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12 Logistic Regression/096 Logistic Regression in R - Step 5.mp4 93.76 MB
31 Artificial Neural Networks/225 ANN in Python - Step 2.mp4 84.87 MB
17 Decision Tree Classification/123 Decision Tree Classification in R.mp4 68.18 MB
14 Support Vector Machine (SVM)/105 SVM in R.mp4 65.31 MB
18 Random Forest Classification/127 Random Forest Classification in R.mp4 64.11 MB
32 Convolutional Neural Networks/256 CNN in Python - Step 9.mp4 62.41 MB
18 Random Forest Classification/126 Random Forest Classification in Python.mp4 62.04 MB
07 Support Vector Regression (SVR)/068 SVR in Python.mp4 60.22 MB
05 Multiple Linear Regression/045 Multiple Linear Regression in Python - Backward Elimination - HOMEWORK.mp4 59.14 MB
27 Upper Confidence Bound (UCB)/178 Upper Confidence Bound in R - Step 3.mp4 57.84 MB
36 Kernel PCA/274 Kernel PCA in R.mp4 56.57 MB
24 Apriori/161 Apriori in R - Step 3.mp4 56.51 MB
08 Decision Tree Regression/073 Decision Tree Regression in R.mp4 56.23 MB
13 K-Nearest Neighbors (K-NN)/101 K-NN in R.mp4 55.77 MB
28 Thompson Sampling/183 Thompson Sampling in Python - Step 1.mp4 55.52 MB
15 Kernel SVM/111 Kernel SVM in Python.mp4 54.86 MB
06 Polynomial Regression/063 Polynomial Regression in R - Step 3.mp4 54.8 MB
06 Polynomial Regression/058 Polynomial Regression in Python - Step 3.mp4 54.5 MB
05 Multiple Linear Regression/046 Multiple Linear Regression in Python - Backward Elimination - Homework Solution.mp4 54.26 MB
29 -------------------- Part 7 Natural Language Processing --------------------/210 Natural Language Processing in R - Step 10.mp4 54.14 MB
27 Upper Confidence Bound (UCB)/174 Upper Confidence Bound in Python - Step 3.mp4 53.71 MB
12 Logistic Regression/090 Logistic Regression in Python - Step 5.mp4 53.15 MB
02 -------------------- Part 1 Data Preprocessing --------------------/015 Categorical Data.mp4 52.88 MB
24 Apriori/159 Apriori in R - Step 1.mp4 52.83 MB
15 Kernel SVM/112 Kernel SVM in R.mp4 52.82 MB
09 Random Forest Regression/076 Random Forest Regression in Python.mp4 52.69 MB
05 Multiple Linear Regression/041 Multiple Linear Regression in Python - Step 1.mp4 52.18 MB
29 -------------------- Part 7 Natural Language Processing --------------------/197 Natural Language Processing in Python - Step 8.mp4 52.02 MB
09 Random Forest Regression/077 Random Forest Regression in R.mp4 51.86 MB
35 Linear Discriminant Analysis (LDA)/271 LDA in R.mp4 51.29 MB
29 -------------------- Part 7 Natural Language Processing --------------------/201 Natural Language Processing in R - Step 1.mp4 51.2 MB
28 Thompson Sampling/185 Thompson Sampling in R - Step 1.mp4 51.04 MB
02 -------------------- Part 1 Data Preprocessing --------------------/017 Splitting the Dataset into the Training set and Test set.mp4 50.91 MB
05 Multiple Linear Regression/051 Multiple Linear Regression in R - Backward Elimination - HOMEWORK.mp4 50.78 MB
16 Naive Bayes/113 Bayes Theorem.mp4 50.43 MB
31 Artificial Neural Networks/234 ANN in R - Step 1.mp4 49.89 MB
21 K-Means Clustering/139 K-Means Clustering in Python.mp4 49.81 MB
16 Naive Bayes/119 Naive Bayes in R.mp4 49.79 MB
04 Simple Linear Regression/032 Simple Linear Regression in R - Step 4.mp4 49.16 MB
24 Apriori/162 Apriori in Python - Step 1.mp4 47.41 MB
39 XGBoost/285 XGBoost in R.mp4 47.26 MB
13 K-Nearest Neighbors (K-NN)/100 K-NN in Python.mp4 46.98 MB
07 Support Vector Regression (SVR)/067 SVR Intuition.mp4 46.59 MB
29 -------------------- Part 7 Natural Language Processing --------------------/190 Natural Language Processing in Python - Step 1.mp4 46.06 MB
35 Linear Discriminant Analysis (LDA)/270 LDA in Python.mp4 45.42 MB
05 Multiple Linear Regression/049 Multiple Linear Regression in R - Step 2.mp4 45.22 MB
02 -------------------- Part 1 Data Preprocessing --------------------/018 Feature Scaling.mp4 44.59 MB
27 Upper Confidence Bound (UCB)/173 Upper Confidence Bound in Python - Step 2.mp4 44.49 MB
31 Artificial Neural Networks/237 ANN in R - Step 4 (Last step).mp4 43.75 MB
38 Model Selection/278 k-Fold Cross Validation in R.mp4 43.63 MB
08 Decision Tree Regression/072 Decision Tree Regression in Python.mp4 43.44 MB
32 Convolutional Neural Networks/244 Step 4 - Full Connection.mp4 42.74 MB
14 Support Vector Machine (SVM)/104 SVM in Python.mp4 41.71 MB
32 Convolutional Neural Networks/242 Step 2 - Pooling.mp4 40.24 MB
04 Simple Linear Regression/028 Simple Linear Regression in Python - Step 4.mp4 39.37 MB
31 Artificial Neural Networks/228 ANN in Python - Step 5.mp4 39.36 MB
27 Upper Confidence Bound (UCB)/172 Upper Confidence Bound in Python - Step 1.mp4 39.01 MB
17 Decision Tree Classification/122 Decision Tree Classification in Python.mp4 38.85 MB
24 Apriori/160 Apriori in R - Step 2.mp4 38.81 MB
38 Model Selection/279 Grid Search in Python - Step 1.mp4 38.21 MB
31 Artificial Neural Networks/236 ANN in R - Step 3.mp4 37.85 MB
29 -------------------- Part 7 Natural Language Processing --------------------/209 Natural Language Processing in R - Step 9.mp4 37.69 MB
31 Artificial Neural Networks/224 ANN in Python - Step 1 - Installing Theano Tensorflow and Keras.mp4 37.45 MB
24 Apriori/163 Apriori in Python - Step 2.mp4 37.32 MB
28 Thompson Sampling/180 Thompson Sampling Intuition.mp4 37.27 MB
21 K-Means Clustering/140 K-Means Clustering in R.mp4 36.91 MB
06 Polynomial Regression/060 Python Regression Template.mp4 36.78 MB
34 Principal Component Analysis (PCA)/267 PCA in R - Step 3.mp4 36.73 MB
38 Model Selection/281 Grid Search in R.mp4 35.54 MB
24 Apriori/164 Apriori in Python - Step 3.mp4 35.3 MB
06 Polynomial Regression/057 Polynomial Regression in Python - Step 2.mp4 35.11 MB
24 Apriori/157 Apriori Intuition.mp4 35.02 MB
15 Kernel SVM/108 The Kernel Trick.mp4 34.72 MB
32 Convolutional Neural Networks/251 CNN in Python - Step 4.mp4 34.62 MB
27 Upper Confidence Bound (UCB)/177 Upper Confidence Bound in R - Step 2.mp4 34.1 MB
31 Artificial Neural Networks/231 ANN in Python - Step 8.mp4 34.03 MB
27 Upper Confidence Bound (UCB)/176 Upper Confidence Bound in R - Step 1.mp4 34.01 MB
07 Support Vector Regression (SVR)/069 SVR in R.mp4 33.73 MB
36 Kernel PCA/273 Kernel PCA in Python.mp4 33.38 MB
32 Convolutional Neural Networks/246 Softmax Cross-Entropy.mp4 33.23 MB
29 -------------------- Part 7 Natural Language Processing --------------------/199 Natural Language Processing in Python - Step 10.mp4 32.91 MB
38 Model Selection/277 k-Fold Cross Validation in Python.mp4 32.83 MB
05 Multiple Linear Regression/040 Multiple Linear Regression Intuition - Step 5.mp4 32.8 MB
06 Polynomial Regression/062 Polynomial Regression in R - Step 2.mp4 32.28 MB
02 -------------------- Part 1 Data Preprocessing --------------------/014 Missing Data.mp4 32.16 MB
34 Principal Component Analysis (PCA)/260 Principal Component Analysis (PCA) Intuition.mp4 32.11 MB
39 XGBoost/284 XGBoost in Python - Step 2.mp4 31.97 MB
34 Principal Component Analysis (PCA)/262 PCA in Python - Step 1.mp4 31.95 MB
06 Polynomial Regression/056 Polynomial Regression in Python - Step 1.mp4 31.64 MB
06 Polynomial Regression/065 R Regression Template.mp4 31.33 MB
30 -------------------- Part 8 Deep Learning --------------------/213 What is Deep Learning.mp4 31.31 MB
16 Naive Bayes/118 Naive Bayes in Python.mp4 31.14 MB
16 Naive Bayes/114 Naive Bayes Intuition.mp4 31.1 MB
32 Convolutional Neural Networks/240 Step 1 - Convolution Operation.mp4 31.02 MB
34 Principal Component Analysis (PCA)/265 PCA in R - Step 1.mp4 30.65 MB
32 Convolutional Neural Networks/248 CNN in Python - Step 1.mp4 30.6 MB
27 Upper Confidence Bound (UCB)/169 The Multi-Armed Bandit Problem.mp4 30.19 MB
21 K-Means Clustering/135 K-Means Clustering Intuition.mp4 29.97 MB
31 Artificial Neural Networks/215 The Neuron.mp4 29.86 MB
29 -------------------- Part 7 Natural Language Processing --------------------/193 Natural Language Processing in Python - Step 4.mp4 29.75 MB
29 -------------------- Part 7 Natural Language Processing --------------------/188 Natural Language Processing Intuition.mp4 29.69 MB
38 Model Selection/280 Grid Search in Python - Step 2.mp4 29.51 MB
32 Convolutional Neural Networks/239 What are convolutional neural networks.mp4 29.5 MB
27 Upper Confidence Bound (UCB)/170 Upper Confidence Bound (UCB) Intuition.mp4 29.32 MB
31 Artificial Neural Networks/223 Business Problem Description.mp4 29.23 MB
12 Logistic Regression/084 Logistic Regression Intuition.mp4 29.17 MB
34 Principal Component Analysis (PCA)/266 PCA in R - Step 2.mp4 29.02 MB
02 -------------------- Part 1 Data Preprocessing --------------------/012 Importing the Dataset.mp4 28.64 MB
06 Polynomial Regression/064 Polynomial Regression in R - Step 4.mp4 28.52 MB
31 Artificial Neural Networks/232 ANN in Python - Step 9.mp4 28.47 MB
31 Artificial Neural Networks/233 ANN in Python - Step 10.mp4 28.42 MB
10 Evaluating Regression Models Performance/080 Evaluating Regression Models Performance - Homeworks Final Part.mp4 28.35 MB
04 Simple Linear Regression/025 Simple Linear Regression in Python - Step 1.mp4 27.92 MB
32 Convolutional Neural Networks/257 CNN in Python - Step 10.mp4 27.74 MB
12 Logistic Regression/094 Logistic Regression in R - Step 3.mp4 27.44 MB
29 -------------------- Part 7 Natural Language Processing --------------------/191 Natural Language Processing in Python - Step 2.mp4 27.44 MB
10 Evaluating Regression Models Performance/081 Interpreting Linear Regression Coefficients.mp4 27.38 MB
35 Linear Discriminant Analysis (LDA)/268 Linear Discriminant Analysis (LDA) Intuition.mp4 26.98 MB
31 Artificial Neural Networks/218 How do Neural Networks learn.mp4 26.55 MB
02 -------------------- Part 1 Data Preprocessing --------------------/019 And here is our Data Preprocessing Template.mp4 25.86 MB
21 K-Means Clustering/137 K-Means Selecting The Number Of Clusters.mp4 25.68 MB
18 Random Forest Classification/124 Random Forest Classification Intuition.mp4 25.66 MB
34 Principal Component Analysis (PCA)/264 PCA in Python - Step 3.mp4 25.51 MB
05 Multiple Linear Regression/043 Multiple Linear Regression in Python - Step 3.mp4 25.48 MB
08 Decision Tree Regression/070 Decision Tree Regression Intuition.mp4 25.33 MB
25 Eclat/167 Eclat in R.mp4 25.26 MB
04 Simple Linear Regression/030 Simple Linear Regression in R - Step 2.mp4 24.87 MB
04 Simple Linear Regression/026 Simple Linear Regression in Python - Step 2.mp4 24.62 MB
01 Welcome to the course/005 Installing Python and Anaconda (Mac Linux Windows).mp4 23.96 MB
05 Multiple Linear Regression/044 Multiple Linear Regression in Python - Backward Elimination - Preparation.mp4 23.82 MB
31 Artificial Neural Networks/217 How do Neural Networks work.mp4 23.53 MB
05 Multiple Linear Regression/048 Multiple Linear Regression in R - Step 1.mp4 23.44 MB
01 Welcome to the course/007 Installing R and R Studio (Mac Linux Windows).mp4 23.21 MB
22 Hierarchical Clustering/143 Hierarchical Clustering Using Dendrograms.mp4 22.81 MB
29 -------------------- Part 7 Natural Language Processing --------------------/196 Natural Language Processing in Python - Step 7.mp4 22.13 MB
34 Principal Component Analysis (PCA)/263 PCA in Python - Step 2.mp4 22.07 MB
05 Multiple Linear Regression/052 Multiple Linear Regression in R - Backward Elimination - Homework Solution.mp4 21.95 MB
29 -------------------- Part 7 Natural Language Processing --------------------/202 Natural Language Processing in R - Step 2.mp4 21.66 MB
17 Decision Tree Classification/120 Decision Tree Classification Intuition.mp4 21.63 MB
10 Evaluating Regression Models Performance/079 Adjusted R-Squared Intuition.mp4 21.41 MB
39 XGBoost/283 XGBoost in Python - Step 1.mp4 21.39 MB
22 Hierarchical Clustering/148 HC in Python - Step 4.mp4 21.32 MB
06 Polynomial Regression/061 Polynomial Regression in R - Step 1.mp4 21.21 MB
02 -------------------- Part 1 Data Preprocessing --------------------/010 Get the dataset.mp4 21.15 MB
04 Simple Linear Regression/027 Simple Linear Regression in Python - Step 3.mp4 20.55 MB
19 Evaluating Classification Models Performance/131 CAP Curve.mp4 20.31 MB
14 Support Vector Machine (SVM)/102 SVM Intuition.mp4 19.92 MB
16 Naive Bayes/116 Naive Bayes Intuition (Extras).mp4 18.94 MB
29 -------------------- Part 7 Natural Language Processing --------------------/198 Natural Language Processing in Python - Step 9.mp4 18.9 MB
29 -------------------- Part 7 Natural Language Processing --------------------/194 Natural Language Processing in Python - Step 5.mp4 18.8 MB
31 Artificial Neural Networks/219 Gradient Descent.mp4 18.53 MB
31 Artificial Neural Networks/235 ANN in R - Step 2.mp4 18.24 MB
06 Polynomial Regression/059 Polynomial Regression in Python - Step 4.mp4 17.65 MB
12 Logistic Regression/091 Python Classification Template.mp4 17.58 MB
12 Logistic Regression/097 R Classification Template.mp4 17.5 MB
22 Hierarchical Clustering/142 Hierarchical Clustering How Dendrograms Work.mp4 17.46 MB
29 -------------------- Part 7 Natural Language Processing --------------------/208 Natural Language Processing in R - Step 8.mp4 17.23 MB
29 -------------------- Part 7 Natural Language Processing --------------------/203 Natural Language Processing in R - Step 3.mp4 16.89 MB
12 Logistic Regression/086 Logistic Regression in Python - Step 1.mp4 16.84 MB
31 Artificial Neural Networks/220 Stochastic Gradient Descent.mp4 16.82 MB
32 Convolutional Neural Networks/254 CNN in Python - Step 7.mp4 16.65 MB
05 Multiple Linear Regression/037 Multiple Linear Regression Intuition - Step 3.mp4 16.59 MB
22 Hierarchical Clustering/141 Hierarchical Clustering Intuition.mp4 16.52 MB
22 Hierarchical Clustering/147 HC in Python - Step 3.mp4 16.17 MB
29 -------------------- Part 7 Natural Language Processing --------------------/206 Natural Language Processing in R - Step 6.mp4 16.09 MB
12 Logistic Regression/092 Logistic Regression in R - Step 1.mp4 15.72 MB
15 Kernel SVM/109 Types of Kernel Functions.mp4 15.71 MB
09 Random Forest Regression/074 Random Forest Regression Intuition.mp4 15.65 MB
22 Hierarchical Clustering/146 HC in Python - Step 2.mp4 15.51 MB
15 Kernel SVM/107 Mapping to a higher dimension.mp4 15.39 MB
21 K-Means Clustering/136 K-Means Random Initialization Trap.mp4 15.36 MB
19 Evaluating Classification Models Performance/128 False Positives False Negatives.mp4 15.12 MB
31 Artificial Neural Networks/230 ANN in Python - Step 7.mp4 14.92 MB
12 Logistic Regression/093 Logistic Regression in R - Step 2.mp4 14.85 MB
31 Artificial Neural Networks/216 The Activation Function.mp4 14.75 MB
31 Artificial Neural Networks/226 ANN in Python - Step 3.mp4 14.62 MB
01 Welcome to the course/002 Why Machine Learning is the Future.mp4 14.48 MB
32 Convolutional Neural Networks/241 Step 1(b) - ReLU Layer.mp4 14.09 MB
28 Thompson Sampling/181 Algorithm Comparison UCB vs Thompson Sampling.mp4 14.08 MB
12 Logistic Regression/089 Logistic Regression in Python - Step 4.mp4 13.87 MB
22 Hierarchical Clustering/151 HC in R - Step 2.mp4 13.87 MB
05 Multiple Linear Regression/050 Multiple Linear Regression in R - Step 3.mp4 13.85 MB
22 Hierarchical Clustering/145 HC in Python - Step 1.mp4 13.77 MB
22 Hierarchical Clustering/154 HC in R - Step 5.mp4 13.68 MB
02 -------------------- Part 1 Data Preprocessing --------------------/011 Importing the Libraries.mp4 13.56 MB
16 Naive Bayes/115 Naive Bayes Intuition (Challenge Reveal).mp4 13.27 MB
19 Evaluating Classification Models Performance/132 CAP Curve Analysis.mp4 12.94 MB
05 Multiple Linear Regression/034 Dataset Business Problem Description.mp4 12.56 MB
27 Upper Confidence Bound (UCB)/175 Upper Confidence Bound in Python - Step 4.mp4 12.44 MB
32 Convolutional Neural Networks/252 CNN in Python - Step 5.mp4 12.38 MB
32 Convolutional Neural Networks/253 CNN in Python - Step 6.mp4 11.94 MB
31 Artificial Neural Networks/229 ANN in Python - Step 6.mp4 11.93 MB
12 Logistic Regression/095 Logistic Regression in R - Step 4.mp4 11.73 MB
04 Simple Linear Regression/021 How to get the dataset.mp4 11.71 MB
05 Multiple Linear Regression/033 How to get the dataset.mp4 11.71 MB
06 Polynomial Regression/055 How to get the dataset.mp4 11.71 MB
07 Support Vector Regression (SVR)/066 How to get the dataset.mp4 11.71 MB
08 Decision Tree Regression/071 How to get the dataset.mp4 11.71 MB
09 Random Forest Regression/075 How to get the dataset.mp4 11.71 MB
12 Logistic Regression/085 How to get the dataset.mp4 11.71 MB
13 K-Nearest Neighbors (K-NN)/099 How to get the dataset.mp4 11.71 MB
14 Support Vector Machine (SVM)/103 How to get the dataset.mp4 11.71 MB
15 Kernel SVM/110 How to get the dataset.mp4 11.71 MB
16 Naive Bayes/117 How to get the dataset.mp4 11.71 MB
17 Decision Tree Classification/121 How to get the dataset.mp4 11.71 MB
18 Random Forest Classification/125 How to get the dataset.mp4 11.71 MB
21 K-Means Clustering/138 How to get the dataset.mp4 11.71 MB
22 Hierarchical Clustering/144 How to get the dataset.mp4 11.71 MB
24 Apriori/158 How to get the dataset.mp4 11.71 MB
25 Eclat/166 How to get the dataset.mp4 11.71 MB
27 Upper Confidence Bound (UCB)/171 How to get the dataset.mp4 11.71 MB
28 Thompson Sampling/182 How to get the dataset.mp4 11.71 MB
29 -------------------- Part 7 Natural Language Processing --------------------/189 How to get the dataset.mp4 11.71 MB
31 Artificial Neural Networks/222 How to get the dataset.mp4 11.71 MB
32 Convolutional Neural Networks/247 How to get the dataset.mp4 11.71 MB
34 Principal Component Analysis (PCA)/261 How to get the dataset.mp4 11.71 MB
35 Linear Discriminant Analysis (LDA)/269 How to get the dataset.mp4 11.71 MB
36 Kernel PCA/272 How to get the dataset.mp4 11.71 MB
38 Model Selection/276 How to get the dataset.mp4 11.71 MB
39 XGBoost/282 How to get the dataset.mp4 11.71 MB
04 Simple Linear Regression/029 Simple Linear Regression in R - Step 1.mp4 11.52 MB
04 Simple Linear Regression/031 Simple Linear Regression in R - Step 3.mp4 11.42 MB
28 Thompson Sampling/184 Thompson Sampling in Python - Step 2.mp4 11.22 MB
12 Logistic Regression/087 Logistic Regression in Python - Step 2.mp4 11.1 MB
31 Artificial Neural Networks/221 Backpropagation.mp4 10.92 MB
25 Eclat/165 Eclat Intuition.mp4 10.65 MB
04 Simple Linear Regression/023 Simple Linear Regression Intuition - Step 1.mp4 10.52 MB
13 K-Nearest Neighbors (K-NN)/098 K-Nearest Neighbor Intuition.mp4 10.48 MB
22 Hierarchical Clustering/153 HC in R - Step 4.mp4 10.17 MB
22 Hierarchical Clustering/152 HC in R - Step 3.mp4 9.95 MB
22 Hierarchical Clustering/149 HC in Python - Step 5.mp4 9.92 MB
05 Multiple Linear Regression/042 Multiple Linear Regression in Python - Step 2.mp4 9.84 MB
01 Welcome to the course/001 Applications of Machine Learning.mp4 9.81 MB
10 Evaluating Regression Models Performance/078 R-Squared Intuition.mp4 9.8 MB
31 Artificial Neural Networks/227 ANN in Python - Step 4.mp4 9.69 MB
29 -------------------- Part 7 Natural Language Processing --------------------/207 Natural Language Processing in R - Step 7.mp4 9.59 MB
28 Thompson Sampling/186 Thompson Sampling in R - Step 2.mp4 9.56 MB
27 Upper Confidence Bound (UCB)/179 Upper Confidence Bound in R - Step 4.mp4 9.55 MB
06 Polynomial Regression/054 Polynomial Regression Intuition.mp4 9.44 MB
32 Convolutional Neural Networks/255 CNN in Python - Step 8.mp4 8.95 MB
19 Evaluating Classification Models Performance/129 Confusion Matrix.mp4 8.91 MB
22 Hierarchical Clustering/150 HC in R - Step 1.mp4 8.59 MB
29 -------------------- Part 7 Natural Language Processing --------------------/195 Natural Language Processing in Python - Step 6.mp4 8.32 MB
29 -------------------- Part 7 Natural Language Processing --------------------/204 Natural Language Processing in R - Step 4.mp4 8.24 MB
12 Logistic Regression/088 Logistic Regression in Python - Step 3.mp4 7.98 MB
32 Convolutional Neural Networks/245 Summary.mp4 7.91 MB
04 Simple Linear Regression/022 Dataset Business Problem Description.mp4 7.77 MB
32 Convolutional Neural Networks/249 CNN in Python - Step 2.mp4 7.2 MB
15 Kernel SVM/106 Kernel SVM Intuition.mp4 6.42 MB
04 Simple Linear Regression/024 Simple Linear Regression Intuition - Step 2.mp4 5.99 MB
32 Convolutional Neural Networks/238 Plan of attack.mp4 5.9 MB
29 -------------------- Part 7 Natural Language Processing --------------------/205 Natural Language Processing in R - Step 5.mp4 5.78 MB
05 Multiple Linear Regression/038 Multiple Linear Regression Intuition - Step 4.mp4 5.34 MB
31 Artificial Neural Networks/214 Plan of attack.mp4 4.74 MB
19 Evaluating Classification Models Performance/130 Accuracy Paradox.mp4 4.21 MB
29 -------------------- Part 7 Natural Language Processing --------------------/192 Natural Language Processing in Python - Step 3.mp4 4.16 MB
02 -------------------- Part 1 Data Preprocessing --------------------/009 Welcome to Part 1 - Data Preprocessing.mp4 3.52 MB
32 Convolutional Neural Networks/243 Step 3 - Flattening.mp4 3.27 MB
32 Convolutional Neural Networks/250 CNN in Python - Step 3.mp4 2.8 MB
01 Welcome to the course/004 Machine-Learning-A-Z-Q-A.pdf 2.26 MB
05 Multiple Linear Regression/036 Multiple Linear Regression Intuition - Step 2.mp4 2.03 MB
05 Multiple Linear Regression/035 Multiple Linear Regression Intuition - Step 1.mp4 2 MB
25 Eclat/167 Eclat.zip 48.54 KB
16 Naive Bayes/113 Bayes Theorem-ja.srt 37.31 KB
18 Random Forest Classification/127 Random Forest Classification in R-ja.srt 37.26 KB
36 Kernel PCA/274 Kernel PCA in R-ja.srt 36.8 KB
08 Decision Tree Regression/073 Decision Tree Regression in R-ja.srt 36.66 KB
32 Convolutional Neural Networks/256 CNN in Python - Step 9-ja.srt 35.69 KB
24 Apriori/161 Apriori in R - Step 3-ja.srt 35.63 KB
35 Linear Discriminant Analysis (LDA)/271 LDA in R-ja.srt 35.59 KB
18 Random Forest Classification/126 Random Forest Classification in Python-ja.srt 35.45 KB
31 Artificial Neural Networks/225 ANN in Python - Step 2-ja.srt 35.41 KB
07 Support Vector Regression (SVR)/068 SVR in Python-ja.srt 35.41 KB
24 Apriori/159 Apriori in R - Step 1-ja.srt 35.18 KB
16 Naive Bayes/113 Bayes Theorem-es.srt 34.64 KB
06 Polynomial Regression/058 Polynomial Regression in Python - Step 3-ja.srt 34.37 KB
16 Naive Bayes/113 Bayes Theorem-pt.srt 33.99 KB
16 Naive Bayes/113 Bayes Theorem-it.srt 33.97 KB
28 Thompson Sampling/183 Thompson Sampling in Python - Step 1-ja.srt 33.94 KB
06 Polynomial Regression/063 Polynomial Regression in R - Step 3-ja.srt 33.68 KB
32 Convolutional Neural Networks/244 Step 4 - Full Connection-ja.srt 33.63 KB
17 Decision Tree Classification/123 Decision Tree Classification in R-ja.srt 33.5 KB
18 Random Forest Classification/127 Random Forest Classification in R-es.srt 33.41 KB
12 Logistic Regression/090 Logistic Regression in Python - Step 5-ja.srt 33.3 KB
36 Kernel PCA/274 Kernel PCA in R-es.srt 33.27 KB
18 Random Forest Classification/127 Random Forest Classification in R-pt.srt 33.21 KB
16 Naive Bayes/113 Bayes Theorem-en.srt 33.15 KB
28 Thompson Sampling/185 Thompson Sampling in R - Step 1-ja.srt 33.05 KB
38 Model Selection/278 k-Fold Cross Validation in R-ja.srt 33.05 KB
15 Kernel SVM/111 Kernel SVM in Python-ja.srt 33.03 KB
18 Random Forest Classification/127 Random Forest Classification in R-it.srt 32.96 KB
36 Kernel PCA/274 Kernel PCA in R-pt.srt 32.89 KB
28 Thompson Sampling/180 Thompson Sampling Intuition-ja.srt 32.86 KB
08 Decision Tree Regression/073 Decision Tree Regression in R-pt.srt 32.8 KB
08 Decision Tree Regression/073 Decision Tree Regression in R-es.srt 32.78 KB
36 Kernel PCA/274 Kernel PCA in R-it.srt 32.68 KB
12 Logistic Regression/096 Logistic Regression in R - Step 5-ja.srt 32.6 KB
21 K-Means Clustering/139 K-Means Clustering in Python-ja.srt 32.54 KB
08 Decision Tree Regression/073 Decision Tree Regression in R-it.srt 32.5 KB
16 Naive Bayes/113 Bayes Theorem-tr.srt 32.36 KB
31 Artificial Neural Networks/234 ANN in R - Step 1-ja.srt 32.25 KB
18 Random Forest Classification/127 Random Forest Classification in R-tr.srt 32.24 KB
27 Upper Confidence Bound (UCB)/174 Upper Confidence Bound in Python - Step 3-ja.srt 32.2 KB
32 Convolutional Neural Networks/256 CNN in Python - Step 9-es.srt 32.08 KB
35 Linear Discriminant Analysis (LDA)/271 LDA in R-es.srt 31.99 KB
06 Polynomial Regression/058 Polynomial Regression in Python - Step 3-es.srt 31.97 KB
36 Kernel PCA/274 Kernel PCA in R-tr.srt 31.95 KB
24 Apriori/162 Apriori in Python - Step 1-ja.srt 31.93 KB
18 Random Forest Classification/126 Random Forest Classification in Python-es.srt 31.91 KB
02 -------------------- Part 1 Data Preprocessing --------------------/017 Splitting the Dataset into the Training set and Test set-ja.srt 31.72 KB
24 Apriori/161 Apriori in R - Step 3-es.srt 31.71 KB
39 XGBoost/285 XGBoost in R-ja.srt 31.63 KB
09 Random Forest Regression/077 Random Forest Regression in R-ja.srt 31.63 KB
09 Random Forest Regression/076 Random Forest Regression in Python-ja.srt 31.62 KB
18 Random Forest Classification/126 Random Forest Classification in Python-pt.srt 31.6 KB
24 Apriori/159 Apriori in R - Step 1-es.srt 31.54 KB
35 Linear Discriminant Analysis (LDA)/271 LDA in R-pt.srt 31.53 KB
07 Support Vector Regression (SVR)/068 SVR in Python-es.srt 31.52 KB
06 Polynomial Regression/058 Polynomial Regression in Python - Step 3-it.srt 31.47 KB
06 Polynomial Regression/058 Polynomial Regression in Python - Step 3-pt.srt 31.43 KB
32 Convolutional Neural Networks/256 CNN in Python - Step 9-pt.srt 31.4 KB
35 Linear Discriminant Analysis (LDA)/271 LDA in R-it.srt 31.31 KB
32 Convolutional Neural Networks/256 CNN in Python - Step 9-it.srt 31.3 KB
29 -------------------- Part 7 Natural Language Processing --------------------/210 Natural Language Processing in R - Step 10-ja.srt 31.29 KB
08 Decision Tree Regression/073 Decision Tree Regression in R-tr.srt 31.29 KB
18 Random Forest Classification/126 Random Forest Classification in Python-it.srt 31.23 KB
24 Apriori/161 Apriori in R - Step 3-it.srt 31.2 KB
24 Apriori/161 Apriori in R - Step 3-pt.srt 31.2 KB
18 Random Forest Classification/127 Random Forest Classification in R-en.srt 31.18 KB
24 Apriori/159 Apriori in R - Step 1-pt.srt 31.09 KB
06 Polynomial Regression/063 Polynomial Regression in R - Step 3-es.srt 31.06 KB
31 Artificial Neural Networks/225 ANN in Python - Step 2-es.srt 31.03 KB
07 Support Vector Regression (SVR)/068 SVR in Python-it.srt 31.03 KB
07 Support Vector Regression (SVR)/068 SVR in Python-pt.srt 31.03 KB
18 Random Forest Classification/126 Random Forest Classification in Python-tr.srt 30.98 KB
28 Thompson Sampling/183 Thompson Sampling in Python - Step 1-es.srt 30.97 KB
08 Decision Tree Regression/073 Decision Tree Regression in R-en.srt 30.91 KB
24 Apriori/159 Apriori in R - Step 1-it.srt 30.86 KB
36 Kernel PCA/274 Kernel PCA in R-en.srt 30.81 KB
06 Polynomial Regression/063 Polynomial Regression in R - Step 3-pt.srt 30.79 KB
32 Convolutional Neural Networks/246 Softmax Cross-Entropy-ja.srt 30.71 KB
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01 Welcome to the course/004 This PDF resource will help you a lot.html 2.35 KB
02 -------------------- Part 1 Data Preprocessing --------------------/013 For Python learners summary of Object-oriented programming classes objects.html 2.3 KB
29 -------------------- Part 7 Natural Language Processing --------------------/211 Homework Challenge.html 2.23 KB
29 -------------------- Part 7 Natural Language Processing --------------------/200 Homework Challenge.html 2.21 KB
01 Welcome to the course/006 Update Recommended Anaconda Version.html 2.17 KB
33 -------------------- Part 9 Dimensionality Reduction --------------------/259 Welcome to Part 9 - Dimensionality Reduction.html 2.12 KB
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01 Welcome to the course/008 BONUS Meet your instructors.html 1.89 KB
37 -------------------- Part 10 Model Selection Boosting --------------------/275 Welcome to Part 10 - Model Selection Boosting.html 1.74 KB
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03 -------------------- Part 2 Regression --------------------/020 Welcome to Part 2 - Regression.html 1.69 KB
11 -------------------- Part 3 Classification --------------------/083 Welcome to Part 3 - Classification.html 1.66 KB
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02 -------------------- Part 1 Data Preprocessing --------------------/016 WARNING - Update.html 1.6 KB
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23 -------------------- Part 5 Association Rule Learning --------------------/156 Welcome to Part 5 - Association Rule Learning.html 1.27 KB
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Udemy Course downloader.txt 94 B
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