From 155b88c593b1ce5c7a9fc971f10c550f75b0d6fd Mon Sep 17 00:00:00 2001 From: Jen Looper Date: Sun, 6 Jun 2021 23:18:44 -0400 Subject: [PATCH] formatting edits --- 4-Classification/1-Introduction/README.md | 35 +++-------------------- 1 file changed, 4 insertions(+), 31 deletions(-) diff --git a/4-Classification/1-Introduction/README.md b/4-Classification/1-Introduction/README.md index 31fb50b62..bc0c7aa4a 100644 --- a/4-Classification/1-Introduction/README.md +++ b/4-Classification/1-Introduction/README.md @@ -17,45 +17,18 @@ Classification uses various algorithms to determine other ways of determining a Before working to clean the data and prepare it for analysis, it's useful to understand several of the algorithms that you will use. -Support-vector machines -Naive Bayes -Decision trees -K-nearest neighbor algorithm +- Support-vector machines +- Naive Bayes +- Decision trees +- K-nearest neighbor algorithm -### Prerequisite -What steps should have been covered before this lesson? - -### Preparation - -Preparatory steps to start this lesson - ---- - -[Step through content in blocks] - -## [Topic 1] - -### Task: - -Work together to progressively enhance your codebase to build the project with shared code: - -```html -code blocks -``` ✅ Knowledge Check - use this moment to stretch students' knowledge with open questions -## [Topic 2] - -## [Topic 3] ## 🚀Challenge -Add a challenge for students to work on collaboratively in class to enhance the project - -Optional: add a screenshot of the completed lesson's UI if appropriate - ## [Post-lecture quiz](link-to-quiz-app) ## Review & Self Study