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Udemy Machine Learning A ZTM AI Python R ChatGPT Bonus 2023

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Files:

[CourseClub.Me].url 122 bytes
[FreeCourseSite.com].url 127 bytes
[GigaCourse.Com].url 49 bytes
001 Welcome Challenge!.html 3.0 KB
002 Machine Learning Demo - Get Excited!.mp4 50.8 MB
002 Machine Learning Demo - Get Excited!_en.srt 9.1 KB
003 Get all the Datasets, Codes and Slides here.html 442 bytes
004 How to use the ML A-Z folder & Google Colab.mp4 25.6 MB
004 How to use the ML A-Z folder & Google Colab_en.srt 11.7 KB
005 Installing R and R Studio (Mac, Linux & Windows).mp4 33.6 MB
005 Installing R and R Studio (Mac, Linux & Windows)_en.srt 10.4 KB
006 BONUS Use ChatGPT to Boost your ML Skills.html 1022 bytes
001 Welcome to Part 1 - Data Preprocessing.html 531 bytes
002 The Machine Learning process.mp4 8.0 MB
002 The Machine Learning process_en.srt 3.0 KB
003 Splitting the data into a Training and Test set.mp4 5.4 MB
003 Splitting the data into a Training and Test set_en.srt 3.5 KB
004 Feature Scaling.mp4 14.0 MB
004 Feature Scaling_en.srt 12.0 KB
001 Getting Started - Step 1.mp4 10.8 MB
001 Getting Started - Step 1_en.srt 10.6 KB
002 Getting Started - Step 2.mp4 35.1 MB
002 Getting Started - Step 2_en.srt 10.0 KB
003 Importing the Libraries.mp4 7.5 MB
003 Importing the Libraries_en.srt 7.1 KB
004 Importing the Dataset - Step 1.mp4 12.5 MB
004 Importing the Dataset - Step 1_en.srt 10.3 KB
005 Importing the Dataset - Step 2.mp4 9.8 MB
005 Importing the Dataset - Step 2_en.srt 8.5 KB
006 Importing the Dataset - Step 3.mp4 13.9 MB
006 Importing the Dataset - Step 3_en.srt 11.0 KB
007 For Python learners, summary of Object-oriented programming classes & objects.html 1.5 KB
008 Taking care of Missing Data - Step 1.mp4 16.1 MB
008 Taking care of Missing Data - Step 1_en.srt 13.3 KB
009 Taking care of Missing Data - Step 2.mp4 29.4 MB
009 Taking care of Missing Data - Step 2_en.srt 10.5 KB
010 Encoding Categorical Data - Step 1.mp4 13.4 MB
010 Encoding Categorical Data - Step 1_en.srt 7.7 KB
011 Encoding Categorical Data - Step 2.mp4 19.7 MB
011 Encoding Categorical Data - Step 2_en.srt 10.7 KB
012 Encoding Categorical Data - Step 3.mp4 14.1 MB
012 Encoding Categorical Data - Step 3_en.srt 8.1 KB
013 Splitting the dataset into the Training set and Test set - Step 1.mp4 10.3 MB
013 Splitting the dataset into the Training set and Test set - Step 1_en.srt 7.1 KB
014 Splitting the dataset into the Training set and Test set - Step 2.mp4 13.7 MB
014 Splitting the dataset into the Training set and Test set - Step 2_en.srt 10.6 KB
015 Splitting the dataset into the Training set and Test set - Step 3.mp4 11.6 MB
015 Splitting the dataset into the Training set and Test set - Step 3_en.srt 6.7 KB
016 Feature Scaling - Step 1.mp4 13.1 MB
016 Feature Scaling - Step 1_en.srt 10.9 KB
017 Feature Scaling - Step 2.mp4 11.7 MB
017 Feature Scaling - Step 2_en.srt 8.7 KB
018 Feature Scaling - Step 3.mp4 11.2 MB
018 Feature Scaling - Step 3_en.srt 7.1 KB
019 Feature Scaling - Step 4.mp4 16.9 MB
019 Feature Scaling - Step 4_en.srt 11.1 KB
001 Getting Started.mp4 4.1 MB
001 Getting Started_en.srt 3.1 KB
002 Dataset Description.mp4 6.4 MB
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003 Importing the Dataset.mp4 6.9 MB
003 Importing the Dataset_en.srt 4.9 KB
004 Taking care of Missing Data.mp4 21.4 MB
004 Taking care of Missing Data_en.srt 10.6 KB
005 Encoding Categorical Data.mp4 63.9 MB
005 Encoding Categorical Data_en.srt 10.2 KB
006 Splitting the dataset into the Training set and Test set - Step 1.mp4 16.6 MB
006 Splitting the dataset into the Training set and Test set - Step 1_en.srt 9.3 KB
007 Splitting the dataset into the Training set and Test set - Step 2.mp4 19.7 MB
007 Splitting the dataset into the Training set and Test set - Step 2_en.srt 9.0 KB
008 Feature Scaling - Step 1.mp4 22.8 MB
008 Feature Scaling - Step 1_en.srt 7.7 KB
009 Feature Scaling - Step 2.mp4 36.3 MB
009 Feature Scaling - Step 2_en.srt 8.1 KB
010 Data Preprocessing Template.mp4 22.6 MB
010 Data Preprocessing Template_en.srt 10.9 KB
[CourseClub.Me].url 122 bytes
[FreeCourseSite.com].url 127 bytes
[GigaCourse.Com].url 49 bytes
001 Welcome to Part 2 - Regression.html 829 bytes
001 Simple Linear Regression Intuition.mp4 5.0 MB
001 Simple Linear Regression Intuition_en.srt 4.1 KB
002 Ordinary Least Squares.mp4 12.7 MB
002 Ordinary Least Squares_en.srt 5.8 KB
003 Simple Linear Regression in Python - Step 1a.mp4 8.7 MB
003 Simple Linear Regression in Python - Step 1a_en.srt 11.2 KB
004 Simple Linear Regression in Python - Step 1b.mp4 14.5 MB
004 Simple Linear Regression in Python - Step 1b_en.srt 11.2 KB
005 Simple Linear Regression in Python - Step 2a.mp4 8.5 MB
005 Simple Linear Regression in Python - Step 2a_en.srt 7.2 KB
006 Simple Linear Regression in Python - Step 2b.mp4 10.9 MB
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007 Simple Linear Regression in Python - Step 3_en.srt 8.9 KB
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008 Simple Linear Regression in Python - Step 4a_en.srt 10.6 KB
009 Simple Linear Regression in Python - Step 4b.mp4 19.4 MB
009 Simple Linear Regression in Python - Step 4b_en.srt 11.1 KB
010 Simple Linear Regression in Python - Additional Lecture.html 1.1 KB
011 Simple Linear Regression in R - Step 1.mp4 11.3 MB
011 Simple Linear Regression in R - Step 1_en.srt 7.4 KB
012 Simple Linear Regression in R - Step 2.mp4 19.1 MB
012 Simple Linear Regression in R - Step 2_en.srt 8.6 KB
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014 Simple Linear Regression in R - Step 4a.mp4 29.0 MB
014 Simple Linear Regression in R - Step 4a_en.srt 9.8 KB
015 Simple Linear Regression in R - Step 4b.mp4 20.7 MB
015 Simple Linear Regression in R - Step 4b_en.srt 9.4 KB
001 Dataset + Business Problem Description.mp4 14.1 MB
001 Dataset + Business Problem Description_en.srt 5.5 KB
002 Multiple Linear Regression Intuition.mp4 8.4 MB
002 Multiple Linear Regression Intuition_en.srt 4.5 KB
003 Assumptions of Linear Regression.mp4 24.6 MB
003 Assumptions of Linear Regression_en.srt 8.8 KB
003 Download-the-PDF.url 68 bytes
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015 Multiple Linear Regression in Python - Step 4b_en.srt 9.5 KB
016 Multiple Linear Regression in Python - Backward Elimination.html 3.5 KB
017 Multiple Linear Regression in Python - EXTRA CONTENT.html 1.2 KB
018 Multiple Linear Regression in R - Step 1a.mp4 10.6 MB
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019 Multiple Linear Regression in R - Step 1b.mp4 14.7 MB
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020 Multiple Linear Regression in R - Step 2a_en.srt 9.5 KB
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022 Multiple Linear Regression in R - Step 3.mp4 14.3 MB
022 Multiple Linear Regression in R - Step 3_en.srt 6.8 KB
023 Multiple Linear Regression in R - Backward Elimination - HOMEWORK !.mp4 64.5 MB
023 Multiple Linear Regression in R - Backward Elimination - HOMEWORK !_en.srt 26.5 KB
024 Multiple Linear Regression in R - Backward Elimination - Homework Solution.mp4 32.5 MB
024 Multiple Linear Regression in R - Backward Elimination - Homework Solution_en.srt 11.4 KB
025 Multiple Linear Regression in R - Automatic Backward Elimination.html 752 bytes
external-links.txt 70 bytes
001 Polynomial Regression Intuition.mp4 8.6 MB
001 Polynomial Regression Intuition_en.srt 7.5 KB
002 Polynomial Regression in Python - Step 1a.mp4 7.5 MB
002 Polynomial Regression in Python - Step 1a_en.srt 8.4 KB
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003 Polynomial Regression in Python - Step 1b_en.srt 11.3 KB
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007 Polynomial Regression in Python - Step 3b_en.srt 10.5 KB
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008 Polynomial Regression in Python - Step 4a_en.srt 6.9 KB
009 Polynomial Regression in Python - Step 4b.mp4 9.0 MB
009 Polynomial Regression in Python - Step 4b_en.srt 6.8 KB
010 Polynomial Regression in R - Step 1a.mp4 16.8 MB
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011 Polynomial Regression in R - Step 1b.mp4 13.7 MB
011 Polynomial Regression in R - Step 1b_en.srt 6.7 KB
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015 Polynomial Regression in R - Step 3b_en.srt 9.9 KB
016 Polynomial Regression in R - Step 3c.mp4 16.2 MB
016 Polynomial Regression in R - Step 3c_en.srt 10.3 KB
017 Polynomial Regression in R - Step 4a.mp4 15.0 MB
017 Polynomial Regression in R - Step 4a_en.srt 6.7 KB
018 Polynomial Regression in R - Step 4b.mp4 14.3 MB
018 Polynomial Regression in R - Step 4b_en.srt 7.5 KB
019 R Regression Template - Step 1.mp4 20.6 MB
019 R Regression Template - Step 1_en.srt 11.0 KB
020 R Regression Template - Step 2.mp4 13.6 MB
020 R Regression Template - Step 2_en.srt 9.6 KB
001 SVR Intuition (Updated!).mp4 36.8 MB
001 SVR Intuition (Updated!)_en.srt 14.7 KB
002 Heads-up on non-linear SVR.mp4 19.8 MB
002 Heads-up on non-linear SVR_en.srt 7.3 KB
003 SVR in Python - Step 1a.mp4 12.1 MB
003 SVR in Python - Step 1a_en.srt 10.6 KB
004 SVR in Python - Step 1b.mp4 9.5 MB
004 SVR in Python - Step 1b_en.srt 7.0 KB
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008 SVR in Python - Step 3_en.srt 12.4 KB
009 SVR in Python - Step 4.mp4 10.9 MB
009 SVR in Python - Step 4_en.srt 6.7 KB
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010 SVR in Python - Step 5a_en.srt 6.7 KB
011 SVR in Python - Step 5b.mp4 24.7 MB
011 SVR in Python - Step 5b_en.srt 7.0 KB
012 SVR in R - Step 1.mp4 17.2 MB
012 SVR in R - Step 1_en.srt 10.3 KB
013 SVR in R - Step 2.mp4 13.4 MB
013 SVR in R - Step 2_en.srt 9.5 KB
001 Decision Tree Regression Intuition.mp4 23.2 MB
001 Decision Tree Regression Intuition_en.srt 16.4 KB
002 Decision Tree Regression in Python - Step 1a.mp4 9.3 MB
002 Decision Tree Regression in Python - Step 1a_en.srt 8.6 KB
003 Decision Tree Regression in Python - Step 1b.mp4 11.1 MB
003 Decision Tree Regression in Python - Step 1b_en.srt 7.3 KB
004 Decision Tree Regression in Python - Step 2.mp4 12.2 MB
004 Decision Tree Regression in Python - Step 2_en.srt 9.8 KB
005 Decision Tree Regression in Python - Step 3.mp4 8.4 MB
005 Decision Tree Regression in Python - Step 3_en.srt 6.2 KB
006 Decision Tree Regression in Python - Step 4.mp4 11.7 MB
006 Decision Tree Regression in Python - Step 4_en.srt 9.0 KB
007 Decision Tree Regression in R - Step 1.mp4 16.7 MB
007 Decision Tree Regression in R - Step 1_en.srt 9.2 KB
008 Decision Tree Regression in R - Step 2.mp4 64.4 MB
008 Decision Tree Regression in R - Step 2_en.srt 10.4 KB
009 Decision Tree Regression in R - Step 3.mp4 10.3 MB
009 Decision Tree Regression in R - Step 3_en.srt 9.3 KB
010 Decision Tree Regression in R - Step 4.mp4 11.7 MB
010 Decision Tree Regression in R - Step 4_en.srt 6.8 KB
001 Random Forest Regression Intuition.mp4 35.8 MB
001 Random Forest Regression Intuition_en.srt 9.9 KB
002 Random Forest Regression in Python - Step 1.mp4 17.5 MB
002 Random Forest Regression in Python - Step 1_en.srt 11.0 KB
003 Random Forest Regression in Python - Step 2.mp4 29.2 MB
003 Random Forest Regression in Python - Step 2_en.srt 10.7 KB
004 Random Forest Regression in R - Step 1.mp4 20.1 MB
004 Random Forest Regression in R - Step 1_en.srt 11.1 KB
005 Random Forest Regression in R - Step 2.mp4 21.6 MB
005 Random Forest Regression in R - Step 2_en.srt 11.4 KB
006 Random Forest Regression in R - Step 3.mp4 16.7 MB
006 Random Forest Regression in R - Step 3_en.srt 10.6 KB
001 R-Squared Intuition.mp4 16.5 MB
001 R-Squared Intuition_en.srt 8.1 KB
002 Adjusted R-Squared Intuition.mp4 11.6 MB
002 Adjusted R-Squared Intuition_en.srt 9.1 KB
001 Machine-Learning-A-Z-Model-Selection.zip 161.9 KB
001 Make sure you have this Model Selection folder ready.html 973 bytes
002 Preparation of the Regression Code Templates - Step 1.mp4 10.4 MB
002 Preparation of the Regression Code Templates - Step 1_en.srt 8.5 KB
003 Preparation of the Regression Code Templates - Step 2.mp4 21.9 MB
003 Preparation of the Regression Code Templates - Step 2_en.srt 11.0 KB
004 Preparation of the Regression Code Templates - Step 3.mp4 13.7 MB
004 Preparation of the Regression Code Templates - Step 3_en.srt 8.1 KB
005 Preparation of the Regression Code Templates - Step 4.mp4 24.9 MB
005 Preparation of the Regression Code Templates - Step 4_en.srt 7.5 KB
006 THE ULTIMATE DEMO OF THE POWERFUL REGRESSION CODE TEMPLATES IN ACTION! - STEP 1.mp4 22.7 MB
006 THE ULTIMATE DEMO OF THE POWERFUL REGRESSION CODE TEMPLATES IN ACTION! - STEP 1_en.srt 8.3 KB
007 THE ULTIMATE DEMO OF THE POWERFUL REGRESSION CODE TEMPLATES IN ACTION! - STEP 2.mp4 28.8 MB
007 THE ULTIMATE DEMO OF THE POWERFUL REGRESSION CODE TEMPLATES IN ACTION! - STEP 2_en.srt 7.8 KB
008 Conclusion of Part 2 - Regression.html 1.7 KB
008 Regression-Bonus.zip 364.5 KB
001 Evaluating Regression Models Performance - Homework's Final Part.mp4 27.7 MB
001 Evaluating Regression Models Performance - Homework's Final Part_en.srt 12.4 KB
002 Interpreting Linear Regression Coefficients.mp4 52.6 MB
002 Interpreting Linear Regression Coefficients_en.srt 12.9 KB
003 Conclusion of Part 2 - Regression.html 1.7 KB
003 Regression-Bonus.zip 364.5 KB
001 Welcome to Part 3 - Classification.html 887 bytes
[CourseClub.Me].url 122 bytes
[FreeCourseSite.com].url 127 bytes
[GigaCourse.Com].url 49 bytes
001 What is Classification.mp4 5.6 MB
001 What is Classification_en.srt 4.6 KB
002 Logistic Regression Intuition.mp4 24.8 MB
002 Logistic Regression Intuition_en.srt 8.7 KB
003 Maximum Likelihood.mp4 7.1 MB
003 Maximum Likelihood_en.srt 6.8 KB
004 Logistic Regression in Python - Step 1a.mp4 11.9 MB
004 Logistic Regression in Python - Step 1a_en.srt 10.2 KB
005 Logistic Regression in Python - Step 1b.mp4 9.3 MB
005 Logistic Regression in Python - Step 1b_en.srt 8.0 KB
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012 Logistic Regression in Python - Step 5_en.srt 11.0 KB
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013 Logistic Regression in Python - Step 6a_en.srt 11.1 KB
014 Logistic Regression in Python - Step 6b.mp4 12.1 MB
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015 Logistic Regression in Python - Step 7a_en.srt 10.1 KB
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016 Logistic Regression in Python - Step 7b_en.srt 6.8 KB
017 Logistic Regression in Python - Step 7c.mp4 20.2 MB
017 Logistic Regression in Python - Step 7c_en.srt 5.8 KB
018 Logistic Regression in Python - Step 7 (Colour-blind friendly image).html 706 bytes
019 Logistic Regression in R - Step 1.mp4 19.2 MB
019 Logistic Regression in R - Step 1_en.srt 8.6 KB
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023 Warning - Update.html 1.8 KB
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026 Logistic Regression in R - Step 5c.mp4 37.4 MB
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027 Logistic Regression in R - Step 5 (Colour-blind friendly image).html 706 bytes
028 R Classification Template.mp4 25.5 MB
028 R Classification Template_en.srt 11.1 KB
029 Machine Learning Regression and Classification BONUS.html 807 bytes
030 EXTRA CONTENT Logistic Regression Practical Case Study.html 619 bytes
001 K-Nearest Neighbor Intuition.mp4 10.5 MB
001 K-Nearest Neighbor Intuition_en.srt 7.7 KB
002 K-NN in Python - Step 1.mp4 35.0 MB
002 K-NN in Python - Step 1_en.srt 10.7 KB
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001 SVM Intuition.mp4 20.1 MB
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001 Bayes Theorem.mp4 145.6 MB
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002 Naive Bayes Intuition.mp4 57.4 MB
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001 Machine-Learning-A-Z-Model-Selection.zip 160.0 KB
001 Make sure you have this Model Selection folder ready.html 985 bytes
002 Confusion Matrix & Accuracy Ratios.mp4 28.7 MB
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003 ULTIMATE DEMO OF THE POWERFUL CLASSIFICATION CODE TEMPLATES IN ACTION - STEP 1.mp4 21.0 MB
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001 False Positives & False Negatives.mp4 19.7 MB
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002 Accuracy Paradox.mp4 4.2 MB
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003 CAP Curve.mp4 19.0 MB
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004 CAP Curve Analysis.mp4 14.4 MB
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005 Classification-Pros-Cons.pdf 29.3 KB
005 Conclusion of Part 3 - Classification.html 3.3 KB
001 Welcome to Part 4 - Clustering.html 789 bytes
001 What is Clustering (Supervised vs Unsupervised Learning).mp4 15.4 MB
001 What is Clustering (Supervised vs Unsupervised Learning)_en.srt 6.5 KB
002 K-Means Clustering Intuition.mp4 4.1 MB
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003 The Elbow Method.mp4 7.5 MB
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016 K-Means Clustering in R - Step 1.mp4 15.1 MB
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017 K-Means Clustering in R - Step 2.mp4 27.7 MB
017 K-Means Clustering in R - Step 2_en.srt 11.2 KB
001 Hierarchical Clustering Intuition.mp4 36.2 MB
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002 Hierarchical Clustering How Dendrograms Work.mp4 16.4 MB
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003 Hierarchical Clustering Using Dendrograms.mp4 25.2 MB
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004 Hierarchical Clustering in Python - Step 1.mp4 20.4 MB
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014 Hierarchical Clustering in R - Step 5.mp4 13.8 MB
014 Hierarchical Clustering in R - Step 5_en.srt 3.9 KB
015 Clustering-Pros-Cons.pdf 25.8 KB
015 Conclusion of Part 4 - Clustering.html 502 bytes
001 Welcome to Part 5 - Association Rule Learning.html 477 bytes
001 Apriori Intuition.mp4 56.2 MB
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002 Apriori in Python - Step 1.mp4 58.3 MB
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003 Apriori in Python - Step 2.mp4 82.3 MB
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005 Apriori in Python - Step 4.mp4 116.7 MB
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006 Apriori in R - Step 1.mp4 73.9 MB
006 Apriori in R - Step 1_en.srt 29.9 KB
007 Apriori in R - Step 2.mp4 96.6 MB
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008 Apriori in R - Step 3.mp4 161.7 MB
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001 Eclat Intuition.mp4 24.3 MB
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003 Eclat in R.mp4 65.3 MB
003 Eclat in R_en.srt 15.2 KB
003 Eclat.zip 48.5 KB
001 Welcome to Part 6 - Reinforcement Learning.html 1.5 KB
001 The Multi-Armed Bandit Problem.mp4 96.4 MB
001 The Multi-Armed Bandit Problem_en.srt 27.2 KB
002 Upper Confidence Bound (UCB) Intuition.mp4 79.2 MB
002 Upper Confidence Bound (UCB) Intuition_en.srt 26.9 KB
003 Upper Confidence Bound in Python - Step 1.mp4 44.7 MB
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004 Upper Confidence Bound in Python - Step 2.mp4 9.0 MB
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010 Upper Confidence Bound in R - Step 1.mp4 34.0 MB
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011 Upper Confidence Bound in R - Step 2.mp4 76.2 MB
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012 Upper Confidence Bound in R - Step 3.mp4 99.0 MB
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001 Thompson Sampling Intuition.mp4 48.7 MB
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002 Algorithm Comparison UCB vs Thompson Sampling.mp4 17.2 MB
002 Algorithm Comparison UCB vs Thompson Sampling_en.srt 14.0 KB
003 Thompson Sampling in Python - Step 1.mp4 12.9 MB
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006 Thompson Sampling in Python - Step 4.mp4 20.7 MB
006 Thompson Sampling in Python - Step 4_en.srt 13.1 KB
007 Additional Resource for this Section.html 2.2 KB
008 Thompson Sampling in R - Step 1.mp4 59.3 MB
008 Thompson Sampling in R - Step 1_en.srt 34.5 KB
009 Thompson Sampling in R - Step 2.mp4 9.7 MB
009 Thompson Sampling in R - Step 2_en.srt 6.3 KB
001 Welcome to Part 7 - Natural Language Processing.html 1.7 KB
002 NLP Intuition.mp4 5.2 MB
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003 Types of Natural Language Processing.mp4 8.1 MB
003 Types of Natural Language Processing_en.srt 6.9 KB
004 Classical vs Deep Learning Models.mp4 84.0 MB
004 Classical vs Deep Learning Models_en.srt 19.4 KB
005 Bag-Of-Words Model.mp4 38.0 MB
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006 Natural Language Processing in Python - Step 1.mp4 14.9 MB
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010 Natural Language Processing in Python - Step 5.mp4 82.5 MB
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011 Natural Language Processing in Python - Step 6.mp4 45.1 MB
011 Natural Language Processing in Python - Step 6_en.srt 18.7 KB
012 Natural Language Processing in Python - BONUS.html 1.1 KB
013 Homework Challenge.html 1.4 KB
014 Natural Language Processing in R - Step 1.mp4 50.5 MB
014 Natural Language Processing in R - Step 1_en.srt 29.4 KB
015 Warning - Update.html 760 bytes
016 Natural Language Processing in R - Step 2.mp4 23.8 MB
016 Natural Language Processing in R - Step 2_en.srt 17.4 KB
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024 Natural Language Processing in R - Step 10.mp4 66.5 MB
024 Natural Language Processing in R - Step 10_en.srt 31.8 KB
025 Homework Challenge.html 1.5 KB
001 Welcome to Part 8 - Deep Learning.html 874 bytes
002 What is Deep Learning.mp4 102.9 MB
002 What is Deep Learning_en.srt 24.3 KB
001 Plan of attack.mp4 4.8 MB
001 Plan of attack_en.srt 5.0 KB
002 The Neuron.mp4 44.1 MB
002 The Neuron_en.srt 31.2 KB
003 The Activation Function.mp4 17.3 MB
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004 How do Neural Networks work.mp4 67.2 MB
004 How do Neural Networks work_en.srt 24.6 KB
005 How do Neural Networks learn.mp4 43.3 MB
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006 Gradient Descent.mp4 25.7 MB
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007 Stochastic Gradient Descent.mp4 26.8 MB
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008 Backpropagation.mp4 14.0 MB
008 Backpropagation_en.srt 9.8 KB
009 Business Problem Description.mp4 43.7 MB
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010 ANN in Python - Step 1.mp4 50.8 MB
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011 ANN in Python - Step 2.mp4 84.5 MB
011 ANN in Python - Step 2_en.srt 34.1 KB
012 ANN in Python - Step 3.mp4 38.6 MB
012 ANN in Python - Step 3_en.srt 26.9 KB
013 ANN in Python - Step 4.mp4 31.9 MB
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014 ANN in Python - Step 5.mp4 75.2 MB
014 ANN in Python - Step 5_en.srt 30.1 KB
015 ANN in R - Step 1.mp4 132.7 MB
015 ANN in R - Step 1_en.srt 32.5 KB
016 ANN in R - Step 2.mp4 25.0 MB
016 ANN in R - Step 2_en.srt 12.4 KB
017 ANN in R - Step 3.mp4 115.7 MB
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018 ANN in R - Step 4 (Last step).mp4 54.6 MB
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019 Deep Learning Additional Content.html 1005 bytes
020 EXTRA CONTENT ANN Case Study.html 544 bytes
001 Plan of attack.mp4 6.2 MB
001 Plan of attack_en.srt 7.0 KB
001 dataset.zip 221.3 MB
002 What are convolutional neural networks.mp4 71.1 MB
002 What are convolutional neural networks_en.srt 28.7 KB
003 Step 1 - Convolution Operation.mp4 65.6 MB
003 Step 1 - Convolution Operation_en.srt 29.4 KB
004 Step 1(b) - ReLU Layer.mp4 20.6 MB
004 Step 1(b) - ReLU Layer_en.srt 11.3 KB
005 Step 2 - Pooling.mp4 87.5 MB
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006 Step 3 - Flattening.mp4 3.1 MB
006 Step 3 - Flattening_en.srt 3.6 KB
007 Step 4 - Full Connection.mp4 58.6 MB
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008 Summary.mp4 10.8 MB
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009 Softmax & Cross-Entropy.mp4 42.1 MB
009 Softmax & Cross-Entropy_en.srt 37.1 KB
010 CNN in Python - Step 1.mp4 31.8 MB
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015 CNN in Python - FINAL DEMO!.mp4 112.1 MB
015 CNN in Python - FINAL DEMO!_en.srt 38.6 KB
016 Deep Learning Additional Content #2.html 923 bytes
001 Welcome to Part 9 - Dimensionality Reduction.html 1.3 KB
001 Principal Component Analysis (PCA) Intuition.mp4 21.0 MB
001 Principal Component Analysis (PCA) Intuition_en.srt 6.4 KB
002 PCA in Python - Step 1.mp4 86.0 MB
002 PCA in Python - Step 1_en.srt 30.1 KB
003 PCA in Python - Step 2.mp4 20.7 MB
003 PCA in Python - Step 2_en.srt 10.4 KB
004 PCA in R - Step 1.mp4 100.6 MB
004 PCA in R - Step 1_en.srt 23.9 KB
005 PCA in R - Step 2.mp4 46.5 MB
005 PCA in R - Step 2_en.srt 21.0 KB
006 PCA in R - Step 3.mp4 65.3 MB
006 PCA in R - Step 3_en.srt 24.3 KB
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001 Linear Discriminant Analysis (LDA) Intuition.mp4 15.1 MB
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002 LDA in Python.mp4 75.4 MB
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003 LDA in R.mp4 93.7 MB
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001 Kernel PCA in Python.mp4 56.9 MB
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002 Kernel PCA in R.mp4 228.8 MB
002 Kernel PCA in R_en.srt 37.3 KB
001 Welcome to Part 10 - Model Selection & Boosting.html 921 bytes
001 k-Fold Cross Validation in Python.mp4 62.0 MB
001 k-Fold Cross Validation in Python_en.srt 32.6 KB
002 Grid Search in Python.mp4 114.4 MB
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003 k-Fold Cross Validation in R.mp4 53.3 MB
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004 Grid Search in R.mp4 50.0 MB
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001 XGBoost in Python.mp4 84.3 MB
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002 Model Selection and Boosting Additional Content.html 1.1 KB
003 XGBoost in R.mp4 69.4 MB
003 XGBoost in R_en.srt 31.1 KB
001 OUR SPECIAL OFFER.html 4.5 KB
001 Logistic Regression Intuition.mp4 32.5 MB
001 Logistic Regression Intuition_en.srt 31.5 KB

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