Главная
Study mode:
on
1
Introduction
2
Class C secondhand reports
3
Class A secondhand reports mutate
4
Exploratory work
5
Data analysis
6
Feature engineering
7
Natural language
8
Logistic regression
9
Tuning grid
10
Show best
11
Last fit
12
Confusion Matrix
13
Variable Importance
14
Deployment
15
Predict
16
Summary
Description:
Learn how to set up various prediction endpoints using vetiver for a model predicting Bigfoot sightings in this 29-minute screencast. Explore the process of feature engineering, natural language processing, and logistic regression as you analyze #TidyTuesday Bigfoot sighting data. Discover techniques for tuning, evaluating model performance through confusion matrices, and assessing variable importance. Gain practical insights into deploying the model and making predictions, with accompanying code available on the presenter's blog for further study and implementation.

Deploy Different Prediction Types for a Bigfoot Sighting Model

Julia Silge
Add to list