| 1. Introduction to Clustering.mp4 | 117.8 MB | ||
| 1. Introduction to Dimensionality Reduction.mp4 | 78.5 MB | ||
| 1. Introduction to Frequent Itemset Mining and Association Rule Mining - Part 1.mp4 | 44.2 MB | ||
| 1. Introduction.mp4 | 37.5 MB | ||
| 2. Example of using College Scorecard Data - from Industry.mp4 | 94.3 MB | ||
| 2. Feature Removal of Highly Correlated Features.mp4 | 70.4 MB | ||
| 2. Instructor Welcome.mp4 | 64.8 MB | ||
| 2. Introduction to Frequent Itemset Mining and Association Rule Mining - Part 2.mp4 | 50.8 MB | ||
| 3. Getting and Loading the College Scorecard Data.mp4 | 166.2 MB | ||
| 3. Measuring Results of Association Rules.mp4 | 52.3 MB | ||
| 3. PCA in R - Part 1.mp4 | 99 MB | ||
| 3. Prerequisites.html | 2.6 KB | ||
| 3.1 CRAN Task Views -- a listing R packages organized into categories or tasks.html | 102.4 B | ||
| 3.2 Installing Packages in R.html | 102.4 B | ||
| 3.3 R Language.html | 102.4 B | ||
| 3.4 R Studio IDE.html | 102.4 B | ||
| 4. Cleaning and Preparing Data for Frequent Itemset Mining and Association Rules.mp4 | 85.1 MB | ||
| 4. PCA in R - Part 2.mp4 | 77.1 MB | ||
| 4. Scaling The Data - Required for Clustering Analyses.mp4 | 161.8 MB | ||
| 4. Why use R and R Studio for this.html | 3 KB | ||
| 5. Dimensionality Quiz.html | 204.8 B | ||
| 5. Frequent Itemsets.mp4 | 70.8 MB | ||
| 5. Getting Data Sets.mp4 | 50.8 MB | ||
| 5. Using Hierarchical Clustering in R.mp4 | 276.4 MB | ||
| 5.1 Data from the FiveThirtyEight website.html | 102.4 B | ||
| 5.2 Data.Gov.html | 102.4 B | ||
| 5.3 Human Resources Data Set.html | 102.4 B | ||
| 5.4 Kaggle.html | 102.4 B | ||
| 6. Apply PCA to a New Dataset.html | 204.8 B | ||
| 6. Association Rules.mp4 | 45.9 MB | ||
| 6. Running a kMeans Clustering Analysis in R.mp4 | 111.3 MB | ||
| 7. Cluster Validity.mp4 | 129.8 MB | ||
| 7. Sorting Itemsets and Rules.mp4 | 48 MB | ||
| 8. Creating Your Own Clustering Analysis.html | 204.8 B | ||
| 8. Frequent Itemset Mining and Association Rules.html | 204.8 B | ||
| Bonus Resources.txt | 409.6 B | ||
| Get Bonus Downloads Here.url | 204.8 B | ||
| ▲ 37 total files | |||
Unlocking the Secrets of Data: Unsupervised Learning with R
https://DevCourseWeb.com
Published 2/2024
Created by Rich Huebner
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English | Duration: 23 Lectures ( 2h 13m ) | Size: 1.88 GB
Clustering, Association Rule Mining, and Dimensionality Reduction Techniques
What you'll learn:
Apply clustering algorithms to college scorecard data
Apply association rule mining to a set of products that customers have subscribed to
Apply dimensionality reduction techniques in preparation for clustering analyses
Use the R programming language to accomplish unsupervised machine learning tasks
Requirements:
Some familiarity with R is needed. Learners should have R and R Studio installed already. I will make sure there is at least one lecture describing which packages you will need for this course.
| torrent name | size | uploader | age | seed | leech |
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| 2.4 GB | freecoursewb | 5 months | 0 | 0 | |
| 1.3 GB | freecoursewb | 8 months | 0 | 0 | |
| 3.7 GB | freecoursewb | 10 months | 7 | 0 | |
| 1.1 GB | freecoursewb | 1 year | 4 | 1 | |
| 318.2 MB | freecoursewb | 1 year | 6 | 1 |
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