clustering edits

Clustering/4-API/README.md

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-# [Lesson Topic]
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-## [Pre-lecture quiz](link-to-quiz-app)
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-Describe what we will learn
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-### Introduction
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-Describe what will be covered
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-> Notes
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-### Prerequisite
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-What steps should have been covered before this lesson?
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-### Preparation
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-## [Topic 1]
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-### Task:
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-Work together to progressively enhance your codebase to build the project with shared code:
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-✅ Knowledge Check - use this moment to stretch students' knowledge with open questions
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-## [Topic 2]
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-## [Topic 3]
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-## 🚀Challenge
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-## [Post-lecture quiz](link-to-quiz-app)
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-## Review & Self Study
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-**Assignment**: [Assignment Name](assignment.md)

Clustering/4-API/assignment.md

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-## Instructions
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-## Rubric
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-| Criteria | Exemplary | Adequate | Needs Improvement |
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Clustering/README.md

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 In this series of lessons, you will discover new ways to analyze data using Clustering techniques. Clustering is particularly useful when your dataset lacks labels. If it does have labels, then Classification techniques such as those you learned in previous lessons are more useful. But in cases where you are looking to group unlabelled data, clustering is a great way to discover patterns.
 ## Lessons
 
-1. [Introduction to Clustering with Data Visualizations](1-Visualize/README.md)
+1. [Introduction to Clustering](1-Visualize/README.md)
 2. [K-Means Clustering](2-K-Means/README.md)
 3. [Centroid Clustering](3-Centroid/README.md)
-4. [Build an API for Recommendations](4-API/README.md)
 ## Credits
 
-"Introduction to Clustering" was written with ♥️ by [Jen Looper](https://www.twitter.com/jenlooper)
+These lessons were written with ♥️ by [Jen Looper](https://www.twitter.com/jenlooper)
 
-The [Nigerian Songs](https://www.kaggle.com/sootersaalu/nigerian-songs-spotify) dataset was sourced from Kaggle as scraped from Spotify.
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-The Flask API project was suggested by [this GitHub repo](https://github.com/amirziai/sklearnflask)
+The [Nigerian Songs](https://www.kaggle.com/sootersaalu/nigerian-songs-spotify) dataset was sourced from Kaggle as scraped from Spotify.