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[GigaCourse.Com] Udemy - Machine Learning A-Z™ AI, Python & R + ChatGPT Bonus [2023]
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[GigaCourse.Com] Udemy - Machine Learning A-Z™ AI, Python & R + ChatGPT Bonus [2023]
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文件列表
41 - Kernel PCA/002 Kernel PCA in R.mp4
239.9 MB
37 - Convolutional Neural Networks/001 dataset.zip
232.0 MB
29 - Apriori/008 Apriori in R - Step 3.mp4
169.5 MB
20 - Naive Bayes/001 Bayes Theorem.mp4
152.7 MB
36 - Artificial Neural Networks/015 ANN in R - Step 1.mp4
139.2 MB
29 - Apriori/005 Apriori in Python - Step 4.mp4
122.4 MB
36 - Artificial Neural Networks/017 ANN in R - Step 3.mp4
121.3 MB
43 - Model Selection/002 Grid Search in Python.mp4
120.0 MB
37 - Convolutional Neural Networks/015 CNN in Python - FINAL DEMO!.mp4
117.5 MB
35 - -------------------- Part 8 Deep Learning --------------------/002 What is Deep Learning.mp4
107.9 MB
39 - Principal Component Analysis (PCA)/004 PCA in R - Step 1.mp4
105.5 MB
37 - Convolutional Neural Networks/011 CNN in Python - Step 2.mp4
104.9 MB
32 - Upper Confidence Bound (UCB)/012 Upper Confidence Bound in R - Step 3.mp4
103.8 MB
29 - Apriori/007 Apriori in R - Step 2.mp4
101.3 MB
32 - Upper Confidence Bound (UCB)/001 The Multi-Armed Bandit Problem.mp4
101.1 MB
40 - Linear Discriminant Analysis (LDA)/003 LDA in R.mp4
98.2 MB
37 - Convolutional Neural Networks/005 Step 2 - Pooling.mp4
91.7 MB
39 - Principal Component Analysis (PCA)/002 PCA in Python - Step 1.mp4
90.2 MB
37 - Convolutional Neural Networks/014 CNN in Python - Step 5.mp4
89.0 MB
36 - Artificial Neural Networks/011 ANN in Python - Step 2.mp4
88.6 MB
44 - XGBoost/001 XGBoost in Python.mp4
88.3 MB
34 - -------------------- Part 7 Natural Language Processing --------------------/004 Classical vs Deep Learning Models.mp4
88.0 MB
34 - -------------------- Part 7 Natural Language Processing --------------------/010 Natural Language Processing in Python - Step 5.mp4
86.5 MB
29 - Apriori/003 Apriori in Python - Step 2.mp4
86.2 MB
32 - Upper Confidence Bound (UCB)/002 Upper Confidence Bound (UCB) Intuition.mp4
83.1 MB
32 - Upper Confidence Bound (UCB)/011 Upper Confidence Bound in R - Step 2.mp4
79.9 MB
40 - Linear Discriminant Analysis (LDA)/002 LDA in Python.mp4
79.1 MB
36 - Artificial Neural Networks/014 ANN in Python - Step 5.mp4
78.9 MB
29 - Apriori/006 Apriori in R - Step 1.mp4
77.5 MB
37 - Convolutional Neural Networks/002 What are convolutional neural networks.mp4
74.5 MB
44 - XGBoost/003 XGBoost in R.mp4
72.7 MB
36 - Artificial Neural Networks/004 How do Neural Networks work.mp4
70.5 MB
34 - -------------------- Part 7 Natural Language Processing --------------------/024 Natural Language Processing in R - Step 10.mp4
69.7 MB
37 - Convolutional Neural Networks/003 Step 1 - Convolution Operation.mp4
68.8 MB
39 - Principal Component Analysis (PCA)/006 PCA in R - Step 3.mp4
68.5 MB
30 - Eclat/003 Eclat in R.mp4
68.5 MB
07 - Multiple Linear Regression/023 Multiple Linear Regression in R - Backward Elimination - HOMEWORK !.mp4
67.7 MB
10 - Decision Tree Regression/008 Decision Tree Regression in R - Step 2.mp4
67.5 MB
37 - Convolutional Neural Networks/012 CNN in Python - Step 3.mp4
67.4 MB
04 - Data Preprocessing in R/005 Encoding Categorical Data.mp4
67.0 MB
43 - Model Selection/001 k-Fold Cross Validation in Python.mp4
65.1 MB
33 - Thompson Sampling/008 Thompson Sampling in R - Step 1.mp4
62.2 MB
37 - Convolutional Neural Networks/007 Step 4 - Full Connection.mp4
61.4 MB
29 - Apriori/002 Apriori in Python - Step 1.mp4
61.2 MB
21 - Decision Tree Classification/004 Decision Tree Classification in R - Step 1.mp4
60.6 MB
20 - Naive Bayes/002 Naive Bayes Intuition.mp4
60.2 MB
41 - Kernel PCA/001 Kernel PCA in Python.mp4
59.7 MB
30 - Eclat/002 Eclat in Python.mp4
58.9 MB
29 - Apriori/001 Apriori Intuition.mp4
58.9 MB
19 - Kernel SVM/008 Kernel SVM in R - Step 1.mp4
58.0 MB
36 - Artificial Neural Networks/018 ANN in R - Step 4 (Last step).mp4
57.2 MB
43 - Model Selection/003 k-Fold Cross Validation in R.mp4
55.9 MB
14 - Regression Model Selection in R/002 Interpreting Linear Regression Coefficients.mp4
55.2 MB
20 - Naive Bayes/005 Naive Bayes in Python - Step 1.mp4
55.1 MB
18 - Support Vector Machine (SVM)/005 SVM in R - Step 1.mp4
54.4 MB
18 - Support Vector Machine (SVM)/002 SVM in Python - Step 1.mp4
54.0 MB
36 - Artificial Neural Networks/010 ANN in Python - Step 1.mp4
53.3 MB
01 - Welcome to the course! Here we will help you get started in the best conditions/002 Machine Learning Demo - Get Excited!.mp4
53.2 MB
34 - -------------------- Part 7 Natural Language Processing --------------------/014 Natural Language Processing in R - Step 1.mp4
53.0 MB
43 - Model Selection/004 Grid Search in R.mp4
52.5 MB
33 - Thompson Sampling/001 Thompson Sampling Intuition.mp4
51.1 MB
39 - Principal Component Analysis (PCA)/005 PCA in R - Step 2.mp4
48.8 MB
34 - -------------------- Part 7 Natural Language Processing --------------------/011 Natural Language Processing in Python - Step 6.mp4
47.3 MB
32 - Upper Confidence Bound (UCB)/003 Upper Confidence Bound in Python - Step 1.mp4
46.8 MB
36 - Artificial Neural Networks/002 The Neuron.mp4
46.2 MB
22 - Random Forest Classification/006 Random Forest Classification in R - Step 3.mp4
46.1 MB
36 - Artificial Neural Networks/009 Business Problem Description.mp4
45.8 MB
36 - Artificial Neural Networks/005 How do Neural Networks learn.mp4
45.4 MB
21 - Decision Tree Classification/005 Decision Tree Classification in R - Step 2.mp4
44.9 MB
18 - Support Vector Machine (SVM)/006 SVM in R - Step 2.mp4
44.7 MB
37 - Convolutional Neural Networks/009 Softmax & Cross-Entropy.mp4
44.2 MB
20 - Naive Bayes/006 Naive Bayes in Python - Step 2.mp4
44.1 MB
32 - Upper Confidence Bound (UCB)/006 Upper Confidence Bound in Python - Step 4.mp4
43.7 MB
22 - Random Forest Classification/001 Random Forest Classification Intuition.mp4
43.6 MB
17 - K-Nearest Neighbors (K-NN)/005 K-NN in R - Step 1.mp4
42.5 MB
33 - Thompson Sampling/005 Thompson Sampling in Python - Step 3.mp4
42.2 MB
29 - Apriori/004 Apriori in Python - Step 3.mp4
41.4 MB
34 - -------------------- Part 7 Natural Language Processing --------------------/023 Natural Language Processing in R - Step 9.mp4
41.2 MB
22 - Random Forest Classification/005 Random Forest Classification in R - Step 2.mp4
40.9 MB
07 - Multiple Linear Regression/014 Multiple Linear Regression in Python - Step 4a.mp4
40.9 MB
36 - Artificial Neural Networks/012 ANN in Python - Step 3.mp4
40.4 MB
07 - Multiple Linear Regression/011 Multiple Linear Regression in Python - Step 2b.mp4
39.9 MB
34 - -------------------- Part 7 Natural Language Processing --------------------/005 Bag-Of-Words Model.mp4
39.8 MB
21 - Decision Tree Classification/002 Decision Tree Classification in Python - Step 1.mp4
39.7 MB
18 - Support Vector Machine (SVM)/003 SVM in Python - Step 2.mp4
39.5 MB
19 - Kernel SVM/010 Kernel SVM in R - Step 3.mp4
39.2 MB
16 - Logistic Regression/026 Logistic Regression in R - Step 5c.mp4
39.2 MB
19 - Kernel SVM/006 Kernel SVM in Python - Step 1.mp4
38.7 MB
09 - Support Vector Regression (SVR)/001 SVR Intuition (Updated!).mp4
38.6 MB
04 - Data Preprocessing in R/009 Feature Scaling - Step 2.mp4
38.1 MB
27 - Hierarchical Clustering/001 Hierarchical Clustering Intuition.mp4
38.0 MB
17 - K-Nearest Neighbors (K-NN)/007 K-NN in R - Step 3.mp4
37.5 MB
11 - Random Forest Regression/001 Random Forest Regression Intuition.mp4
37.5 MB
26 - K-Means Clustering/014 K-Means Clustering in Python - Step 5b.mp4
37.4 MB
19 - Kernel SVM/007 Kernel SVM in Python - Step 2.mp4
37.2 MB
34 - -------------------- Part 7 Natural Language Processing --------------------/009 Natural Language Processing in Python - Step 4.mp4
37.0 MB
03 - Data Preprocessing in Python/002 Getting Started - Step 2.mp4
36.8 MB
17 - K-Nearest Neighbors (K-NN)/002 K-NN in Python - Step 1.mp4
36.7 MB
22 - Random Forest Classification/002 Random Forest Classification in Python - Step 1.mp4
36.6 MB
34 - -------------------- Part 7 Natural Language Processing --------------------/007 Natural Language Processing in Python - Step 2.mp4
36.5 MB
17 - K-Nearest Neighbors (K-NN)/004 K-NN in Python - Step 3.mp4
36.0 MB
33 - Thompson Sampling/004 Thompson Sampling in Python - Step 2.mp4
35.9 MB
32 - Upper Confidence Bound (UCB)/010 Upper Confidence Bound in R - Step 1.mp4
35.6 MB
21 - Decision Tree Classification/003 Decision Tree Classification in Python - Step 2.mp4
35.3 MB
01 - Welcome to the course! Here we will help you get started in the best conditions/005 Installing R and R Studio (Mac, Linux & Windows).mp4
35.2 MB
17 - K-Nearest Neighbors (K-NN)/003 K-NN in Python - Step 2.mp4
35.2 MB
19 - Kernel SVM/003 The Kernel Trick.mp4
35.2 MB
07 - Multiple Linear Regression/007 Multiple Linear Regression Intuition - Step 5.mp4
35.0 MB
23 - Classification Model Selection in Python/004 ULTIMATE DEMO OF THE POWERFUL CLASSIFICATION CODE TEMPLATES IN ACTION - STEP 2.mp4
34.6 MB
22 - Random Forest Classification/003 Random Forest Classification in Python - Step 2.mp4
34.4 MB
16 - Logistic Regression/007 Logistic Regression in Python - Step 2b.mp4
34.4 MB
16 - Logistic Regression/022 Logistic Regression in R - Step 4.mp4
34.2 MB
07 - Multiple Linear Regression/024 Multiple Linear Regression in R - Backward Elimination - Homework Solution.mp4
34.0 MB
46 - Annex Logistic Regression (Long Explanation)/001 Logistic Regression Intuition.mp4
34.0 MB
36 - Artificial Neural Networks/013 ANN in Python - Step 4.mp4
33.4 MB
19 - Kernel SVM/002 Mapping to a higher dimension.mp4
33.4 MB
37 - Convolutional Neural Networks/010 CNN in Python - Step 1.mp4
33.4 MB
27 - Hierarchical Clustering/012 Hierarchical Clustering in R - Step 3.mp4
32.9 MB
03 - Data Preprocessing in Python/009 Taking care of Missing Data - Step 2.mp4
30.9 MB
11 - Random Forest Regression/003 Random Forest Regression in Python - Step 2.mp4
30.6 MB
16 - Logistic Regression/006 Logistic Regression in Python - Step 2a.mp4
30.5 MB
06 - Simple Linear Regression/014 Simple Linear Regression in R - Step 4a.mp4
30.4 MB
13 - Regression Model Selection in Python/007 THE ULTIMATE DEMO OF THE POWERFUL REGRESSION CODE TEMPLATES IN ACTION! - STEP 2.mp4
30.2 MB
23 - Classification Model Selection in Python/002 Confusion Matrix & Accuracy Ratios.mp4
30.1 MB
16 - Logistic Regression/024 Logistic Regression in R - Step 5a.mp4
30.0 MB
07 - Multiple Linear Regression/010 Multiple Linear Regression in Python - Step 2a.mp4
29.9 MB
34 - -------------------- Part 7 Natural Language Processing --------------------/008 Natural Language Processing in Python - Step 3.mp4
29.6 MB
14 - Regression Model Selection in R/001 Evaluating Regression Models Performance - Homework's Final Part.mp4
29.1 MB
26 - K-Means Clustering/017 K-Means Clustering in R - Step 2.mp4
29.0 MB
19 - Kernel SVM/005 Non-Linear Kernel SVR (Advanced).mp4
28.8 MB
20 - Naive Bayes/010 Naive Bayes in R - Step 3.mp4
28.5 MB
16 - Logistic Regression/021 Logistic Regression in R - Step 3.mp4
28.3 MB
09 - Support Vector Regression (SVR)/008 SVR in Python - Step 3.mp4
28.2 MB
36 - Artificial Neural Networks/007 Stochastic Gradient Descent.mp4
28.1 MB
07 - Multiple Linear Regression/020 Multiple Linear Regression in R - Step 2a.mp4
28.0 MB
26 - K-Means Clustering/015 K-Means Clustering in Python - Step 5c.mp4
28.0 MB
27 - Hierarchical Clustering/007 Hierarchical Clustering in Python - Step 2c.mp4
27.8 MB
36 - Artificial Neural Networks/006 Gradient Descent.mp4
26.9 MB
01 - Welcome to the course! Here we will help you get started in the best conditions/004 How to use the ML A-Z folder & Google Colab.mp4
26.9 MB
16 - Logistic Regression/028 R Classification Template.mp4
26.7 MB
27 - Hierarchical Clustering/003 Hierarchical Clustering Using Dendrograms.mp4
26.4 MB
36 - Artificial Neural Networks/016 ANN in R - Step 2.mp4
26.2 MB
13 - Regression Model Selection in Python/005 Preparation of the Regression Code Templates - Step 4.mp4
26.1 MB
16 - Logistic Regression/002 Logistic Regression Intuition.mp4
26.0 MB
09 - Support Vector Regression (SVR)/011 SVR in Python - Step 5b.mp4
25.9 MB
16 - Logistic Regression/025 Logistic Regression in R - Step 5b.mp4
25.9 MB
07 - Multiple Linear Regression/003 Assumptions of Linear Regression.mp4
25.8 MB
30 - Eclat/001 Eclat Intuition.mp4
25.4 MB
22 - Random Forest Classification/004 Random Forest Classification in R - Step 1.mp4
25.2 MB
16 - Logistic Regression/016 Logistic Regression in Python - Step 7b.mp4
25.2 MB
08 - Polynomial Regression/013 Polynomial Regression in R - Step 2b.mp4
25.0 MB
34 - -------------------- Part 7 Natural Language Processing --------------------/016 Natural Language Processing in R - Step 2.mp4
24.9 MB
10 - Decision Tree Regression/001 Decision Tree Regression Intuition.mp4
24.4 MB
07 - Multiple Linear Regression/006 Understanding the P-Value.mp4
24.3 MB
04 - Data Preprocessing in R/008 Feature Scaling - Step 1.mp4
23.9 MB
13 - Regression Model Selection in Python/006 THE ULTIMATE DEMO OF THE POWERFUL REGRESSION CODE TEMPLATES IN ACTION! - STEP 1.mp4
23.9 MB
20 - Naive Bayes/009 Naive Bayes in R - Step 2.mp4
23.8 MB
37 - Convolutional Neural Networks/013 CNN in Python - Step 4.mp4
23.8 MB
04 - Data Preprocessing in R/010 Data Preprocessing Template.mp4
23.7 MB
27 - Hierarchical Clustering/006 Hierarchical Clustering in Python - Step 2b.mp4
23.4 MB
13 - Regression Model Selection in Python/003 Preparation of the Regression Code Templates - Step 2.mp4
23.0 MB
21 - Decision Tree Classification/006 Decision Tree Classification in R - Step 3.mp4
22.8 MB
23 - Classification Model Selection in Python/005 ULTIMATE DEMO OF THE POWERFUL CLASSIFICATION CODE TEMPLATES IN ACTION - STEP 3.mp4
22.7 MB
11 - Random Forest Regression/005 Random Forest Regression in R - Step 2.mp4
22.7 MB
04 - Data Preprocessing in R/004 Taking care of Missing Data.mp4
22.5 MB
23 - Classification Model Selection in Python/003 ULTIMATE DEMO OF THE POWERFUL CLASSIFICATION CODE TEMPLATES IN ACTION - STEP 1.mp4
22.1 MB
06 - Simple Linear Regression/007 Simple Linear Regression in Python - Step 3.mp4
22.0 MB
39 - Principal Component Analysis (PCA)/001 Principal Component Analysis (PCA) Intuition.mp4
22.0 MB
39 - Principal Component Analysis (PCA)/003 PCA in Python - Step 2.mp4
21.8 MB
08 - Polynomial Regression/014 Polynomial Regression in R - Step 3a.mp4
21.7 MB
33 - Thompson Sampling/006 Thompson Sampling in Python - Step 4.mp4
21.7 MB
06 - Simple Linear Regression/015 Simple Linear Regression in R - Step 4b.mp4
21.7 MB
37 - Convolutional Neural Networks/004 Step 1(b) - ReLU Layer.mp4
21.6 MB
08 - Polynomial Regression/019 R Regression Template - Step 1.mp4
21.6 MB
16 - Logistic Regression/015 Logistic Regression in Python - Step 7a.mp4
21.5 MB
32 - Upper Confidence Bound (UCB)/009 Upper Confidence Bound in Python - Step 7.mp4
21.5 MB
27 - Hierarchical Clustering/004 Hierarchical Clustering in Python - Step 1.mp4
21.4 MB
16 - Logistic Regression/008 Logistic Regression in Python - Step 3a.mp4
21.4 MB
16 - Logistic Regression/017 Logistic Regression in Python - Step 7c.mp4
21.1 MB
18 - Support Vector Machine (SVM)/001 SVM Intuition.mp4
21.1 MB
11 - Random Forest Regression/004 Random Forest Regression in R - Step 1.mp4
21.1 MB
09 - Support Vector Regression (SVR)/002 Heads-up on non-linear SVR.mp4
20.7 MB
08 - Polynomial Regression/003 Polynomial Regression in Python - Step 1b.mp4
20.7 MB
08 - Polynomial Regression/006 Polynomial Regression in Python - Step 3a.mp4
20.7 MB
03 - Data Preprocessing in Python/011 Encoding Categorical Data - Step 2.mp4
20.7 MB
24 - Evaluating Classification Models Performance/001 False Positives & False Negatives.mp4
20.6 MB
04 - Data Preprocessing in R/007 Splitting the dataset into the Training set and Test set - Step 2.mp4
20.6 MB
08 - Polynomial Regression/015 Polynomial Regression in R - Step 3b.mp4
20.5 MB
27 - Hierarchical Clustering/013 Hierarchical Clustering in R - Step 4.mp4
20.3 MB
06 - Simple Linear Regression/009 Simple Linear Regression in Python - Step 4b.mp4
20.3 MB
16 - Logistic Regression/019 Logistic Regression in R - Step 1.mp4
20.2 MB
06 - Simple Linear Regression/012 Simple Linear Regression in R - Step 2.mp4
20.0 MB
32 - Upper Confidence Bound (UCB)/005 Upper Confidence Bound in Python - Step 3.mp4
20.0 MB
32 - Upper Confidence Bound (UCB)/008 Upper Confidence Bound in Python - Step 6.mp4
20.0 MB
07 - Multiple Linear Regression/004 Multiple Linear Regression Intuition - Step 3.mp4
19.9 MB
24 - Evaluating Classification Models Performance/003 CAP Curve.mp4
19.9 MB
07 - Multiple Linear Regression/008 Multiple Linear Regression in Python - Step 1a.mp4
19.8 MB
19 - Kernel SVM/009 Kernel SVM in R - Step 2.mp4
19.7 MB
26 - K-Means Clustering/004 K-Means++.mp4
19.6 MB
34 - -------------------- Part 7 Natural Language Processing --------------------/017 Natural Language Processing in R - Step 3.mp4
19.5 MB
08 - Polynomial Regression/007 Polynomial Regression in Python - Step 3b.mp4
19.2 MB
20 - Naive Bayes/008 Naive Bayes in R - Step 1.mp4
19.2 MB
16 - Logistic Regression/012 Logistic Regression in Python - Step 5.mp4
19.1 MB
08 - Polynomial Regression/005 Polynomial Regression in Python - Step 2b.mp4
18.8 MB
16 - Logistic Regression/010 Logistic Regression in Python - Step 4a.mp4
18.7 MB
17 - K-Nearest Neighbors (K-NN)/006 K-NN in R - Step 2.mp4
18.7 MB
21 - Decision Tree Classification/001 Decision Tree Classification Intuition.mp4
18.6 MB
07 - Multiple Linear Regression/021 Multiple Linear Regression in R - Step 2b.mp4
18.6 MB
06 - Simple Linear Regression/008 Simple Linear Regression in Python - Step 4a.mp4
18.5 MB
11 - Random Forest Regression/002 Random Forest Regression in Python - Step 1.mp4
18.3 MB
34 - -------------------- Part 7 Natural Language Processing --------------------/020 Natural Language Processing in R - Step 6.mp4
18.2 MB
36 - Artificial Neural Networks/003 The Activation Function.mp4
18.1 MB
33 - Thompson Sampling/002 Algorithm Comparison UCB vs Thompson Sampling.mp4
18.1 MB
09 - Support Vector Regression (SVR)/012 SVR in R - Step 1.mp4
18.1 MB
09 - Support Vector Regression (SVR)/005 SVR in Python - Step 2a.mp4
18.0 MB
27 - Hierarchical Clustering/008 Hierarchical Clustering in Python - Step 3a.mp4
17.9 MB
03 - Data Preprocessing in Python/019 Feature Scaling - Step 4.mp4
17.7 MB
08 - Polynomial Regression/010 Polynomial Regression in R - Step 1a.mp4
17.7 MB
32 - Upper Confidence Bound (UCB)/007 Upper Confidence Bound in Python - Step 5.mp4
17.6 MB
11 - Random Forest Regression/006 Random Forest Regression in R - Step 3.mp4
17.5 MB
34 - -------------------- Part 7 Natural Language Processing --------------------/022 Natural Language Processing in R - Step 8.mp4
17.5 MB
10 - Decision Tree Regression/007 Decision Tree Regression in R - Step 1.mp4
17.5 MB
04 - Data Preprocessing in R/006 Splitting the dataset into the Training set and Test set - Step 1.mp4
17.4 MB
12 - Evaluating Regression Models Performance/001 R-Squared Intuition.mp4
17.3 MB
08 - Polynomial Regression/004 Polynomial Regression in Python - Step 2a.mp4
17.3 MB
07 - Multiple Linear Regression/005 Multiple Linear Regression Intuition - Step 4.mp4
17.3 MB
26 - K-Means Clustering/012 K-Means Clustering in Python - Step 4.mp4
17.3 MB
27 - Hierarchical Clustering/002 Hierarchical Clustering How Dendrograms Work.mp4
17.2 MB
08 - Polynomial Regression/016 Polynomial Regression in R - Step 3c.mp4
17.0 MB
20 - Naive Bayes/004 Naive Bayes Intuition (Extras).mp4
16.9 MB
03 - Data Preprocessing in Python/008 Taking care of Missing Data - Step 1.mp4
16.9 MB
26 - K-Means Clustering/006 K-Means Clustering in Python - Step 1b.mp4
16.4 MB
26 - K-Means Clustering/001 What is Clustering (Supervised vs Unsupervised Learning).mp4
16.2 MB
27 - Hierarchical Clustering/009 Hierarchical Clustering in Python - Step 3b.mp4
15.9 MB
26 - K-Means Clustering/016 K-Means Clustering in R - Step 1.mp4
15.9 MB
26 - K-Means Clustering/013 K-Means Clustering in Python - Step 5a.mp4
15.8 MB
40 - Linear Discriminant Analysis (LDA)/001 Linear Discriminant Analysis (LDA) Intuition.mp4
15.8 MB
08 - Polynomial Regression/017 Polynomial Regression in R - Step 4a.mp4
15.7 MB
09 - Support Vector Regression (SVR)/006 SVR in Python - Step 2b.mp4
15.7 MB
34 - -------------------- Part 7 Natural Language Processing --------------------/006 Natural Language Processing in Python - Step 1.mp4
15.6 MB
07 - Multiple Linear Regression/012 Multiple Linear Regression in Python - Step 3a.mp4
15.5 MB
07 - Multiple Linear Regression/019 Multiple Linear Regression in R - Step 1b.mp4
15.4 MB
07 - Multiple Linear Regression/013 Multiple Linear Regression in Python - Step 3b.mp4
15.4 MB
06 - Simple Linear Regression/013 Simple Linear Regression in R - Step 3.mp4
15.3 MB
06 - Simple Linear Regression/004 Simple Linear Regression in Python - Step 1b.mp4
15.2 MB
08 - Polynomial Regression/012 Polynomial Regression in R - Step 2a.mp4
15.2 MB
24 - Evaluating Classification Models Performance/004 CAP Curve Analysis.mp4
15.1 MB
07 - Multiple Linear Regression/022 Multiple Linear Regression in R - Step 3.mp4
15.0 MB
08 - Polynomial Regression/018 Polynomial Regression in R - Step 4b.mp4
14.9 MB
07 - Multiple Linear Regression/015 Multiple Linear Regression in Python - Step 4b.mp4
14.9 MB
03 - Data Preprocessing in Python/012 Encoding Categorical Data - Step 3.mp4
14.8 MB
07 - Multiple Linear Regression/001 Dataset + Business Problem Description.mp4
14.8 MB
02 - -------------------- Part 1 Data Preprocessing --------------------/004 Feature Scaling.mp4
14.7 MB
36 - Artificial Neural Networks/008 Backpropagation.mp4
14.7 MB
03 - Data Preprocessing in Python/006 Importing the Dataset - Step 3.mp4
14.6 MB
27 - Hierarchical Clustering/014 Hierarchical Clustering in R - Step 5.mp4
14.5 MB
16 - Logistic Regression/013 Logistic Regression in Python - Step 6a.mp4
14.4 MB
13 - Regression Model Selection in Python/004 Preparation of the Regression Code Templates - Step 3.mp4
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13 - Regression Model Selection in Python/008 Regression-Bonus.zip
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13 - Regression Model Selection in Python/001 Machine-Learning-A-Z-Model-Selection.zip
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37 - Convolutional Neural Networks/015 CNN in Python - FINAL DEMO!_en.srt
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32 - Upper Confidence Bound (UCB)/010 Upper Confidence Bound in R - Step 1_en.srt
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32 - Upper Confidence Bound (UCB)/003 Upper Confidence Bound in Python - Step 1_en.srt
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01 - Welcome to the course! Here we will help you get started in the best conditions/004 How to use the ML A-Z folder & Google Colab_en.srt
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19 - Kernel SVM/007 Kernel SVM in Python - Step 2_en.srt
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21 - Decision Tree Classification/004 Decision Tree Classification in R - Step 1_en.srt
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01 - Welcome to the course! Here we will help you get started in the best conditions/005 Installing R and R Studio (Mac, Linux & Windows)_en.srt
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