[FreeCourseSite.com] Udemy - Machine Learning A-Z™ Hands-On Python & R In Data Science

Creation Time	Aug. 27, 2023, 6:04 a.m.
Last Access Time	Sept. 8, 2024, 9:19 a.m.
File Size	5.5 GB
Keywords	A-Z™ FreeCourseSite Data Python Hands-On - Science Udemy Machine R Learning In com
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Total Files	538
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36 Kernel PCA/264 Kernel PCA in R.mp4 56.6 MB
12 Logistic Regression/089 Logistic Regression in R - Step 5.mp4 51.7 MB
35 Linear Discriminant Analysis (LDA)/261 LDA in R.mp4 51.3 MB
17 Decision Tree Classification/116 Decision Tree Classification in R.mp4 51.2 MB
18 Random Forest Classification/120 Random Forest Classification in R.mp4 49.4 MB
31 Artificial Neural Networks/217 ANN in Python - Step 2.mp4 48.1 MB
39 XGBoost/275 XGBoost in R.mp4 47.3 MB
27 Upper Confidence Bound (UCB)/171 Upper Confidence Bound in R - Step 3.mp4 47.2 MB
18 Random Forest Classification/119 Random Forest Classification in Python.mp4 47.2 MB
32 Convolutional Neural Networks/248 CNN in Python - Step 9.mp4 46.9 MB
07 Support Vector Regression (SVR)/061 SVR in Python.mp4 46.2 MB
35 Linear Discriminant Analysis (LDA)/260 LDA in Python.mp4 45.4 MB
08 Decision Tree Regression/066 Decision Tree Regression in R.mp4 44.4 MB
16 Naive Bayes/106 Bayes Theorem.mp4 43.9 MB
24 Apriori/154 Apriori in R - Step 3.mp4 43.8 MB
38 Model Selection/268 k-Fold Cross Validation in R.mp4 43.6 MB
06 Polynomial Regression/057 Polynomial Regression in R - Step 3.mp4 43.3 MB
28 Thompson Sampling/176 Thompson Sampling in Python - Step 1.mp4 43.1 MB
06 Polynomial Regression/052 Polynomial Regression in Python - Step 3.mp4 43.0 MB
24 Apriori/152 Apriori in R - Step 1.mp4 42.9 MB
32 Convolutional Neural Networks/236 Step 4 - Full Connection.mp4 42.7 MB
12 Logistic Regression/083 Logistic Regression in Python - Step 5.mp4 42.5 MB
15 Kernel SVM/104 Kernel SVM in Python.mp4 41.6 MB
13 K-Nearest Neighbors (K-NN)/094 K-NN in R.mp4 41.4 MB
29 -------------------- Part 7_ Natural Language Processing --------------------/202 Natural Language Processing in R - Step 10.mp4 41.2 MB
27 Upper Confidence Bound (UCB)/167 Upper Confidence Bound in Python - Step 3.mp4 41.1 MB
28 Thompson Sampling/178 Thompson Sampling in R - Step 1.mp4 40.9 MB
02 -------------------- Part 1_ Data Preprocessing --------------------/013 Categorical Data.mp4 40.8 MB
15 Kernel SVM/105 Kernel SVM in R.mp4 40.5 MB
29 -------------------- Part 7_ Natural Language Processing --------------------/193 Natural Language Processing in R - Step 1.mp4 40.4 MB
09 Random Forest Regression/070 Random Forest Regression in R.mp4 40.3 MB
32 Convolutional Neural Networks/234 Step 2 - Pooling.mp4 40.2 MB
21 K-Means Clustering/132 K-Means Clustering in Python.mp4 39.8 MB
05 Multiple Linear Regression/046 Multiple Linear Regression in R - Backward Elimination - HOMEWORK !.mp4 39.7 MB
05 Multiple Linear Regression/037 Multiple Linear Regression in Python - Step 1.mp4 39.6 MB
29 -------------------- Part 7_ Natural Language Processing --------------------/189 Natural Language Processing in Python - Step 8.mp4 39.5 MB
09 Random Forest Regression/069 Random Forest Regression in Python.mp4 39.5 MB
02 -------------------- Part 1_ Data Preprocessing --------------------/014 Splitting the Dataset into the Training set and Test set.mp4 39.0 MB
31 Artificial Neural Networks/226 ANN in R - Step 1.mp4 38.6 MB
38 Model Selection/269 Grid Search in Python - Step 1.mp4 38.2 MB
24 Apriori/155 Apriori in Python - Step 1.mp4 38.0 MB
04 Simple Linear Regression/029 Simple Linear Regression in R - Step 4.mp4 37.4 MB
16 Naive Bayes/112 Naive Bayes in R.mp4 37.3 MB
28 Thompson Sampling/173 Thompson Sampling Intuition.mp4 37.3 MB
34 Principal Component Analysis (PCA)/258 PCA in R - Step 3.mp4 36.7 MB
38 Model Selection/271 Grid Search in R.mp4 35.5 MB
27 Upper Confidence Bound (UCB)/166 Upper Confidence Bound in Python - Step 2.mp4 35.4 MB
13 K-Nearest Neighbors (K-NN)/093 K-NN in Python.mp4 35.2 MB
29 -------------------- Part 7_ Natural Language Processing --------------------/182 Natural Language Processing in Python - Step 1.mp4 35.2 MB
24 Apriori/150 Apriori Intuition.mp4 35.0 MB
02 -------------------- Part 1_ Data Preprocessing --------------------/015 Feature Scaling.mp4 34.6 MB
08 Decision Tree Regression/065 Decision Tree Regression in Python.mp4 33.5 MB
31 Artificial Neural Networks/229 ANN in R - Step 4 (Last step).mp4 33.4 MB
36 Kernel PCA/263 Kernel PCA in Python.mp4 33.4 MB
32 Convolutional Neural Networks/238 Softmax & Cross-Entropy.mp4 33.2 MB
38 Model Selection/267 k-Fold Cross Validation in Python.mp4 32.8 MB
05 Multiple Linear Regression/040 Multiple Linear Regression in Python - Backward Elimination - Preparation.mp4 32.8 MB
05 Multiple Linear Regression/041 Multiple Linear Regression in Python - Backward Elimination - HOMEWORK !.mp4 32.6 MB
14 Support Vector Machine (SVM)/098 SVM in R.mp4 32.3 MB
02 -------------------- Part 1_ Data Preprocessing --------------------/012 Missing Data.mp4 32.2 MB
39 XGBoost/274 XGBoost in Python - Step 2.mp4 32.0 MB
34 Principal Component Analysis (PCA)/253 PCA in Python - Step 1.mp4 31.9 MB
27 Upper Confidence Bound (UCB)/165 Upper Confidence Bound in Python - Step 1.mp4 31.5 MB
30 -------------------- Part 8_ Deep Learning --------------------/205 What is Deep Learning_.mp4 31.3 MB
14 Support Vector Machine (SVM)/097 SVM in Python.mp4 31.2 MB
32 Convolutional Neural Networks/232 Step 1 - Convolution Operation.mp4 31.0 MB
04 Simple Linear Regression/025 Simple Linear Regression in Python - Step 4.mp4 30.8 MB
34 Principal Component Analysis (PCA)/256 PCA in R - Step 1.mp4 30.6 MB
24 Apriori/153 Apriori in R - Step 2.mp4 30.5 MB
27 Upper Confidence Bound (UCB)/162 The Multi-Armed Bandit Problem.mp4 30.2 MB
31 Artificial Neural Networks/207 The Neuron.mp4 29.9 MB
17 Decision Tree Classification/115 Decision Tree Classification in Python.mp4 29.8 MB
31 Artificial Neural Networks/220 ANN in Python - Step 5.mp4 29.6 MB
24 Apriori/156 Apriori in Python - Step 2.mp4 29.5 MB
38 Model Selection/270 Grid Search in Python - Step 2.mp4 29.5 MB
32 Convolutional Neural Networks/231 What are convolutional neural networks_.mp4 29.5 MB
27 Upper Confidence Bound (UCB)/163 Upper Confidence Bound (UCB) Intuition.mp4 29.3 MB
31 Artificial Neural Networks/216 ANN in Python - Step 1 - Installing Theano_ Tensorflow and Keras.mp4 29.3 MB
15 Kernel SVM/101 The Kernel Trick.mp4 29.3 MB
12 Logistic Regression/077 Logistic Regression Intuition.mp4 29.2 MB
34 Principal Component Analysis (PCA)/257 PCA in R - Step 2.mp4 29.0 MB
27 Upper Confidence Bound (UCB)/170 Upper Confidence Bound in R - Step 2.mp4 29.0 MB
21 K-Means Clustering/133 K-Means Clustering in R.mp4 29.0 MB
29 -------------------- Part 7_ Natural Language Processing --------------------/201 Natural Language Processing in R - Step 9.mp4 29.0 MB
31 Artificial Neural Networks/228 ANN in R - Step 3.mp4 28.9 MB
05 Multiple Linear Regression/036 Multiple Linear Regression Intuition - Step 5.mp4 28.8 MB
27 Upper Confidence Bound (UCB)/169 Upper Confidence Bound in R - Step 1.mp4 28.1 MB
16 Naive Bayes/107 Naive Bayes Intuition.mp4 27.8 MB
06 Polynomial Regression/054 Python Regression Template.mp4 27.4 MB
32 Convolutional Neural Networks/243 CNN in Python - Step 4.mp4 27.2 MB
05 Multiple Linear Regression/042 Multiple Linear Regression in Python - Backward Elimination - Homework Solution.mp4 27.2 MB
06 Polynomial Regression/051 Polynomial Regression in Python - Step 2.mp4 27.1 MB
24 Apriori/157 Apriori in Python - Step 3.mp4 27.0 MB
21 K-Means Clustering/128 K-Means Clustering Intuition.mp4 26.9 MB
31 Artificial Neural Networks/210 How do Neural Networks learn_.mp4 26.6 MB
05 Multiple Linear Regression/044 Multiple Linear Regression in R - Step 2.mp4 25.9 MB
07 Support Vector Regression (SVR)/062 SVR in R.mp4 25.9 MB
34 Principal Component Analysis (PCA)/255 PCA in Python - Step 3.mp4 25.5 MB
06 Polynomial Regression/059 R Regression Template.mp4 25.4 MB
32 Convolutional Neural Networks/240 CNN in Python - Step 1.mp4 24.9 MB
06 Polynomial Regression/050 Polynomial Regression in Python - Step 1.mp4 24.9 MB
10 Evaluating Regression Models Performance/074 Interpreting Linear Regression Coefficients.mp4 24.2 MB
29 -------------------- Part 7_ Natural Language Processing --------------------/191 Natural Language Processing in Python - Step 10.mp4 24.1 MB
29 -------------------- Part 7_ Natural Language Processing --------------------/185 Natural Language Processing in Python - Step 4.mp4 24.0 MB
06 Polynomial Regression/056 Polynomial Regression in R - Step 2.mp4 23.9 MB
31 Artificial Neural Networks/209 How do Neural Networks work_.mp4 23.5 MB
16 Naive Bayes/111 Naive Bayes in Python.mp4 23.4 MB
02 -------------------- Part 1_ Data Preprocessing --------------------/010 Importing the Dataset.mp4 23.3 MB
21 K-Means Clustering/130 K-Means Selecting The Number Of Clusters.mp4 23.1 MB
22 Hierarchical Clustering/136 Hierarchical Clustering Using Dendrograms.mp4 22.8 MB
08 Decision Tree Regression/063 Decision Tree Regression Intuition.mp4 22.7 MB
06 Polynomial Regression/058 Polynomial Regression in R - Step 4.mp4 22.3 MB
34 Principal Component Analysis (PCA)/254 PCA in Python - Step 2.mp4 22.1 MB
29 -------------------- Part 7_ Natural Language Processing --------------------/183 Natural Language Processing in Python - Step 2.mp4 22.0 MB
10 Evaluating Regression Models Performance/073 Evaluating Regression Models Performance - Homework's Final Part.mp4 21.9 MB
04 Simple Linear Regression/022 Simple Linear Regression in Python - Step 1.mp4 21.7 MB
39 XGBoost/273 XGBoost in Python - Step 1.mp4 21.4 MB
02 -------------------- Part 1_ Data Preprocessing --------------------/008 Get the dataset.mp4 21.1 MB
25 Eclat/160 Eclat in R.mp4 20.7 MB
32 Convolutional Neural Networks/249 CNN in Python - Step 10.mp4 20.6 MB
02 -------------------- Part 1_ Data Preprocessing --------------------/016 And here is our Data Preprocessing Template!.mp4 19.7 MB
01 Welcome to the course!/005 Installing Python and Anaconda (MAC & Windows).mp4 19.5 MB
18 Random Forest Classification/117 Random Forest Classification Intuition.mp4 19.4 MB
10 Evaluating Regression Models Performance/072 Adjusted R-Squared Intuition.mp4 19.3 MB
16 Naive Bayes/109 Naive Bayes Intuition (Extras).mp4 18.9 MB
17 Decision Tree Classification/113 Decision Tree Classification Intuition.mp4 18.8 MB
04 Simple Linear Regression/023 Simple Linear Regression in Python - Step 2.mp4 18.8 MB
19 Evaluating Classification Models Performance/124 CAP Curve.mp4 18.7 MB
31 Artificial Neural Networks/211 Gradient Descent.mp4 18.5 MB
31 Artificial Neural Networks/223 ANN in Python - Step 8.mp4 18.2 MB
14 Support Vector Machine (SVM)/095 SVM Intuition.mp4 18.0 MB
05 Multiple Linear Regression/043 Multiple Linear Regression in R - Step 1.mp4 17.9 MB
06 Polynomial Regression/055 Polynomial Regression in R - Step 1.mp4 17.8 MB
01 Welcome to the course!/003 Installing R and R Studio (MAC & Windows).mp4 17.6 MB
29 -------------------- Part 7_ Natural Language Processing --------------------/194 Natural Language Processing in R - Step 2.mp4 17.5 MB
22 Hierarchical Clustering/135 Hierarchical Clustering How Dendrograms Work.mp4 17.5 MB
05 Multiple Linear Regression/047 Multiple Linear Regression in R - Backward Elimination - Homework Solution.mp4 17.2 MB
29 -------------------- Part 7_ Natural Language Processing --------------------/188 Natural Language Processing in Python - Step 7.mp4 17.1 MB
31 Artificial Neural Networks/225 ANN in Python - Step 10.mp4 17.1 MB
31 Artificial Neural Networks/224 ANN in Python - Step 9.mp4 16.9 MB
31 Artificial Neural Networks/212 Stochastic Gradient Descent.mp4 16.8 MB
22 Hierarchical Clustering/134 Hierarchical Clustering Intuition.mp4 16.5 MB
31 Artificial Neural Networks/215 Business Problem Description.mp4 16.4 MB
04 Simple Linear Regression/024 Simple Linear Regression in Python - Step 3.mp4 15.6 MB
21 K-Means Clustering/129 K-Means Random Initialization Trap.mp4 15.4 MB
29 -------------------- Part 7_ Natural Language Processing --------------------/186 Natural Language Processing in Python - Step 5.mp4 14.9 MB
31 Artificial Neural Networks/208 The Activation Function.mp4 14.8 MB
12 Logistic Regression/087 Logistic Regression in R - Step 3.mp4 14.6 MB
04 Simple Linear Regression/027 Simple Linear Regression in R - Step 2.mp4 14.4 MB
05 Multiple Linear Regression/039 Multiple Linear Regression in Python - Step 3.mp4 14.3 MB
05 Multiple Linear Regression/034 Multiple Linear Regression Intuition - Step 3.mp4 14.3 MB
31 Artificial Neural Networks/227 ANN in R - Step 2.mp4 14.2 MB
32 Convolutional Neural Networks/233 Step 1(b) - ReLU Layer.mp4 14.1 MB
28 Thompson Sampling/174 Algorithm Comparison_ UCB vs Thompson Sampling.mp4 14.1 MB
29 -------------------- Part 7_ Natural Language Processing --------------------/190 Natural Language Processing in Python - Step 9.mp4 14.0 MB
09 Random Forest Regression/067 Random Forest Regression Intuition.mp4 13.8 MB
15 Kernel SVM/100 Mapping to a higher dimension.mp4 13.7 MB
19 Evaluating Classification Models Performance/121 False Positives & False Negatives.mp4 13.6 MB
29 -------------------- Part 7_ Natural Language Processing --------------------/195 Natural Language Processing in R - Step 3.mp4 13.5 MB
06 Polynomial Regression/053 Polynomial Regression in Python - Step 4.mp4 13.5 MB
16 Naive Bayes/108 Naive Bayes Intuition (Challenge Reveal).mp4 13.3 MB
29 -------------------- Part 7_ Natural Language Processing --------------------/200 Natural Language Processing in R - Step 8.mp4 13.3 MB
32 Convolutional Neural Networks/246 CNN in Python - Step 7.mp4 12.9 MB
12 Logistic Regression/079 Logistic Regression in Python - Step 1.mp4 12.9 MB
01 Welcome to the course!/002 Why Machine Learning is the Future.mp4 12.8 MB
29 -------------------- Part 7_ Natural Language Processing --------------------/198 Natural Language Processing in R - Step 6.mp4 12.7 MB
22 Hierarchical Clustering/139 HC in Python - Step 2.mp4 12.6 MB
12 Logistic Regression/085 Logistic Regression in R - Step 1.mp4 12.6 MB
12 Logistic Regression/090 R Classification Template.mp4 12.5 MB
15 Kernel SVM/102 Types of Kernel Functions.mp4 12.3 MB
22 Hierarchical Clustering/140 HC in Python - Step 3.mp4 12.3 MB
12 Logistic Regression/084 Python Classification Template.mp4 12.1 MB
22 Hierarchical Clustering/141 HC in Python - Step 4.mp4 12.0 MB
04 Simple Linear Regression/018 How to get the dataset.mp4 11.7 MB
05 Multiple Linear Regression/030 How to get the dataset.mp4 11.7 MB
06 Polynomial Regression/049 How to get the dataset.mp4 11.7 MB
07 Support Vector Regression (SVR)/060 How to get the dataset.mp4 11.7 MB
08 Decision Tree Regression/064 How to get the dataset.mp4 11.7 MB
09 Random Forest Regression/068 How to get the dataset.mp4 11.7 MB
12 Logistic Regression/078 How to get the dataset.mp4 11.7 MB
13 K-Nearest Neighbors (K-NN)/092 How to get the dataset.mp4 11.7 MB
14 Support Vector Machine (SVM)/096 How to get the dataset.mp4 11.7 MB
15 Kernel SVM/103 How to get the dataset.mp4 11.7 MB
16 Naive Bayes/110 How to get the dataset.mp4 11.7 MB
17 Decision Tree Classification/114 How to get the dataset.mp4 11.7 MB
18 Random Forest Classification/118 How to get the dataset.mp4 11.7 MB
21 K-Means Clustering/131 How to get the dataset.mp4 11.7 MB
22 Hierarchical Clustering/137 How to get the dataset.mp4 11.7 MB
24 Apriori/151 How to get the dataset.mp4 11.7 MB
25 Eclat/159 How to get the dataset.mp4 11.7 MB
27 Upper Confidence Bound (UCB)/164 How to get the dataset.mp4 11.7 MB
28 Thompson Sampling/175 How to get the dataset.mp4 11.7 MB
29 -------------------- Part 7_ Natural Language Processing --------------------/181 How to get the dataset.mp4 11.7 MB
31 Artificial Neural Networks/214 How to get the dataset.mp4 11.7 MB
32 Convolutional Neural Networks/239 How to get the dataset.mp4 11.7 MB
34 Principal Component Analysis (PCA)/252 How to get the dataset.mp4 11.7 MB
35 Linear Discriminant Analysis (LDA)/259 How to get the dataset.mp4 11.7 MB
36 Kernel PCA/262 How to get the dataset.mp4 11.7 MB
38 Model Selection/266 How to get the dataset.mp4 11.7 MB
39 XGBoost/272 How to get the dataset.mp4 11.7 MB
19 Evaluating Classification Models Performance/125 CAP Curve Analysis.mp4 11.5 MB
22 Hierarchical Clustering/144 HC in R - Step 2.mp4 11.2 MB
02 -------------------- Part 1_ Data Preprocessing --------------------/009 Importing the Libraries.mp4 11.1 MB
31 Artificial Neural Networks/213 Backpropagation.mp4 10.9 MB
22 Hierarchical Clustering/138 HC in Python - Step 1.mp4 10.7 MB
25 Eclat/158 Eclat Intuition.mp4 10.6 MB
05 Multiple Linear Regression/045 Multiple Linear Regression in R - Step 3.mp4 10.4 MB
12 Logistic Regression/082 Logistic Regression in Python - Step 4.mp4 10.4 MB
05 Multiple Linear Regression/031 Dataset + Business Problem Description.mp4 10.0 MB
32 Convolutional Neural Networks/244 CNN in Python - Step 5.mp4 9.9 MB
32 Convolutional Neural Networks/245 CNN in Python - Step 6.mp4 9.7 MB
04 Simple Linear Regression/026 Simple Linear Regression in R - Step 1.mp4 9.5 MB
04 Simple Linear Regression/020 Simple Linear Regression Intuition - Step 1.mp4 9.5 MB
06 Polynomial Regression/048 Polynomial Regression Intuition.mp4 9.4 MB
13 K-Nearest Neighbors (K-NN)/091 K-Nearest Neighbor Intuition.mp4 9.3 MB
27 Upper Confidence Bound (UCB)/168 Upper Confidence Bound in Python - Step 4.mp4 9.1 MB
31 Artificial Neural Networks/222 ANN in Python - Step 7.mp4 9.0 MB
10 Evaluating Regression Models Performance/071 R-Squared Intuition.mp4 8.9 MB
04 Simple Linear Regression/028 Simple Linear Regression in R - Step 3.mp4 8.6 MB
28 Thompson Sampling/177 Thompson Sampling in Python - Step 2.mp4 8.4 MB
22 Hierarchical Clustering/142 HC in Python - Step 5.mp4 8.4 MB
31 Artificial Neural Networks/218 ANN in Python - Step 3.mp4 8.4 MB
12 Logistic Regression/080 Logistic Regression in Python - Step 2.mp4 8.2 MB
19 Evaluating Classification Models Performance/122 Confusion Matrix.mp4 8.2 MB
01 Welcome to the course!/001 Applications of Machine Learning.mp4 8.0 MB
32 Convolutional Neural Networks/237 Summary.mp4 7.9 MB
12 Logistic Regression/086 Logistic Regression in R - Step 2.mp4 7.8 MB
22 Hierarchical Clustering/145 HC in R - Step 3.mp4 7.8 MB
29 -------------------- Part 7_ Natural Language Processing --------------------/199 Natural Language Processing in R - Step 7.mp4 7.5 MB
28 Thompson Sampling/179 Thompson Sampling in R - Step 2.mp4 7.5 MB
22 Hierarchical Clustering/146 HC in R - Step 4.mp4 7.4 MB
27 Upper Confidence Bound (UCB)/172 Upper Confidence Bound in R - Step 4.mp4 7.4 MB
22 Hierarchical Clustering/143 HC in R - Step 1.mp4 7.4 MB
05 Multiple Linear Regression/038 Multiple Linear Regression in Python - Step 2.mp4 7.2 MB
31 Artificial Neural Networks/221 ANN in Python - Step 6.mp4 7.1 MB
12 Logistic Regression/088 Logistic Regression in R - Step 4.mp4 6.9 MB
22 Hierarchical Clustering/147 HC in R - Step 5.mp4 6.9 MB
32 Convolutional Neural Networks/247 CNN in Python - Step 8.mp4 6.8 MB
04 Simple Linear Regression/019 Dataset + Business Problem Description.mp4 6.6 MB
29 -------------------- Part 7_ Natural Language Processing --------------------/196 Natural Language Processing in R - Step 4.mp4 6.5 MB
29 -------------------- Part 7_ Natural Language Processing --------------------/187 Natural Language Processing in Python - Step 6.mp4 6.5 MB
12 Logistic Regression/081 Logistic Regression in Python - Step 3.mp4 6.0 MB
32 Convolutional Neural Networks/230 Plan of attack.mp4 5.9 MB
31 Artificial Neural Networks/219 ANN in Python - Step 4.mp4 5.9 MB
32 Convolutional Neural Networks/241 CNN in Python - Step 2.mp4 5.9 MB
15 Kernel SVM/099 Kernel SVM Intuition.mp4 5.8 MB
04 Simple Linear Regression/021 Simple Linear Regression Intuition - Step 2.mp4 5.4 MB
31 Artificial Neural Networks/206 Plan of attack.mp4 4.7 MB
29 -------------------- Part 7_ Natural Language Processing --------------------/197 Natural Language Processing in R - Step 5.mp4 4.6 MB
05 Multiple Linear Regression/035 Multiple Linear Regression Intuition - Step 4.mp4 4.5 MB
19 Evaluating Classification Models Performance/123 Accuracy Paradox.mp4 3.8 MB
29 -------------------- Part 7_ Natural Language Processing --------------------/184 Natural Language Processing in Python - Step 3.mp4 3.4 MB
32 Convolutional Neural Networks/235 Step 3 - Flattening.mp4 3.3 MB
02 -------------------- Part 1_ Data Preprocessing --------------------/007 Welcome to Part 1 - Data Preprocessing.mp4 3.0 MB
32 Convolutional Neural Networks/242 CNN in Python - Step 3.mp4 2.2 MB
05 Multiple Linear Regression/032 Multiple Linear Regression Intuition - Step 1.mp4 1.8 MB
05 Multiple Linear Regression/033 Multiple Linear Regression Intuition - Step 2.mp4 1.8 MB
25 Eclat/160 Eclat.zip 48.5 KB
16 Naive Bayes/106 Bayes Theorem-subtitle-en.srt 34.5 KB
18 Random Forest Classification/120 Random Forest Classification in R-subtitle-en.srt 32.4 KB
08 Decision Tree Regression/066 Decision Tree Regression in R-subtitle-en.srt 32.1 KB
36 Kernel PCA/264 Kernel PCA in R-subtitle-en.srt 32.0 KB
06 Polynomial Regression/052 Polynomial Regression in Python - Step 3-subtitle-en.srt 31.4 KB
24 Apriori/154 Apriori in R - Step 3-subtitle-en.srt 31.2 KB
24 Apriori/152 Apriori in R - Step 1-subtitle-en.srt 31.1 KB
07 Support Vector Regression (SVR)/061 SVR in Python-subtitle-en.srt 30.9 KB
35 Linear Discriminant Analysis (LDA)/261 LDA in R-subtitle-en.srt 30.9 KB
06 Polynomial Regression/057 Polynomial Regression in R - Step 3-subtitle-en.srt 30.9 KB
18 Random Forest Classification/119 Random Forest Classification in Python-subtitle-en.srt 30.7 KB
32 Convolutional Neural Networks/248 CNN in Python - Step 9-subtitle-en.srt 30.5 KB
31 Artificial Neural Networks/217 ANN in Python - Step 2-subtitle-en.srt 30.2 KB
28 Thompson Sampling/176 Thompson Sampling in Python - Step 1-subtitle-en.srt 30.0 KB
12 Logistic Regression/083 Logistic Regression in Python - Step 5-subtitle-en.srt 29.7 KB
32 Convolutional Neural Networks/236 Step 4 - Full Connection-subtitle-en.srt 29.6 KB
17 Decision Tree Classification/116 Decision Tree Classification in R-subtitle-en.srt 29.1 KB
12 Logistic Regression/089 Logistic Regression in R - Step 5-subtitle-en.srt 29.1 KB
38 Model Selection/268 k-Fold Cross Validation in R-subtitle-en.srt 29.0 KB
28 Thompson Sampling/178 Thompson Sampling in R - Step 1-subtitle-en.srt 28.9 KB
28 Thompson Sampling/173 Thompson Sampling Intuition-subtitle-en.srt 28.5 KB
15 Kernel SVM/104 Kernel SVM in Python-subtitle-en.srt 28.2 KB
21 K-Means Clustering/132 K-Means Clustering in Python-subtitle-en.srt 28.2 KB
09 Random Forest Regression/070 Random Forest Regression in R-subtitle-en.srt 28.1 KB
27 Upper Confidence Bound (UCB)/167 Upper Confidence Bound in Python - Step 3-subtitle-en.srt 28.0 KB
24 Apriori/155 Apriori in Python - Step 1-subtitle-en.srt 28.0 KB
31 Artificial Neural Networks/226 ANN in R - Step 1-subtitle-en.srt 27.9 KB
09 Random Forest Regression/069 Random Forest Regression in Python-subtitle-en.srt 27.5 KB
35 Linear Discriminant Analysis (LDA)/260 LDA in Python-subtitle-en.srt 27.5 KB
05 Multiple Linear Regression/046 Multiple Linear Regression in R - Backward Elimination - HOMEWORK !-subtitle-en.srt 27.5 KB
29 -------------------- Part 7_ Natural Language Processing --------------------/202 Natural Language Processing in R - Step 10-subtitle-en.srt 27.3 KB
39 XGBoost/275 XGBoost in R-subtitle-en.srt 27.0 KB
02 -------------------- Part 1_ Data Preprocessing --------------------/013 Categorical Data-subtitle-en.srt 27.0 KB
02 -------------------- Part 1_ Data Preprocessing --------------------/014 Splitting the Dataset into the Training set and Test set-subtitle-en.srt 26.9 KB
24 Apriori/150 Apriori Intuition-subtitle-en.srt 26.9 KB
27 Upper Confidence Bound (UCB)/171 Upper Confidence Bound in R - Step 3-subtitle-en.srt 26.3 KB
27 Upper Confidence Bound (UCB)/166 Upper Confidence Bound in Python - Step 2-subtitle-en.srt 26.3 KB
32 Convolutional Neural Networks/238 Softmax & Cross-Entropy-subtitle-en.srt 26.2 KB
31 Artificial Neural Networks/207 The Neuron-subtitle-en.srt 26.0 KB
15 Kernel SVM/105 Kernel SVM in R-subtitle-en.srt 25.4 KB
29 -------------------- Part 7_ Natural Language Processing --------------------/193 Natural Language Processing in R - Step 1-subtitle-en.srt 24.9 KB
12 Logistic Regression/077 Logistic Regression Intuition-subtitle-en.srt 24.8 KB
29 -------------------- Part 7_ Natural Language Processing --------------------/189 Natural Language Processing in Python - Step 8-subtitle-en.srt 24.7 KB
05 Multiple Linear Regression/037 Multiple Linear Regression in Python - Step 1-subtitle-en.srt 24.4 KB
32 Convolutional Neural Networks/232 Step 1 - Convolution Operation-subtitle-en.srt 24.1 KB
04 Simple Linear Regression/029 Simple Linear Regression in R - Step 4-subtitle-en.srt 23.9 KB
08 Decision Tree Regression/065 Decision Tree Regression in Python-subtitle-en.srt 23.7 KB
02 -------------------- Part 1_ Data Preprocessing --------------------/012 Missing Data-subtitle-en.srt 23.6 KB
05 Multiple Linear Regression/036 Multiple Linear Regression Intuition - Step 5-subtitle-en.srt 23.6 KB
02 -------------------- Part 1_ Data Preprocessing --------------------/015 Feature Scaling-subtitle-en.srt 23.5 KB
13 K-Nearest Neighbors (K-NN)/094 K-NN in R-subtitle-en.srt 23.4 KB
21 K-Means Clustering/128 K-Means Clustering Intuition-subtitle-en.srt 23.3 KB
16 Naive Bayes/107 Naive Bayes Intuition-subtitle-en.srt 23.3 KB
27 Upper Confidence Bound (UCB)/162 The Multi-Armed Bandit Problem-subtitle-en.srt 23.1 KB
27 Upper Confidence Bound (UCB)/170 Upper Confidence Bound in R - Step 2-subtitle-en.srt 23.1 KB
24 Apriori/153 Apriori in R - Step 2-subtitle-en.srt 23.0 KB
38 Model Selection/269 Grid Search in Python - Step 1-subtitle-en.srt 22.9 KB
32 Convolutional Neural Networks/231 What are convolutional neural networks_-subtitle-en.srt 22.9 KB
27 Upper Confidence Bound (UCB)/163 Upper Confidence Bound (UCB) Intuition-subtitle-en.srt 22.8 KB
27 Upper Confidence Bound (UCB)/165 Upper Confidence Bound in Python - Step 1-subtitle-en.srt 22.7 KB
24 Apriori/156 Apriori in Python - Step 2-subtitle-en.srt 22.5 KB
04 Simple Linear Regression/025 Simple Linear Regression in Python - Step 4-subtitle-en.srt 22.4 KB
36 Kernel PCA/263 Kernel PCA in Python-subtitle-en.srt 22.3 KB
16 Naive Bayes/112 Naive Bayes in R-subtitle-en.srt 21.9 KB
32 Convolutional Neural Networks/234 Step 2 - Pooling-subtitle-en.srt 21.8 KB
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31 Artificial Neural Networks/229 ANN in R - Step 4 (Last step)-subtitle-en.srt 21.5 KB
27 Upper Confidence Bound (UCB)/169 Upper Confidence Bound in R - Step 1-subtitle-en.srt 21.3 KB
13 K-Nearest Neighbors (K-NN)/093 K-NN in Python-subtitle-en.srt 21.2 KB
38 Model Selection/267 k-Fold Cross Validation in Python-subtitle-en.srt 21.0 KB
31 Artificial Neural Networks/216 ANN in Python - Step 1 - Installing Theano_ Tensorflow and Keras-subtitle-en.srt 20.8 KB
34 Principal Component Analysis (PCA)/258 PCA in R - Step 3-subtitle-en.srt 20.6 KB
29 -------------------- Part 7_ Natural Language Processing --------------------/201 Natural Language Processing in R - Step 9-subtitle-en.srt 20.3 KB
31 Artificial Neural Networks/220 ANN in Python - Step 5-subtitle-en.srt 20.2 KB
32 Convolutional Neural Networks/243 CNN in Python - Step 4-subtitle-en.srt 20.0 KB
31 Artificial Neural Networks/209 How do Neural Networks work_-subtitle-en.srt 19.8 KB
05 Multiple Linear Regression/040 Multiple Linear Regression in Python - Backward Elimination - Preparation-subtitle-en.srt 19.7 KB
05 Multiple Linear Regression/041 Multiple Linear Regression in Python - Backward Elimination - HOMEWORK !-subtitle-en.srt 19.7 KB
31 Artificial Neural Networks/210 How do Neural Networks learn_-subtitle-en.srt 19.7 KB
39 XGBoost/274 XGBoost in Python - Step 2-subtitle-en.srt 19.6 KB
31 Artificial Neural Networks/228 ANN in R - Step 3-subtitle-en.srt 19.6 KB
24 Apriori/157 Apriori in Python - Step 3-subtitle-en.srt 19.6 KB
21 K-Means Clustering/133 K-Means Clustering in R-subtitle-en.srt 19.4 KB
17 Decision Tree Classification/115 Decision Tree Classification in Python-subtitle-en.srt 19.4 KB
34 Principal Component Analysis (PCA)/256 PCA in R - Step 1-subtitle-en.srt 19.4 KB
14 Support Vector Machine (SVM)/097 SVM in Python-subtitle-en.srt 19.2 KB
29 -------------------- Part 7_ Natural Language Processing --------------------/182 Natural Language Processing in Python - Step 1-subtitle-en.srt 19.0 KB
32 Convolutional Neural Networks/240 CNN in Python - Step 1-subtitle-en.srt 19.0 KB
30 -------------------- Part 8_ Deep Learning --------------------/205 What is Deep Learning_-subtitle-en.srt 18.8 KB
07 Support Vector Regression (SVR)/062 SVR in R-subtitle-en.srt 18.7 KB
02 -------------------- Part 1_ Data Preprocessing --------------------/010 Importing the Dataset-subtitle-en.srt 18.7 KB
06 Polynomial Regression/059 R Regression Template-subtitle-en.srt 18.6 KB
21 K-Means Clustering/130 K-Means Selecting The Number Of Clusters-subtitle-en.srt 18.5 KB
14 Support Vector Machine (SVM)/098 SVM in R-subtitle-en.srt 18.4 KB
34 Principal Component Analysis (PCA)/253 PCA in Python - Step 1-subtitle-en.srt 18.3 KB
29 -------------------- Part 7_ Natural Language Processing --------------------/185 Natural Language Processing in Python - Step 4-subtitle-en.srt 18.2 KB
22 Hierarchical Clustering/136 Hierarchical Clustering Using Dendrograms-subtitle-en.srt 17.6 KB
34 Principal Component Analysis (PCA)/257 PCA in R - Step 2-subtitle-en.srt 17.6 KB
06 Polynomial Regression/050 Polynomial Regression in Python - Step 1-subtitle-en.srt 17.5 KB
06 Polynomial Regression/051 Polynomial Regression in Python - Step 2-subtitle-en.srt 17.2 KB
15 Kernel SVM/101 The Kernel Trick-subtitle-en.srt 17.2 KB
08 Decision Tree Regression/063 Decision Tree Regression Intuition-subtitle-en.srt 17.1 KB
29 -------------------- Part 7_ Natural Language Processing --------------------/183 Natural Language Processing in Python - Step 2-subtitle-en.srt 16.4 KB
06 Polynomial Regression/054 Python Regression Template-subtitle-en.srt 16.4 KB
19 Evaluating Classification Models Performance/124 CAP Curve-subtitle-en.srt 16.2 KB
38 Model Selection/270 Grid Search in Python - Step 2-subtitle-en.srt 15.9 KB
16 Naive Bayes/109 Naive Bayes Intuition (Extras)-subtitle-en.srt 15.9 KB
25 Eclat/160 Eclat in R-subtitle-en.srt 15.8 KB
14 Support Vector Machine (SVM)/095 SVM Intuition-subtitle-en.srt 15.7 KB
04 Simple Linear Regression/022 Simple Linear Regression in Python - Step 1-subtitle-en.srt 15.5 KB
06 Polynomial Regression/058 Polynomial Regression in R - Step 4-subtitle-en.srt 15.4 KB
05 Multiple Linear Regression/044 Multiple Linear Regression in R - Step 2-subtitle-en.srt 15.4 KB
34 Principal Component Analysis (PCA)/255 PCA in Python - Step 3-subtitle-en.srt 15.4 KB
06 Polynomial Regression/056 Polynomial Regression in R - Step 2-subtitle-en.srt 15.3 KB
29 -------------------- Part 7_ Natural Language Processing --------------------/191 Natural Language Processing in Python - Step 10-subtitle-en.srt 14.9 KB
22 Hierarchical Clustering/134 Hierarchical Clustering Intuition-subtitle-en.srt 14.6 KB
31 Artificial Neural Networks/211 Gradient Descent-subtitle-en.srt 14.6 KB
10 Evaluating Regression Models Performance/072 Adjusted R-Squared Intuition-subtitle-en.srt 14.4 KB
22 Hierarchical Clustering/135 Hierarchical Clustering How Dendrograms Work-subtitle-en.srt 14.4 KB
05 Multiple Linear Regression/042 Multiple Linear Regression in Python - Backward Elimination - Homework Solution-subtitle-en.srt 14.2 KB
02 -------------------- Part 1_ Data Preprocessing --------------------/016 And here is our Data Preprocessing Template!-subtitle-en.srt 14.2 KB
39 XGBoost/273 XGBoost in Python - Step 1-subtitle-en.srt 14.2 KB
06 Polynomial Regression/055 Polynomial Regression in R - Step 1-subtitle-en.srt 14.1 KB
16 Naive Bayes/111 Naive Bayes in Python-subtitle-en.srt 13.8 KB
32 Convolutional Neural Networks/249 CNN in Python - Step 10-subtitle-en.srt 13.5 KB
29 -------------------- Part 7_ Natural Language Processing --------------------/194 Natural Language Processing in R - Step 2-subtitle-en.srt 13.4 KB
10 Evaluating Regression Models Performance/074 Interpreting Linear Regression Coefficients-subtitle-en.srt 13.3 KB
21 K-Means Clustering/129 K-Means Random Initialization Trap-subtitle-en.srt 13.0 KB
10 Evaluating Regression Models Performance/073 Evaluating Regression Models Performance - Homework's Final Part-subtitle-en.srt 12.9 KB
17 Decision Tree Classification/113 Decision Tree Classification Intuition-subtitle-en.srt 12.9 KB
31 Artificial Neural Networks/212 Stochastic Gradient Descent-subtitle-en.srt 12.6 KB
31 Artificial Neural Networks/208 The Activation Function-subtitle-en.srt 12.5 KB
04 Simple Linear Regression/023 Simple Linear Regression in Python - Step 2-subtitle-en.srt 12.3 KB
01 Welcome to the course!/005 Installing Python and Anaconda (MAC & Windows)-subtitle-en.srt 12.3 KB
34 Principal Component Analysis (PCA)/254 PCA in Python - Step 2-subtitle-en.srt 12.3 KB
05 Multiple Linear Regression/047 Multiple Linear Regression in R - Backward Elimination - Homework Solution-subtitle-en.srt 11.9 KB
05 Multiple Linear Regression/043 Multiple Linear Regression in R - Step 1-subtitle-en.srt 11.9 KB
28 Thompson Sampling/174 Algorithm Comparison_ UCB vs Thompson Sampling-subtitle-en.srt 11.5 KB
31 Artificial Neural Networks/223 ANN in Python - Step 8-subtitle-en.srt 11.5 KB
19 Evaluating Classification Models Performance/121 False Positives & False Negatives-subtitle-en.srt 11.3 KB
29 -------------------- Part 7_ Natural Language Processing --------------------/186 Natural Language Processing in Python - Step 5-subtitle-en.srt 11.1 KB
02 -------------------- Part 1_ Data Preprocessing --------------------/008 Get the dataset-subtitle-en.srt 11.1 KB
15 Kernel SVM/100 Mapping to a higher dimension-subtitle-en.srt 10.9 KB
31 Artificial Neural Networks/225 ANN in Python - Step 10-subtitle-en.srt 10.8 KB
05 Multiple Linear Regression/034 Multiple Linear Regression Intuition - Step 3-subtitle-en.srt 10.7 KB
29 -------------------- Part 7_ Natural Language Processing --------------------/195 Natural Language Processing in R - Step 3-subtitle-en.srt 10.5 KB
31 Artificial Neural Networks/227 ANN in R - Step 2-subtitle-en.srt 10.5 KB
09 Random Forest Regression/067 Random Forest Regression Intuition-subtitle-en.srt 10.2 KB
29 -------------------- Part 7_ Natural Language Processing --------------------/188 Natural Language Processing in Python - Step 7-subtitle-en.srt 10.2 KB
31 Artificial Neural Networks/224 ANN in Python - Step 9-subtitle-en.srt 9.9 KB
04 Simple Linear Regression/024 Simple Linear Regression in Python - Step 3-subtitle-en.srt 9.8 KB
01 Welcome to the course!/002 Why Machine Learning is the Future-subtitle-en.srt 9.6 KB
32 Convolutional Neural Networks/233 Step 1(b) - ReLU Layer-subtitle-en.srt 9.5 KB
22 Hierarchical Clustering/139 HC in Python - Step 2-subtitle-en.srt 9.5 KB
16 Naive Bayes/108 Naive Bayes Intuition (Challenge Reveal)-subtitle-en.srt 9.5 KB
32 Convolutional Neural Networks/246 CNN in Python - Step 7-subtitle-en.srt 9.5 KB
19 Evaluating Classification Models Performance/125 CAP Curve Analysis-subtitle-en.srt 9.2 KB
01 Welcome to the course!/003 Installing R and R Studio (MAC & Windows)-subtitle-en.srt 9.2 KB
12 Logistic Regression/085 Logistic Regression in R - Step 1-subtitle-en.srt 8.9 KB
04 Simple Linear Regression/027 Simple Linear Regression in R - Step 2-subtitle-en.srt 8.9 KB
12 Logistic Regression/079 Logistic Regression in Python - Step 1-subtitle-en.srt 8.8 KB
29 -------------------- Part 7_ Natural Language Processing --------------------/198 Natural Language Processing in R - Step 6-subtitle-en.srt 8.7 KB
06 Polynomial Regression/053 Polynomial Regression in Python - Step 4-subtitle-en.srt 8.7 KB
29 -------------------- Part 7_ Natural Language Processing --------------------/190 Natural Language Processing in Python - Step 9-subtitle-en.srt 8.6 KB
25 Eclat/158 Eclat Intuition-subtitle-en.srt 8.4 KB
02 -------------------- Part 1_ Data Preprocessing --------------------/009 Importing the Libraries-subtitle-en.srt 8.4 KB
29 -------------------- Part 7_ Natural Language Processing --------------------/200 Natural Language Processing in R - Step 8-subtitle-en.srt 8.3 KB
04 Simple Linear Regression/020 Simple Linear Regression Intuition - Step 1-subtitle-en.srt 8.3 KB
05 Multiple Linear Regression/039 Multiple Linear Regression in Python - Step 3-subtitle-en.srt 8.3 KB
14 Support Vector Machine (SVM)/098 SVM.zip 8.3 KB
22 Hierarchical Clustering/144 HC in R - Step 2-subtitle-en.srt 8.1 KB
13 K-Nearest Neighbors (K-NN)/091 K-Nearest Neighbor Intuition-subtitle-en.srt 8.0 KB
32 Convolutional Neural Networks/245 CNN in Python - Step 6-subtitle-en.srt 7.9 KB
06 Polynomial Regression/048 Polynomial Regression Intuition-subtitle-en.srt 7.8 KB
32 Convolutional Neural Networks/244 CNN in Python - Step 5-subtitle-en.srt 7.8 KB
22 Hierarchical Clustering/140 HC in Python - Step 3-subtitle-en.srt 7.7 KB
04 Simple Linear Regression/026 Simple Linear Regression in R - Step 1-subtitle-en.srt 7.7 KB
22 Hierarchical Clustering/138 HC in Python - Step 1-subtitle-en.srt 7.6 KB
31 Artificial Neural Networks/215 Business Problem Description-subtitle-en.srt 7.6 KB
19 Evaluating Classification Models Performance/122 Confusion Matrix-subtitle-en.srt 7.5 KB
12 Logistic Regression/087 Logistic Regression in R - Step 3-subtitle-en.srt 7.4 KB
31 Artificial Neural Networks/213 Backpropagation-subtitle-en.srt 7.4 KB
10 Evaluating Regression Models Performance/071 R-Squared Intuition-subtitle-en.srt 7.2 KB
12 Logistic Regression/082 Logistic Regression in Python - Step 4-subtitle-en.srt 7.2 KB
05 Multiple Linear Regression/045 Multiple Linear Regression in R - Step 3-subtitle-en.srt 7.1 KB
18 Random Forest Classification/117 Random Forest Classification Intuition-subtitle-en.srt 7.1 KB
22 Hierarchical Clustering/142 HC in Python - Step 5-subtitle-en.srt 6.8 KB
12 Logistic Regression/090 R Classification Template-subtitle-en.srt 6.7 KB
22 Hierarchical Clustering/141 HC in Python - Step 4-subtitle-en.srt 6.5 KB
22 Hierarchical Clustering/143 HC in R - Step 1-subtitle-en.srt 6.4 KB
32 Convolutional Neural Networks/237 Summary-subtitle-en.srt 6.2 KB
12 Logistic Regression/084 Python Classification Template-subtitle-en.srt 6.1 KB
28 Thompson Sampling/177 Thompson Sampling in Python - Step 2-subtitle-en.srt 5.8 KB
40 Bonus Lectures/276 ___YOUR SPECIAL BONUS___.html 5.8 KB
31 Artificial Neural Networks/222 ANN in Python - Step 7-subtitle-en.srt 5.7 KB
05 Multiple Linear Regression/031 Dataset + Business Problem Description-subtitle-en.srt 5.7 KB
29 -------------------- Part 7_ Natural Language Processing --------------------/199 Natural Language Processing in R - Step 7-subtitle-en.srt 5.6 KB
04 Simple Linear Regression/028 Simple Linear Regression in R - Step 3-subtitle-en.srt 5.5 KB
01 Welcome to the course!/001 Applications of Machine Learning-subtitle-en.srt 5.5 KB
32 Convolutional Neural Networks/230 Plan of attack-subtitle-en.srt 5.4 KB
28 Thompson Sampling/179 Thompson Sampling in R - Step 2-subtitle-en.srt 5.3 KB
31 Artificial Neural Networks/218 ANN in Python - Step 3-subtitle-en.srt 5.2 KB
27 Upper Confidence Bound (UCB)/168 Upper Confidence Bound in Python - Step 4-subtitle-en.srt 5.2 KB
15 Kernel SVM/102 Types of Kernel Functions-subtitle-en.srt 5.1 KB
04 Simple Linear Regression/018 How to get the dataset-subtitle-en.srt 4.9 KB
05 Multiple Linear Regression/030 How to get the dataset-subtitle-en.srt 4.9 KB
06 Polynomial Regression/049 How to get the dataset-subtitle-en.srt 4.9 KB
07 Support Vector Regression (SVR)/060 How to get the dataset-subtitle-en.srt 4.9 KB
08 Decision Tree Regression/064 How to get the dataset-subtitle-en.srt 4.9 KB
09 Random Forest Regression/068 How to get the dataset-subtitle-en.srt 4.9 KB
12 Logistic Regression/078 How to get the dataset-subtitle-en.srt 4.9 KB
13 K-Nearest Neighbors (K-NN)/092 How to get the dataset-subtitle-en.srt 4.9 KB
14 Support Vector Machine (SVM)/096 How to get the dataset-subtitle-en.srt 4.9 KB
15 Kernel SVM/103 How to get the dataset-subtitle-en.srt 4.9 KB
16 Naive Bayes/110 How to get the dataset-subtitle-en.srt 4.9 KB
17 Decision Tree Classification/114 How to get the dataset-subtitle-en.srt 4.9 KB
18 Random Forest Classification/118 How to get the dataset-subtitle-en.srt 4.9 KB
21 K-Means Clustering/131 How to get the dataset-subtitle-en.srt 4.9 KB
22 Hierarchical Clustering/137 How to get the dataset-subtitle-en.srt 4.9 KB
24 Apriori/151 How to get the dataset-subtitle-en.srt 4.9 KB
25 Eclat/159 How to get the dataset-subtitle-en.srt 4.9 KB
27 Upper Confidence Bound (UCB)/164 How to get the dataset-subtitle-en.srt 4.9 KB
28 Thompson Sampling/175 How to get the dataset-subtitle-en.srt 4.9 KB
29 -------------------- Part 7_ Natural Language Processing --------------------/181 How to get the dataset-subtitle-en.srt 4.9 KB
31 Artificial Neural Networks/214 How to get the dataset-subtitle-en.srt 4.9 KB
32 Convolutional Neural Networks/239 How to get the dataset-subtitle-en.srt 4.9 KB
34 Principal Component Analysis (PCA)/252 How to get the dataset-subtitle-en.srt 4.9 KB
35 Linear Discriminant Analysis (LDA)/259 How to get the dataset-subtitle-en.srt 4.9 KB
36 Kernel PCA/262 How to get the dataset-subtitle-en.srt 4.9 KB
38 Model Selection/266 How to get the dataset-subtitle-en.srt 4.9 KB
39 XGBoost/272 How to get the dataset-subtitle-en.srt 4.9 KB
12 Logistic Regression/080 Logistic Regression in Python - Step 2-subtitle-en.srt 4.9 KB
19 Evaluating Classification Models Performance/126 Conclusion of Part 3 - Classification.html 4.8 KB
32 Convolutional Neural Networks/247 CNN in Python - Step 8-subtitle-en.srt 4.8 KB
22 Hierarchical Clustering/145 HC in R - Step 3-subtitle-en.srt 4.7 KB
29 -------------------- Part 7_ Natural Language Processing --------------------/196 Natural Language Processing in R - Step 4-subtitle-en.srt 4.7 KB
32 Convolutional Neural Networks/241 CNN in Python - Step 2-subtitle-en.srt 4.6 KB
27 Upper Confidence Bound (UCB)/172 Upper Confidence Bound in R - Step 4-subtitle-en.srt 4.6 KB
15 Kernel SVM/099 Kernel SVM Intuition-subtitle-en.srt 4.6 KB
29 -------------------- Part 7_ Natural Language Processing --------------------/187 Natural Language Processing in Python - Step 6-subtitle-en.srt 4.6 KB
31 Artificial Neural Networks/221 ANN in Python - Step 6-subtitle-en.srt 4.5 KB
12 Logistic Regression/086 Logistic Regression in R - Step 2-subtitle-en.srt 4.4 KB
04 Simple Linear Regression/021 Simple Linear Regression Intuition - Step 2-subtitle-en.srt 4.3 KB
10 Evaluating Regression Models Performance/075 Conclusion of Part 2 - Regression.html 4.3 KB
31 Artificial Neural Networks/206 Plan of attack-subtitle-en.srt 4.1 KB
12 Logistic Regression/081 Logistic Regression in Python - Step 3-subtitle-en.srt 4.1 KB
04 Simple Linear Regression/019 Dataset + Business Problem Description-subtitle-en.srt 4.1 KB
05 Multiple Linear Regression/038 Multiple Linear Regression in Python - Step 2-subtitle-en.srt 4.1 KB
22 Hierarchical Clustering/147 HC in R - Step 5-subtitle-en.srt 4.0 KB
12 Logistic Regression/088 Logistic Regression in R - Step 4-subtitle-en.srt 4.0 KB
31 Artificial Neural Networks/219 ANN in Python - Step 4-subtitle-en.srt 3.9 KB
22 Hierarchical Clustering/146 HC in R - Step 4-subtitle-en.srt 3.8 KB
05 Multiple Linear Regression/035 Multiple Linear Regression Intuition - Step 4-subtitle-en.srt 3.5 KB
32 Convolutional Neural Networks/250 CNN in R.html 3.5 KB
29 -------------------- Part 7_ Natural Language Processing --------------------/197 Natural Language Processing in R - Step 5-subtitle-en.srt 3.4 KB
19 Evaluating Classification Models Performance/123 Accuracy Paradox-subtitle-en.srt 3.2 KB
29 -------------------- Part 7_ Natural Language Processing --------------------/180 Welcome to Part 7 - Natural Language Processing.html 2.8 KB
32 Convolutional Neural Networks/235 Step 3 - Flattening-subtitle-en.srt 2.6 KB
29 -------------------- Part 7_ Natural Language Processing --------------------/184 Natural Language Processing in Python - Step 3-subtitle-en.srt 2.6 KB
02 -------------------- Part 1_ Data Preprocessing --------------------/007 Welcome to Part 1 - Data Preprocessing-subtitle-en.srt 2.5 KB
29 -------------------- Part 7_ Natural Language Processing --------------------/203 Homework Challenge.html 2.5 KB
29 -------------------- Part 7_ Natural Language Processing --------------------/192 Homework Challenge.html 2.5 KB
33 -------------------- Part 9_ Dimensionality Reduction --------------------/251 Welcome to Part 9 - Dimensionality Reduction.html 2.4 KB
01 Welcome to the course!/004 Update_ Recommended Anaconda Version.html 2.3 KB
01 Welcome to the course!/006 BONUS_ Meet your instructors.html 2.2 KB
37 -------------------- Part 10_ Model Selection & Boosting --------------------/265 Welcome to Part 10 - Model Selection & Boosting.html 2.0 KB
03 -------------------- Part 2_ Regression --------------------/017 Welcome to Part 2 - Regression.html 2.0 KB
30 -------------------- Part 8_ Deep Learning --------------------/204 Welcome to Part 8 - Deep Learning.html 2.0 KB
11 -------------------- Part 3_ Classification --------------------/076 Welcome to Part 3 - Classification.html 1.9 KB
26 -------------------- Part 6_ Reinforcement Learning --------------------/161 Welcome to Part 6 - Reinforcement Learning.html 1.9 KB
20 -------------------- Part 4_ Clustering --------------------/127 Welcome to Part 4 - Clustering.html 1.8 KB
32 Convolutional Neural Networks/242 CNN in Python - Step 3-subtitle-en.srt 1.7 KB
22 Hierarchical Clustering/148 Conclusion of Part 4 - Clustering.html 1.6 KB
05 Multiple Linear Regression/032 Multiple Linear Regression Intuition - Step 1-subtitle-en.srt 1.6 KB
23 -------------------- Part 5_ Association Rule Learning --------------------/149 Welcome to Part 5 - Association Rule Learning.html 1.5 KB
05 Multiple Linear Regression/033 Multiple Linear Regression Intuition - Step 2-subtitle-en.srt 1.5 KB
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