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Please note that this page does not hosts or makes available any of the listed filenames. You
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| [FreeCourseSite.com].txt |
1.07KB |
| [FreeCourseSite.com].url |
127B |
| [HaxTech.me].txt |
1.05KB |
| [HaxTech.me].url |
123B |
| 001 Applications of Machine Learning.mp4 |
9.81MB |
| 001 Data Preprocessing.html |
4.62KB |
| 002 Simple Linear Regression.html |
4.47KB |
| 002 Why Machine Learning is the Future.mp4 |
14.48MB |
| 003 Installing R and R Studio MAC Windows.mp4 |
23.21MB |
| 003 Multiple Linear Regression.html |
4.68KB |
| 004 Installing Python and Anaconda MAC Windows.mp4 |
23.96MB |
| 004 Logistic Regression.html |
4.13KB |
| 005 BONUS Meet your instructors.html |
1.33KB |
| 005 K-Nearest Neighbor.html |
4.07KB |
| 006 K-Means Clustering.html |
4.12KB |
| 006 Welcome to Part 1 - Data Preprocessing.mp4 |
3.52MB |
| 007 Get the dataset.mp4 |
21.15MB |
| 007 Hierarchical Clustering.html |
4.38KB |
| 008 Importing the Libraries.mp4 |
13.56MB |
| 009 Importing the Dataset.mp4 |
28.64MB |
| 011 Missing Data.mp4 |
39.32MB |
| 012 Categorical Data.mp4 |
52.88MB |
| 013 Splitting the Dataset into the Training set and Test set.mp4 |
50.91MB |
| 014 Feature Scaling.mp4 |
44.59MB |
| 015 And here is our Data Preprocessing Template.mp4 |
25.86MB |
| 016 Welcome to Part 2 - Regression.html |
1.12KB |
| 017 How to get the dataset.mp4 |
11.71MB |
| 018 Dataset Business Problem Description.mp4 |
7.77MB |
| 019 Simple Linear Regression Intuition - Step 1.mp4 |
10.52MB |
| 020 Simple Linear Regression Intuition - Step 2.mp4 |
5.99MB |
| 021 Simple Linear Regression in Python - Step 1.mp4 |
27.92MB |
| 022 Simple Linear Regression in Python - Step 2.mp4 |
24.62MB |
| 023 Simple Linear Regression in Python - Step 3.mp4 |
20.55MB |
| 024 Simple Linear Regression in Python - Step 4.mp4 |
39.37MB |
| 025 Simple Linear Regression in R - Step 1.mp4 |
11.52MB |
| 026 Simple Linear Regression in R - Step 2.mp4 |
24.87MB |
| 027 Simple Linear Regression in R - Step 3.mp4 |
11.42MB |
| 028 Simple Linear Regression in R - Step 4.mp4 |
49.16MB |
| 029 How to get the dataset.mp4 |
11.71MB |
| 030 Dataset Business Problem Description.mp4 |
12.56MB |
| 031 Multiple Linear Regression Intuition - Step 1.mp4 |
2.00MB |
| 032 Multiple Linear Regression Intuition - Step 2.mp4 |
2.03MB |
| 033 Multiple Linear Regression Intuition - Step 3.mp4 |
16.59MB |
| 034 Multiple Linear Regression Intuition - Step 4.mp4 |
5.34MB |
| 035 Multiple Linear Regression Intuition - Step 5.mp4 |
32.80MB |
| 036 Multiple Linear Regression in Python - Step 1.mp4 |
52.18MB |
| 037 Multiple Linear Regression in Python - Step 2.mp4 |
9.84MB |
| 038 Multiple Linear Regression in Python - Step 3.mp4 |
25.48MB |
| 039 Multiple Linear Regression in Python - Backward Elimination - Preparation.mp4 |
54.54MB |
| 040 Multiple Linear Regression in Python - Backward Elimination - HOMEWORK.mp4 |
59.14MB |
| 041 Multiple Linear Regression in Python - Backward Elimination - Homework Solution.mp4 |
54.26MB |
| 042 Multiple Linear Regression in R - Step 1.mp4 |
23.44MB |
| 043 Multiple Linear Regression in R - Step 2.mp4 |
45.22MB |
| 044 Multiple Linear Regression in R - Step 3.mp4 |
13.85MB |
| 045 Multiple Linear Regression in R - Backward Elimination - HOMEWORK.mp4 |
50.78MB |
| 046 Multiple Linear Regression in R - Backward Elimination - Homework Solution.mp4 |
21.95MB |
| 047 Polynomial Regression Intuition.mp4 |
9.44MB |
| 048 How to get the dataset.mp4 |
11.71MB |
| 049 Polynomial Regression in Python - Step 1.mp4 |
31.64MB |
| 050 Polynomial Regression in Python - Step 2.mp4 |
35.11MB |
| 051 Polynomial Regression in Python - Step 3.mp4 |
54.50MB |
| 052 Polynomial Regression in Python - Step 4.mp4 |
17.65MB |
| 053 Python Regression Template.mp4 |
36.78MB |
| 054 Polynomial Regression in R - Step 1.mp4 |
21.21MB |
| 055 Polynomial Regression in R - Step 2.mp4 |
32.28MB |
| 056 Polynomial Regression in R - Step 3.mp4 |
54.80MB |
| 057 Polynomial Regression in R - Step 4.mp4 |
28.52MB |
| 058 R Regression Template.mp4 |
31.33MB |
| 059 How to get the dataset.mp4 |
11.71MB |
| 060 SVR in Python.mp4 |
60.22MB |
| 061 SVR in R.mp4 |
33.73MB |
| 062 Decision Tree Regression Intuition.mp4 |
25.33MB |
| 063 How to get the dataset.mp4 |
11.71MB |
| 064 Decision Tree Regression in Python.mp4 |
43.44MB |
| 065 Decision Tree Regression in R.mp4 |
56.23MB |
| 066 Random Forest Regression Intuition.mp4 |
15.65MB |
| 067 How to get the dataset.mp4 |
11.71MB |
| 068 Random Forest Regression in Python.mp4 |
52.69MB |
| 069 Random Forest Regression in R.mp4 |
51.86MB |
| 070 R-Squared Intuition.mp4 |
9.80MB |
| 071 Adjusted R-Squared Intuition.mp4 |
21.41MB |
| 072 Evaluating Regression Models Performance - Homeworks Final Part.mp4 |
28.35MB |
| 073 Interpreting Linear Regression Coefficients.mp4 |
27.38MB |
| 074 Conclusion of Part 2 - Regression.html |
3.34KB |
| 075 Welcome to Part 3 - Classification.html |
1.08KB |
| 076 Logistic Regression Intuition.mp4 |
29.17MB |
| 077 How to get the dataset.mp4 |
11.71MB |
| 078 Logistic Regression in Python - Step 1.mp4 |
16.84MB |
| 079 Logistic Regression in Python - Step 2.mp4 |
11.10MB |
| 080 Logistic Regression in Python - Step 3.mp4 |
7.98MB |
| 081 Logistic Regression in Python - Step 4.mp4 |
13.87MB |
| 082 Logistic Regression in Python - Step 5.mp4 |
53.15MB |
| 083 Python Classification Template.mp4 |
17.58MB |
| 084 Logistic Regression in R - Step 1.mp4 |
15.72MB |
| 085 Logistic Regression in R - Step 2.mp4 |
14.85MB |
| 086 Logistic Regression in R - Step 3.mp4 |
27.44MB |
| 087 Logistic Regression in R - Step 4.mp4 |
11.73MB |
| 088 Logistic Regression in R - Step 5.mp4 |
93.76MB |
| 089 R Classification Template.mp4 |
17.50MB |
| 090 K-Nearest Neighbor Intuition.mp4 |
10.48MB |
| 091 How to get the dataset.mp4 |
11.71MB |
| 092 K-NN in Python.mp4 |
46.98MB |
| 093 K-NN in R.mp4 |
55.77MB |
| 094 SVM Intuition.mp4 |
19.92MB |
| 095 How to get the dataset.mp4 |
11.71MB |
| 096 SVM in Python.mp4 |
41.71MB |
| 097 SVM in R.mp4 |
65.31MB |
| 098 Kernel SVM Intuition.mp4 |
6.42MB |
| 099 Mapping to a higher dimension.mp4 |
15.39MB |
| 100 The Kernel Trick.mp4 |
34.72MB |
| 101 Types of Kernel Functions.mp4 |
15.71MB |
| 102 How to get the dataset.mp4 |
11.71MB |
| 103 Kernel SVM in Python.mp4 |
54.86MB |
| 104 Kernel SVM in R.mp4 |
52.82MB |
| 105 Bayes Theorem.mp4 |
50.43MB |
| 106 Naive Bayes Intuition.mp4 |
31.10MB |
| 107 Naive Bayes Intuition Challenge Reveal.mp4 |
13.27MB |
| 108 Naive Bayes Intuition Extras.mp4 |
18.94MB |
| 109 How to get the dataset.mp4 |
11.71MB |
| 110 Naive Bayes in Python.mp4 |
31.14MB |
| 111 Naive Bayes in R.mp4 |
49.79MB |
| 112 Decision Tree Classification Intuition.mp4 |
21.63MB |
| 113 How to get the dataset.mp4 |
11.71MB |
| 114 Decision Tree Classification in Python.mp4 |
38.85MB |
| 115 Decision Tree Classification in R.mp4 |
68.18MB |
| 116 Random Forest Classification Intuition.mp4 |
25.66MB |
| 117 How to get the dataset.mp4 |
11.71MB |
| 118 Random Forest Classification in Python.mp4 |
62.04MB |
| 119 Random Forest Classification in R.mp4 |
64.11MB |
| 120 False Positives False Negatives.mp4 |
15.12MB |
| 121 Confusion Matrix.mp4 |
8.91MB |
| 122 Accuracy Paradox.mp4 |
4.21MB |
| 123 CAP Curve.mp4 |
20.31MB |
| 124 CAP Curve Analysis.mp4 |
12.94MB |
| 125 Conclusion of Part 3 - Classification.html |
3.86KB |
| 126 Welcome to Part 4 - Clustering.html |
1004B |
| 127 K-Means Clustering Intuition.mp4 |
29.97MB |
| 128 K-Means Random Initialization Trap.mp4 |
15.36MB |
| 129 K-Means Selecting The Number Of Clusters.mp4 |
25.68MB |
| 130 How to get the dataset.mp4 |
11.71MB |
| 131 K-Means Clustering in Python.mp4 |
49.81MB |
| 132 K-Means Clustering in R.mp4 |
36.91MB |
| 133 Hierarchical Clustering Intuition.mp4 |
16.52MB |
| 134 Hierarchical Clustering How Dendrograms Work.mp4 |
17.46MB |
| 135 Hierarchical Clustering Using Dendrograms.mp4 |
22.81MB |
| 136 How to get the dataset.mp4 |
11.71MB |
| 137 HC in Python - Step 1.mp4 |
13.77MB |
| 138 HC in Python - Step 2.mp4 |
15.51MB |
| 139 HC in Python - Step 3.mp4 |
16.17MB |
| 140 HC in Python - Step 4.mp4 |
21.32MB |
| 141 HC in Python - Step 5.mp4 |
9.92MB |
| 142 HC in R - Step 1.mp4 |
8.59MB |
| 143 HC in R - Step 2.mp4 |
13.87MB |
| 144 HC in R - Step 3.mp4 |
9.95MB |
| 145 HC in R - Step 4.mp4 |
10.17MB |
| 146 HC in R - Step 5.mp4 |
13.68MB |
| 147 Conclusion of Part 4 - Clustering.html |
809B |
| 148 Welcome to Part 5 - Association Rule Learning.html |
713B |
| 149 Apriori Intuition.mp4 |
35.02MB |
| 150 How to get the dataset.mp4 |
11.71MB |
| 151 Apriori in R - Step 1.mp4 |
52.83MB |
| 152 Apriori in R - Step 2.mp4 |
38.81MB |
| 153 Apriori in R - Step 3.mp4 |
56.51MB |
| 154 Apriori in Python - Step 1.mp4 |
47.41MB |
| 155 Apriori in Python - Step 2.mp4 |
37.32MB |
| 156 Apriori in Python - Step 3.mp4 |
35.30MB |
| 157 Eclat Intuition.mp4 |
10.65MB |
| 158 How to get the dataset.mp4 |
11.71MB |
| 159 Eclat in R.mp4 |
25.26MB |
| 160 Welcome to Part 6 - Reinforcement Learning.html |
1.09KB |
| 161 The Multi-Armed Bandit Problem.mp4 |
30.19MB |
| 162 Upper Confidence Bound UCB Intuition.mp4 |
29.32MB |
| 163 How to get the dataset.mp4 |
11.71MB |
| 164 Upper Confidence Bound in Python - Step 1.mp4 |
39.01MB |
| 165 Upper Confidence Bound in Python - Step 2.mp4 |
44.49MB |
| 166 Upper Confidence Bound in Python - Step 3.mp4 |
53.71MB |
| 167 Upper Confidence Bound in Python - Step 4.mp4 |
12.44MB |
| 168 Upper Confidence Bound in R - Step 1.mp4 |
34.01MB |
| 169 Upper Confidence Bound in R - Step 2.mp4 |
34.10MB |
| 170 Upper Confidence Bound in R - Step 3.mp4 |
57.84MB |
| 171 Upper Confidence Bound in R - Step 4.mp4 |
9.55MB |
| 172 Thompson Sampling Intuition.mp4 |
37.27MB |
| 173 Algorithm Comparison UCB vs Thompson Sampling.mp4 |
14.08MB |
| 174 How to get the dataset.mp4 |
11.71MB |
| 175 Thompson Sampling in Python - Step 1.mp4 |
55.52MB |
| 176 Thompson Sampling in Python - Step 2.mp4 |
11.22MB |
| 177 Thompson Sampling in R - Step 1.mp4 |
51.04MB |
| 178 Thompson Sampling in R - Step 2.mp4 |
9.56MB |
| 179 Welcome to Part 7 - Natural Language Processing.html |
2.00KB |
| 180 How to get the dataset.mp4 |
11.71MB |
| 181 Natural Language Processing in Python - Step 1.mp4 |
46.06MB |
| 182 Natural Language Processing in Python - Step 2.mp4 |
27.44MB |
| 183 Natural Language Processing in Python - Step 3.mp4 |
4.16MB |
| 184 Natural Language Processing in Python - Step 4.mp4 |
29.75MB |
| 185 Natural Language Processing in Python - Step 5.mp4 |
18.80MB |
| 186 Natural Language Processing in Python - Step 6.mp4 |
8.32MB |
| 187 Natural Language Processing in Python - Step 7.mp4 |
22.13MB |
| 188 Natural Language Processing in Python - Step 8.mp4 |
52.02MB |
| 189 Natural Language Processing in Python - Step 9.mp4 |
18.90MB |
| 190 Natural Language Processing in Python - Step 10.mp4 |
32.91MB |
| 191 Homework Challenge.html |
1.65KB |
| 192 Natural Language Processing in R - Step 1.mp4 |
51.20MB |
| 193 Natural Language Processing in R - Step 2.mp4 |
21.66MB |
| 194 Natural Language Processing in R - Step 3.mp4 |
16.89MB |
| 195 Natural Language Processing in R - Step 4.mp4 |
8.24MB |
| 196 Natural Language Processing in R - Step 5.mp4 |
5.78MB |
| 197 Natural Language Processing in R - Step 6.mp4 |
16.09MB |
| 198 Natural Language Processing in R - Step 7.mp4 |
9.59MB |
| 199 Natural Language Processing in R - Step 8.mp4 |
17.23MB |
| 200 Natural Language Processing in R - Step 9.mp4 |
37.69MB |
| 201 Natural Language Processing in R - Step 10.mp4 |
54.14MB |
| 202 Homework Challenge.html |
1.68KB |
| 203 Welcome to Part 8 - Deep Learning.html |
1.15KB |
| 204 What is Deep Learning.mp4 |
31.31MB |
| 205 Plan of attack.mp4 |
4.74MB |
| 206 The Neuron.mp4 |
29.86MB |
| 207 The Activation Function.mp4 |
14.75MB |
| 208 How do Neural Networks work.mp4 |
23.53MB |
| 209 How do Neural Networks learn.mp4 |
26.55MB |
| 210 Gradient Descent.mp4 |
18.53MB |
| 211 Stochastic Gradient Descent.mp4 |
16.82MB |
| 212 Backpropagation.mp4 |
10.92MB |
| 213 How to get the dataset.mp4 |
11.71MB |
| 214 Business Problem Description.mp4 |
29.23MB |
| 215 ANN in Python - Step 1 - Installing Theano Tensorflow and Keras.mp4 |
37.45MB |
| 216 ANN in Python - Step 2.mp4 |
84.87MB |
| 217 ANN in Python - Step 3.mp4 |
14.62MB |
| 218 ANN in Python - Step 4.mp4 |
9.69MB |
| 219 ANN in Python - Step 5.mp4 |
39.36MB |
| 220 ANN in Python - Step 6.mp4 |
11.93MB |
| 221 ANN in Python - Step 7.mp4 |
14.92MB |
| 222 ANN in Python - Step 8.mp4 |
34.03MB |
| 223 ANN in Python - Step 9.mp4 |
28.47MB |
| 224 ANN in Python - Step 10.mp4 |
28.42MB |
| 225 ANN in R - Step 1.mp4 |
49.89MB |
| 226 ANN in R - Step 2.mp4 |
18.24MB |
| 227 ANN in R - Step 3.mp4 |
37.85MB |
| 228 ANN in R - Step 4 Last step.mp4 |
43.75MB |
| 229 Plan of attack.mp4 |
5.90MB |
| 230 What are convolutional neural networks.mp4 |
29.50MB |
| 231 Step 1 - Convolution Operation.mp4 |
31.02MB |
| 232 Step 1b - ReLU Layer.mp4 |
14.09MB |
| 233 Step 2 - Pooling.mp4 |
40.24MB |
| 234 Step 3 - Flattening.mp4 |
3.27MB |
| 235 Step 4 - Full Connection.mp4 |
42.74MB |
| 236 Summary.mp4 |
7.91MB |
| 237 Softmax Cross-Entropy.mp4 |
33.23MB |
| 238 How to get the dataset.mp4 |
11.71MB |
| 239 CNN in Python - Step 1.mp4 |
30.60MB |
| 240 CNN in Python - Step 2.mp4 |
7.20MB |
| 241 CNN in Python - Step 3.mp4 |
2.80MB |
| 242 CNN in Python - Step 4.mp4 |
34.62MB |
| 243 CNN in Python - Step 5.mp4 |
12.38MB |
| 244 CNN in Python - Step 6.mp4 |
11.94MB |
| 245 CNN in Python - Step 7.mp4 |
16.65MB |
| 246 CNN in Python - Step 8.mp4 |
8.95MB |
| 247 CNN in Python - Step 9.mp4 |
62.41MB |
| 248 CNN in Python - Step 10.mp4 |
27.74MB |
| 249 CNN in R.html |
2.65KB |
| 250 Welcome to Part 9 - Dimensionality Reduction.html |
1.57KB |
| 251 How to get the dataset.mp4 |
11.71MB |
| 252 PCA in Python - Step 1.mp4 |
31.95MB |
| 253 PCA in Python - Step 2.mp4 |
22.07MB |
| 254 PCA in Python - Step 3.mp4 |
25.51MB |
| 255 PCA in R - Step 1.mp4 |
30.65MB |
| 256 PCA in R - Step 2.mp4 |
29.02MB |
| 257 PCA in R - Step 3.mp4 |
36.73MB |
| 258 How to get the dataset.mp4 |
11.71MB |
| 259 LDA in Python.mp4 |
45.42MB |
| 260 LDA in R.mp4 |
51.29MB |
| 261 How to get the dataset.mp4 |
11.71MB |
| 262 Kernel PCA in Python.mp4 |
33.38MB |
| 263 Kernel PCA in R.mp4 |
56.57MB |
| 264 Welcome to Part 10 - Model Selection Boosting.html |
1.19KB |
| 265 How to get the dataset.mp4 |
11.71MB |
| 266 k-Fold Cross Validation in Python.mp4 |
32.83MB |
| 267 k-Fold Cross Validation in R.mp4 |
43.63MB |
| 268 Grid Search in Python - Step 1.mp4 |
38.21MB |
| 269 Grid Search in Python - Step 2.mp4 |
29.51MB |
| 270 Grid Search in R.mp4 |
35.54MB |
| 271 How to get the dataset.mp4 |
11.71MB |
| 272 XGBoost in Python - Step 1.mp4 |
21.39MB |
| 273 XGBoost in Python - Step 2.mp4 |
31.97MB |
| 274 XGBoost in R.mp4 |
47.26MB |
| 275 YOUR SPECIAL BONUS.html |
5.02KB |
| Eclat.zip |
48.54KB |
| SVM.zip |
8.27KB |