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[ FreeCourseWeb.com ] Udemy - Machine Learning for BI, PART 2 - Classification Modeling

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Folder[ FreeCourseWeb.com ] Udemy - Machine Learning for BI, PART 2 - Classification Modeling
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Folder03 Classification Models
File004 CASE STUDY_ KNN.mp4 - 74.9 MB
File025 CASE STUDY_ Sentiment Analysis.mp4 - 45.5 MB
File014 CASE STUDY_ Decision Trees.mp4 - 45.2 MB
File021 CASE STUDY_ Logistic Regression.mp4 - 44.2 MB
File008 CASE STUDY_ Naïve Bayes.mp4 - 39.9 MB
File007 Naïve Bayes _ Conditional Probability.mp4 - 26 MB
File012 Decision Tree Examples.mp4 - 23.7 MB
File019 The Likelihood Function.mp4 - 23 MB
File024 _Bag of Words_ Analysis.mp4 - 21.2 MB
File011 Entropy & Information Gain.mp4 - 20.5 MB
File003 KNN Examples.mp4 - 19.2 MB
File020 Multivariate Logistic Regression.mp4 - 16.1 MB
File017 False Positives vs. False Negatives.mp4 - 15.9 MB
File022 Intro to Sentiment Analysis.mp4 - 13.1 MB
File010 Decision Trees _ Entropy 101.mp4 - 12.9 MB
File016 Logistic Regression Example.mp4 - 11.1 MB
File023 Cleaning Text Data.mp4 - 10 MB
File015 Intro to Logistic Regression.mp4 - 9.84 MB
File009 Intro to Decision Trees.mp4 - 9.51 MB
File006 Naïve Bayes _ Frequency Tables.mp4 - 8.97 MB
File018 Logistic Regression Equation.mp4 - 8.08 MB
File013 Random Forests.mp4 - 7.73 MB
File005 Intro to Naïve Bayes.mp4 - 7.57 MB
File001 Common Classification Models.mp4 - 6.21 MB
File002 Intro to K-Nearest Neighbors (KNN).mp4 - 5.52 MB
File004 CASE STUDY_ KNN.en.srt - 14.5 kB
File014 CASE STUDY_ Decision Trees.en.srt - 12.2 kB
File021 CASE STUDY_ Logistic Regression.en.srt - 12 kB
File008 CASE STUDY_ Naïve Bayes.en.srt - 11.4 kB
File025 CASE STUDY_ Sentiment Analysis.en.srt - 9.79 kB
File007 Naïve Bayes _ Conditional Probability.en.srt - 8.08 kB
File012 Decision Tree Examples.en.srt - 7.66 kB
File003 KNN Examples.en.srt - 6.76 kB
File011 Entropy & Information Gain.en.srt - 6.7 kB
File024 _Bag of Words_ Analysis.en.srt - 6.28 kB
File019 The Likelihood Function.en.srt - 5.29 kB
File017 False Positives vs. False Negatives.en.srt - 4.34 kB
File010 Decision Trees _ Entropy 101.en.srt - 3.99 kB
File020 Multivariate Logistic Regression.en.srt - 3.71 kB
File016 Logistic Regression Example.en.srt - 3.64 kB
File006 Naïve Bayes _ Frequency Tables.en.srt - 3.62 kB
File022 Intro to Sentiment Analysis.en.srt - 2.94 kB
File009 Intro to Decision Trees.en.srt - 2.78 kB
File015 Intro to Logistic Regression.en.srt - 2.75 kB
File023 Cleaning Text Data.en.srt - 2.69 kB
File018 Logistic Regression Equation.en.srt - 2.69 kB
File005 Intro to Naïve Bayes.en.srt - 2.49 kB
File001 Common Classification Models.en.srt - 1.87 kB
File002 Intro to K-Nearest Neighbors (KNN).en.srt - 1.75 kB
File013 Random Forests.en.srt - 1.71 kB
Folder01 Getting Started
File001 Course Structure & Outline.mp4 - 31.2 MB
File005 Setting Expectations.mp4 - 15.7 MB
File003 About this Series.mp4 - 9.86 MB
File004 Machine Learning Part 2 - Classification.pdf - 3.64 MB
File004 Maven_ML_Demos_Part_2.xlsx - 258 kB
File002 READ ME_ Important Notes for New Students.html - 5.41 kB
File005 Setting Expectations.en.srt - 4.41 kB
File003 About this Series.en.srt - 3.24 kB
File001 Course Structure & Outline.en.srt - 3.02 kB
File004 DOWNLOAD_ Course Resources.html - 1.69 kB
Folder04 Model Selection & Tuning
File007 Multi-class Scoring.mp4 - 20.6 MB
File003 Imbalanced Classes.mp4 - 16.2 MB
File002 Hyperparameters.mp4 - 14.5 MB
File006 Multi-class Confusion Matrix.mp4 - 10.8 MB
File005 Accuracy, Precision & Recall.mp4 - 10.7 MB
File004 Confusion Matrix.mp4 - 10.4 MB
File008 Model Selection.mp4 - 8.86 MB
File009 Model Drift.mp4 - 4.88 MB
File001 Intro to Selection & Tuning.mp4 - 4.39 MB
File007 Multi-class Scoring.en.srt - 6.22 kB
File003 Imbalanced Classes.en.srt - 5.16 kB
File002 Hyperparameters.en.srt - 4.86 kB
File005 Accuracy, Precision & Recall.en.srt - 3.67 kB
File004 Confusion Matrix.en.srt - 3.4 kB
File006 Multi-class Confusion Matrix.en.srt - 3.31 kB
File008 Model Selection.en.srt - 2.51 kB
File009 Model Drift.en.srt - 1.72 kB
File001 Intro to Selection & Tuning.en.srt - 1.41 kB
Folder02 Intro to Classification
File004 Classification 101.mp4 - 18.1 MB
File008 Overfitting.mp4 - 17.5 MB
File006 Feature Engineering.mp4 - 17.4 MB
File003 RECAP_ Key Concepts.mp4 - 15.7 MB
File005 Classification Workflow.mp4 - 13 MB
File002 Classification vs. Regression.mp4 - 8.83 MB
File001 Supervised vs. Unsupervised Learning.mp4 - 8.76 MB
File007 Data Splitting.mp4 - 8.7 MB
File004 Classification 101.en.srt - 6.07 kB
File008 Overfitting.en.srt - 5.77 kB
File003 RECAP_ Key Concepts.en.srt - 5.46 kB
File006 Feature Engineering.en.srt - 5.33 kB
File005 Classification Workflow.en.srt - 5.2 kB
File002 Classification vs. Regression.en.srt - 3.35 kB
File001 Supervised vs. Unsupervised Learning.en.srt - 3.02 kB
File007 Data Splitting.en.srt - 2.5 kB
Folder05 Wrapping Up
File001 Looking Ahead to Part 3.mp4 - 3.59 MB
File002 BONUS LECTURE.html - 7.78 kB
File001 Looking Ahead to Part 3.en.srt - 740 B
FileBonus Resources.txt - 357 B
FileGet Bonus Downloads Here.url - 183 B
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  • InfoHash: A6A20E862EEE1D07D3E0A1C9703A72E6C1BF27AC
  • Last Updated: Jan 23, 2022
  • File Count: 99
  • File Category: 1
  • Tags: freecourseweb, udemy, machine, learning, part, classification, modeling
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