: Modeling Data with Regression and Classification Methods
Budget: $250 – $750 USD
Objective
The goal of this assessment is to guide you through the modeling workflow to produce the best possible model. In this lesson, you will apply the best practices you've learned to date to slice your data and validate your model.
You'll demonstrate the following skills:
Linear Regression
Handling categorical features in a scikit-learn model.
Carrying out a train/test split.
Training a model.
Evaluating that model on the testing data.
K-Nearest Neighbors
Preparing your data for modeling.
Scaling your data.
Tuning a hyperparameter using k-fold cross-validation.
Selecting a model based on a tuning parameter.
Using a model to make predictions on new data.
Compare to other models
Pick a model to compare against.
The goal of this assessment is to guide you through the modeling workflow to produce the best possible model. In this lesson, you will apply the best practices you've learned to date to slice your data and validate your model.
You'll demonstrate the following skills:
Linear Regression
Handling categorical features in a scikit-learn model.
Carrying out a train/test split.
Training a model.
Evaluating that model on the testing data.
K-Nearest Neighbors
Preparing your data for modeling.
Scaling your data.
Tuning a hyperparameter using k-fold cross-validation.
Selecting a model based on a tuning parameter.
Using a model to make predictions on new data.
Compare to other models
Pick a model to compare against.