YoVDO

Deploy Different Prediction Types for a Bigfoot Sighting Model

Offered By: Julia Silge via YouTube

Tags

Data Science Courses Machine Learning Courses Predictive Modeling Courses Logistic Regression Courses Feature Engineering Courses Confusion Matrix Courses

Course Description

Overview

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.

Syllabus

Introduction
Class C secondhand reports
Class A secondhand reports mutate
Exploratory work
Data analysis
Feature engineering
Natural language
Logistic regression
Tuning grid
Show best
Last fit
Confusion Matrix
Variable Importance
Deployment
Predict
Summary


Taught by

Julia Silge

Related Courses

Data Science at Scale - Capstone Project
University of Washington via Coursera
Feature Engineering for Improving Learning Environments
University of Texas Arlington via edX
How to Win a Data Science Competition: Learn from Top Kagglers
Higher School of Economics via Coursera
Advanced Machine Learning
The Open University via FutureLearn
Feature Engineering
Google Cloud via Coursera