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| [TGx]Downloaded from torrentgalaxy.to .txt |
585б |
| 0 |
223б |
| 1 |
64.08Кб |
| 1.1 Data_Set.csv |
580б |
| 1.1 Python Source Codes.zip |
7.46Кб |
| 1. Course Content.mp4 |
17.07Мб |
| 1. Course Content.srt |
6.43Кб |
| 1. Introduction.mp4 |
38.11Мб |
| 1. Introduction.mp4 |
17.03Мб |
| 1. Introduction.srt |
8.33Кб |
| 1. Introduction.srt |
4.69Кб |
| 1. Learning Types.mp4 |
45.44Мб |
| 1. Learning Types.srt |
8.92Кб |
| 1. Python Source Codes.html |
368б |
| 1. Reading and Modifying a Dataset.mp4 |
154.55Мб |
| 1. Reading and Modifying a Dataset.srt |
22.19Кб |
| 1. Simple and Multiple Linear Regression Concepts.mp4 |
212.19Мб |
| 1. Simple and Multiple Linear Regression Concepts.srt |
31.21Кб |
| 1. Supervised Learning Models - Introduction and Understanding the Data.mp4 |
233.75Мб |
| 1. Supervised Learning Models - Introduction and Understanding the Data.srt |
33.14Кб |
| 10 |
131.15Кб |
| 10.1 Data_New.csv |
201б |
| 10. Concatenation.mp4 |
65.88Мб |
| 10. Concatenation.srt |
8.05Кб |
| 10. Hierarchical Clustering Model Development.mp4 |
145.89Мб |
| 10. Hierarchical Clustering Model Development.srt |
17.64Кб |
| 10. Logistic Regression Concepts.mp4 |
10.85Мб |
| 10. Logistic Regression Concepts.srt |
3.45Кб |
| 10. Pandas3.mp4 |
117.83Мб |
| 10. Pandas3.srt |
16.64Кб |
| 10. Support Vector Regression Model Development.mp4 |
121.01Мб |
| 10. Support Vector Regression Model Development.srt |
11.43Кб |
| 11 |
985.44Кб |
| 11.1 Data_Set.csv |
580б |
| 11. Chapter 6 Quiz.html |
160б |
| 11. Chapter 7 Quiz.html |
160б |
| 11. Dummy Variable.mp4 |
57.59Мб |
| 11. Dummy Variable.srt |
7.90Кб |
| 11. Logistic Regression Model Development.mp4 |
112.12Мб |
| 11. Logistic Regression Model Development.srt |
11.95Кб |
| 11. Pandas4.mp4 |
203.04Мб |
| 11. Pandas4.srt |
26.69Кб |
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104.56Кб |
| 12. Model Evaluation Concepts.mp4 |
83.47Мб |
| 12. Model Evaluation Concepts.srt |
19.29Кб |
| 12. Normalization.mp4 |
186.87Мб |
| 12. Normalization.srt |
21.92Кб |
| 12. Visualization with Matplotlib1.mp4 |
99.45Мб |
| 12. Visualization with Matplotlib1.srt |
16.05Кб |
| 13 |
456.95Кб |
| 13. Chapter3 Quiz.html |
160б |
| 13. Model Evaluation - Calculating with Python.mp4 |
174.04Мб |
| 13. Model Evaluation - Calculating with Python.srt |
19.93Кб |
| 13. Visualization with Matplotlib2.mp4 |
205.24Мб |
| 13. Visualization with Matplotlib2.srt |
25.65Кб |
| 14 |
369.49Кб |
| 14. Chapter 5 Quiz.html |
160б |
| 14. Visualization with Matplotlib3.mp4 |
188.84Мб |
| 14. Visualization with Matplotlib3.srt |
19.60Кб |
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117.64Кб |
| 15. Visualization with Matplotlib4.mp4 |
142.99Мб |
| 15. Visualization with Matplotlib4.srt |
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14.96Кб |
| 16. Visualization with Matplotlib5.mp4 |
129.25Мб |
| 16. Visualization with Matplotlib5.srt |
14.44Кб |
| 17 |
354.56Кб |
| 17. Chapter 2 Quiz.html |
160б |
| 18 |
514.20Кб |
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372.05Кб |
| 2 |
597.38Кб |
| 2. Chapter 4 Quiz.html |
160б |
| 2. K-means Concepts1.mp4 |
44.53Мб |
| 2. K-means Concepts1.srt |
11.27Кб |
| 2. k-NN Concepts.mp4 |
48.03Мб |
| 2. k-NN Concepts.srt |
11.54Кб |
| 2. Multiple Linear Regression - Model Development.mp4 |
75.59Мб |
| 2. Multiple Linear Regression - Model Development.srt |
8.72Кб |
| 2. NumPy1.mp4 |
37.49Мб |
| 2. NumPy1.srt |
8.21Кб |
| 2. Statistics1.mp4 |
34.04Мб |
| 2. Statistics1.srt |
10.14Кб |
| 2. Support Vector Regression - Model Tuning.mp4 |
125.61Мб |
| 2. Support Vector Regression - Model Tuning.srt |
13.57Кб |
| 2. What is Machine Learning Some Basic Terms.mp4 |
25.82Мб |
| 2. What is Machine Learning Some Basic Terms.srt |
7.11Кб |
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| 3 |
639.27Кб |
| 3. Evaluation Metrics - Concepts.mp4 |
49.47Мб |
| 3. Evaluation Metrics - Concepts.srt |
12.64Кб |
| 3. K-means Concepts2.mp4 |
21.28Мб |
| 3. K-means Concepts2.srt |
7.15Кб |
| 3. K-Means - Model Tuning.mp4 |
15.30Мб |
| 3. K-Means - Model Tuning.srt |
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| 3. k-NN Model Development.mp4 |
140.65Мб |
| 3. k-NN Model Development.srt |
16.51Кб |
| 3. NumPy2.mp4 |
56.91Мб |
| 3. NumPy2.srt |
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| 3. Python Installation.html |
612б |
| 3. Statistics2.mp4 |
207.49Мб |
| 3. Statistics2.srt |
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| 4 |
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| 4. Evaluation Metrics - Implementation.mp4 |
159.90Мб |
| 4. Evaluation Metrics - Implementation.srt |
18.25Кб |
| 4. K-means Model Development1.mp4 |
35.98Мб |
| 4. K-means Model Development1.srt |
5.20Кб |
| 4. k-NN - Model Tuning.mp4 |
133.64Мб |
| 4. k-NN - Model Tuning.srt |
13.05Кб |
| 4. k-NN Training-Set and Test-Set Creation.mp4 |
228.42Мб |
| 4. k-NN Training-Set and Test-Set Creation.srt |
27.76Кб |
| 4. NumPy3.mp4 |
84.52Мб |
| 4. NumPy3.srt |
13.58Кб |
| 4. Python IDE.mp4 |
7.51Мб |
| 4. Python IDE.srt |
2.75Кб |
| 4. Statistics3 - Covariance.mp4 |
107.48Мб |
| 4. Statistics3 - Covariance.srt |
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168.06Кб |
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792.39Кб |
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371.17Кб |
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542.38Кб |
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992.18Кб |
| 5 |
523.76Кб |
| 5. Decision Tree Concepts.mp4 |
25.62Мб |
| 5. Decision Tree Concepts.srt |
7.59Кб |
| 5. IDE Installation.mp4 |
22.28Мб |
| 5. IDE Installation.srt |
3.25Кб |
| 5. K-means Model Development2.mp4 |
103.83Мб |
| 5. K-means Model Development2.srt |
13.80Кб |
| 5. Missing Values1.mp4 |
129.64Мб |
| 5. Missing Values1.srt |
14.43Кб |
| 5. NumPy4.mp4 |
56.56Мб |
| 5. NumPy4.srt |
7.69Кб |
| 5. Overfitting and Underfitting.mp4 |
72.09Мб |
| 5. Overfitting and Underfitting.srt |
11.20Кб |
| 5. Polynomial Linear Regression Concepts.mp4 |
26.39Мб |
| 5. Polynomial Linear Regression Concepts.srt |
6.67Кб |
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659.67Кб |
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572.71Кб |
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| 57 |
1011.74Кб |
| 58 |
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| 59 |
34.76Кб |
| 6 |
47.10Кб |
| 6. Decision Tree Model Development.mp4 |
66.84Мб |
| 6. Decision Tree Model Development.srt |
7.03Кб |
| 6. Installation of Required Libraries.mp4 |
70.78Мб |
| 6. Installation of Required Libraries.srt |
8.57Кб |
| 6. K-means - Model Evaluation.mp4 |
102.40Мб |
| 6. K-means - Model Evaluation.srt |
11.55Кб |
| 6. Missing Values2.mp4 |
219.38Мб |
| 6. Missing Values2.srt |
22.39Кб |
| 6. NumPy5.mp4 |
152.64Мб |
| 6. NumPy5.srt |
19.13Кб |
| 6. Polynomial Linear Regression Model Development.mp4 |
206.95Мб |
| 6. Polynomial Linear Regression Model Development.srt |
20.75Кб |
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| 7 |
780.14Кб |
| 7. DBSCAN Concepts.mp4 |
26.85Мб |
| 7. DBSCAN Concepts.srt |
6.28Кб |
| 7. Decision Tree - Cross Validation.mp4 |
54.64Мб |
| 7. Decision Tree - Cross Validation.srt |
9.69Кб |
| 7. NumPy6.mp4 |
134.50Мб |
| 7. NumPy6.srt |
18.48Кб |
| 7. Outlier Detection1.mp4 |
73.20Мб |
| 7. Outlier Detection1.srt |
13.32Кб |
| 7. Random Forest Concepts.mp4 |
30.23Мб |
| 7. Random Forest Concepts.srt |
7.43Кб |
| 7. Spyder Interface.mp4 |
46.36Мб |
| 7. Spyder Interface.srt |
8.94Кб |
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150.04Кб |
| 8 |
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| 8. DBSCAN Model Development.mp4 |
86.87Мб |
| 8. DBSCAN Model Development.srt |
10.41Кб |
| 8. Naive Bayes Concepts.mp4 |
59.23Мб |
| 8. Naive Bayes Concepts.srt |
16.27Кб |
| 8. Outlier Detection2.mp4 |
130.67Мб |
| 8. Outlier Detection2.srt |
15.18Кб |
| 8. Pandas1.mp4 |
95.61Мб |
| 8. Pandas1.srt |
17.33Кб |
| 8. Random Forest Model Development.mp4 |
246.24Мб |
| 8. Random Forest Model Development.srt |
24.62Кб |
| 9 |
158.77Кб |
| 9. Hierarchical Clustering Concepts.mp4 |
24.29Мб |
| 9. Hierarchical Clustering Concepts.srt |
6.53Кб |
| 9. Naive Bayes Model Development.mp4 |
58.95Мб |
| 9. Naive Bayes Model Development.srt |
6.84Кб |
| 9. Outlier Detection3.mp4 |
31.01Мб |
| 9. Outlier Detection3.srt |
3.55Кб |
| 9. Pandas2.mp4 |
116.94Мб |
| 9. Pandas2.srt |
17.33Кб |
| 9. Support Vector Regression Concepts.mp4 |
26.97Мб |
| 9. Support Vector Regression Concepts.srt |
7.50Кб |
| TutsNode.com.txt |
63б |