Udemy - Machine Learning for BI, PART 4 - Unsupervised Learning
- CategoryOther
- TypeTutorials
- LanguageEnglish
- Total size685.2 MB
- Uploaded Byfreecoursewb
- Downloads45
- Last checkedFeb. 14th '22
- Date uploadedFeb. 11th '22
- Seeders 2
- Leechers7
Machine Learning for BI, PART 4: Unsupervised Learning 
https://TutGee.com
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English + srt | Duration: 49 lectures (2h) | Size: 528.4 MB
Learn powerful Unsupervised Machine Learning techniques like clustering, association mining, outlier detection and more!
What you'll learn
Build foundational Machine Learning & data science skills WITHOUT writing complex code
Use intuitive, user-friendly tools like Microsoft Excel to introduce & demystify machine learning tools & techniques
Explore powerful techniques for clustering, association mining, outlier detection, and dimensionality reduction
Learn how ML models like K-Means, Apriori, Markov and Principal Component Analysis actually work
Enjoy unique, hands-on s to see how Unsupervised ML can be applied to real-world Business Intelligence projects
Requirements
This is a beginner-friendly course (no prior knowledge or math/stats background required)
We'll use Microsoft Excel (Office 365) for some course s, but participation is optional
This is PART 4 of our Machine Learning for BI series (we recommend taking Parts 1, 2 & 3 first)
Files:
[ TutGee.com ] Udemy - Machine Learning for BI, PART 4 - Unsupervised Learning- Get Bonus Downloads Here.url (0.2 KB) ~Get Your Files Here ! 01 - Getting Started
- 001 Course Structure & Outline.mp4 (28.5 MB)
- 001 Course Structure & Outline_en.srt (3.0 KB)
- 002 READ ME Important Notes for New Students.html (4.8 KB)
- 003 About This Series.mp4 (2.2 MB)
- 003 About This Series_en.srt (0.4 KB)
- 004 DOWNLOAD Course Resources.html (0.8 KB)
- 004 Machine-Learning-Part-4-Unsupervised.pdf (17.1 MB)
- 004 Maven-ML-Demos-Part-4.xlsx (3.5 MB)
- 005 Setting Expectations.mp4 (11.6 MB)
- 005 Setting Expectations_en.srt (3.0 KB)
- 001 Supervised vs. Unsupervised Learning.mp4 (10.5 MB)
- 001 Supervised vs. Unsupervised Learning_en.srt (2.8 KB)
- 002 Common Unsupervised Techniques.mp4 (7.2 MB)
- 002 Common Unsupervised Techniques_en.srt (2.1 KB)
- 003 Unsupervised ML Workflow.mp4 (9.1 MB)
- 003 Unsupervised ML Workflow_en.srt (2.5 KB)
- 004 Feature Engineering.mp4 (6.7 MB)
- 004 Feature Engineering_en.srt (1.9 KB)
- 005 KEY TAKEAWAYS Intro to Unsupervised ML.mp4 (6.1 MB)
- 005 KEY TAKEAWAYS Intro to Unsupervised ML_en.srt (1.9 KB)
- 001 Introduction.mp4 (4.5 MB)
- 001 Introduction_en.srt (1.5 KB)
- 002 Clustering Basics.mp4 (10.4 MB)
- 002 Clustering Basics_en.srt (2.8 KB)
- 003 Intro to K-Means.mp4 (15.2 MB)
- 003 Intro to K-Means_en.srt (5.0 KB)
- 004 WSS & Elbow Plots.mp4 (10.7 MB)
- 004 WSS & Elbow Plots_en.srt (3.3 KB)
- 005 K-Means FAQs.mp4 (6.6 MB)
- 005 K-Means FAQs_en.srt (1.9 KB)
- 006 CASE STUDY K-Means.mp4 (88.2 MB)
- 006 CASE STUDY K-Means_en.srt (17.0 KB)
- 007 Intro to Hierarchical Clustering.mp4 (12.7 MB)
- 007 Intro to Hierarchical Clustering_en.srt (4.9 KB)
- 008 Anatomy of a Dendrogram.mp4 (8.6 MB)
- 008 Anatomy of a Dendrogram_en.srt (2.8 KB)
- 009 Hierarchical Clustering FAQs.mp4 (9.4 MB)
- 009 Hierarchical Clustering FAQs_en.srt (2.7 KB)
- 010 KEY TAKEAWAYS Clustering & Segmentation.mp4 (7.3 MB)
- 010 KEY TAKEAWAYS Clustering & Segmentation_en.srt (2.0 KB)
- 001 Introduction.mp4 (4.2 MB)
- 001 Introduction_en.srt (1.2 KB)
- 002 Association Mining Basics.mp4 (7.7 MB)
- 002 Association Mining Basics_en.srt (2.0 KB)
- 003 The Apriori Algorithm.mp4 (9.0 MB)
- 003 The Apriori Algorithm_en.srt (2.0 KB)
- 004 Basket Analysis Examples.mp4 (23.5 MB)
- 004 Basket Analysis Examples_en.srt (6.9 KB)
- 005 Minimum Support Thresholds.mp4 (7.0 MB)
- 005 Minimum Support Thresholds_en.srt (1.6 KB)
- 006 Infrequent Itemsets.mp4 (18.8 MB)
- 006 Infrequent Itemsets_en.srt (4.7 KB)
- 007 Multiple Item Sets.mp4 (7.8 MB)
- 007 Multiple Item Sets_en.srt (2.5 KB)
- 008 CASE STUDY Apriori.mp4 (52.5 MB)
- 008 CASE STUDY Apriori_en.srt (10.8 KB)
- 009 Markov Chains.mp4 (24.8 MB)
- 009 Markov Chains_en.srt (7.1 KB)
- 010 CASE STUDY Markov Chains.mp4 (28.6 MB)
- 010 CASE STUDY Markov Chains_en.srt (6.2 KB)
- 011 KEY TAKEAWAYS Association Mining.mp4 (8.5 MB)
- 011 KEY TAKEAWAYS Association Mining_en.srt (2.0 KB)
- 001 Introduction.mp4 (7.7 MB)
- 001 Introduction_en.srt (1.9 KB)
- 002 Outlier Detection Basics.mp4 (10.1 MB)
- 002 Outlier Detection Basics_en.srt (2.8 KB)
- 003 Cross-Sectional Outliers.mp4 (11.2 MB)
- 003 Cross-Sectional Outliers_en.srt (2.8 KB)
- 004 Cross-Sectional Outlier Example.mp4 (21.3 MB)
- 004 Cross-Sectional Outlier Example_en.srt (4.3 KB)
- 005 CASE STUDY Cross-Sectional Outlier.mp4 (54.8 MB)
- 005 CASE STUDY Cross-Sectional Outlier_en.srt (8.5 KB)
- 006 Time-Series Outliers.mp4 (8.5 MB)
- 006 Time-Series Outliers_en.srt (2.3 KB)
- 007 Time-Series Outlier Example.mp4 (14.7 MB)
- 007 Time-Series Outlier Example_en.srt (3.3 KB)
- 008 KEY TAKEAWAYS Outlier Detection.mp4 (6.0 MB)
- 008 KEY TAKEAWAYS Outlier Detection_en.srt (1.4 KB)
- 001 Introduction.mp4 (2.6 MB)
- 001 Introduction_en.srt (0.7 KB)
- 002 Dimensionality Reduction Basics.mp4 (14.4 MB)
- 002 Dimensionality Reduction Basics_en.srt (3.2 KB)
- 003 Principle Component Analysis.mp4 (7.8 MB)
- 003 Principle Component Analysis_en.srt (1.9 KB)
- 004 PCA Example.mp4 (14.2 MB)
- 004 PCA Example_en.srt (3.3 KB)
- 005 Interpreting Components.mp4 (15.1 MB)
- 005 Interpreting Components_en.srt (3.5 KB)
- 006 Scree Plots.mp4 (13.9 MB)
- 006 Scree Plots_en.srt (3.4 KB)
- 007 Advanced Techniques.mp4 (5.0 MB)
- 007 Advanced Techniques_en.srt (1.3 KB)
- 008 KEY TAKEAWAYS Dimensionality Reduction.mp4 (6.2 MB)
- 008 KEY TAKEAWAYS Dimensionality Reduction_en.srt (1.5 KB)
- 001 Series Conclusion.mp4 (3.4 MB)
- 001 Series Conclusion_en.srt (0.9 KB)
- 002 BONUS LECTURE.html (8.0 KB)
- Bonus Resources.txt (0.4 KB)
Code:
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