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| [TGx]Downloaded from torrentgalaxy.to .txt |
585б |
| 1. Install Anaconda package.mp4 |
48.10Мб |
| 1. Install Anaconda package.srt |
7.29Кб |
| 1. Introduction to Course.mp4 |
11.97Мб |
| 1. Introduction to Course.srt |
2.41Кб |
| 1. Introduction to Deep Learning.mp4 |
36.87Мб |
| 1. Introduction to Deep Learning.srt |
6.91Кб |
| 1. Introduction to Supervised Learning Algorithms.mp4 |
6.26Мб |
| 1. Introduction to Supervised Learning Algorithms.srt |
1.34Кб |
| 1. Review Unsupervised Learning Algorithms.mp4 |
8.52Мб |
| 1. Review Unsupervised Learning Algorithms.srt |
1.83Кб |
| 10. Create K-means Clustering Algorithm Model in Python - 2.mp4 |
32.95Мб |
| 10. Create K-means Clustering Algorithm Model in Python - 2.srt |
3.73Кб |
| 10. Machine Leaning Types.html |
165б |
| 10. P-Value.mp4 |
17.43Мб |
| 10. P-Value.srt |
4.23Кб |
| 10. The Newer Version of Keras Python code to Create the Model and Add the Layers.html |
1.26Кб |
| 11. Association Rules (Market Basket Analysis).mp4 |
52.22Мб |
| 11. Association Rules (Market Basket Analysis).srt |
11.50Кб |
| 11. Course Rating.html |
508б |
| 11. Create Artificial Neural Network Model in Python Part-4.mp4 |
22.00Мб |
| 11. Create Artificial Neural Network Model in Python Part-4.srt |
2.29Кб |
| 11. Simple Linear Regression.mp4 |
3.75Мб |
| 11. Simple Linear Regression.srt |
1007б |
| 12.1 GroceryStoreDataSet.csv |
543б |
| 12. Concepts used in Machine Learning (Important).html |
228б |
| 12. Course Rating.html |
508б |
| 12. Overview on the business problem data.mp4 |
13.47Мб |
| 12. Overview on the business problem data.srt |
1.98Кб |
| 13.1 apyori.py |
14.21Кб |
| 13.1 Study_Hours.csv |
287б |
| 13.2 AR.py |
560б |
| 13. Create Association Rules (Market Basket Analysis) Model in Python - 1.mp4 |
69.41Мб |
| 13. Create Association Rules (Market Basket Analysis) Model in Python - 1.srt |
10.30Кб |
| 13. Overview on the dataset.mp4 |
7.89Мб |
| 13. Overview on the dataset.srt |
1.52Кб |
| 14.1 SLR.py |
1.24Кб |
| 14. Create Association Rules (Market Basket Analysis) Model in Python - 2.mp4 |
33.26Мб |
| 14. Create Association Rules (Market Basket Analysis) Model in Python - 2.srt |
5.08Кб |
| 14. Create Simple Linear Regression Model in Python-Part 1.mp4 |
30.86Мб |
| 14. Create Simple Linear Regression Model in Python-Part 1.srt |
5.48Кб |
| 15. Create Association Rules (Market Basket Analysis) Model in Python - 3.mp4 |
28.61Мб |
| 15. Create Association Rules (Market Basket Analysis) Model in Python - 3.srt |
2.77Кб |
| 15. Create Simple Linear Regression Model in Python-Part 2.mp4 |
129.27Мб |
| 15. Create Simple Linear Regression Model in Python-Part 2.srt |
13.22Кб |
| 16. Create Simple Linear Regression Model in Python-Part 3.mp4 |
66.15Мб |
| 16. Create Simple Linear Regression Model in Python-Part 3.srt |
6.36Кб |
| 17. Create Simple Linear Regression Model in Python-Part 4.mp4 |
70.30Мб |
| 17. Create Simple Linear Regression Model in Python-Part 4.srt |
6.95Кб |
| 18. Multiple Linear Regression.mp4 |
14.19Мб |
| 18. Multiple Linear Regression.srt |
2.93Кб |
| 19. Dummy Variables.mp4 |
36.36Мб |
| 19. Dummy Variables.srt |
5.76Кб |
| 2. Course Contents.mp4 |
10.10Мб |
| 2. Course Contents.srt |
1.67Кб |
| 2. Hierarchical Clustering Algorithm.mp4 |
9.87Мб |
| 2. Hierarchical Clustering Algorithm.srt |
4.07Кб |
| 2. Types of Variables.mp4 |
10.31Мб |
| 2. Types of Variables.srt |
2.63Кб |
| 2. Use Deep Learning in Classification.mp4 |
14.07Мб |
| 2. Use Deep Learning in Classification.srt |
2.75Кб |
| 20. Dummy Variables Trap.html |
612б |
| 21. Step-wise Approach.mp4 |
28.78Мб |
| 21. Step-wise Approach.srt |
6.96Кб |
| 22. Assumptions of Multiple Linear Regression.mp4 |
31.31Мб |
| 22. Assumptions of Multiple Linear Regression.srt |
9.36Кб |
| 23.1 Companies spends and profits.csv |
3.24Кб |
| 23. Overview on the business problem data.mp4 |
8.74Мб |
| 23. Overview on the business problem data.srt |
1.46Кб |
| 24.1 MLR.py |
2.12Кб |
| 24. Create Multiple Linear Regression Model in Python-Part 1.mp4 |
172.58Мб |
| 24. Create Multiple Linear Regression Model in Python-Part 1.srt |
16.94Кб |
| 25. Create Multiple Linear Regression Model in Python-Part 2.mp4 |
141.28Мб |
| 25. Create Multiple Linear Regression Model in Python-Part 2.srt |
12.88Кб |
| 26. Create Multiple Linear Regression Model in Python-Part 3.mp4 |
138.08Мб |
| 26. Create Multiple Linear Regression Model in Python-Part 3.srt |
11.62Кб |
| 27. Create Multiple Linear Regression Model in Python-Part 4.mp4 |
82.28Мб |
| 27. Create Multiple Linear Regression Model in Python-Part 4.srt |
7.99Кб |
| 28. Polynomial Regression.mp4 |
10.65Мб |
| 28. Polynomial Regression.srt |
2.29Кб |
| 29.1 Reward_system.csv |
213б |
| 29. Overview on the business problem data.mp4 |
7.17Мб |
| 29. Overview on the business problem data.srt |
1.28Кб |
| 3. Data Types.html |
165б |
| 3. Dendrogram Diagram Method.mp4 |
28.60Мб |
| 3. Dendrogram Diagram Method.srt |
6.87Кб |
| 3. How Does Deep Learning Work.mp4 |
27.57Мб |
| 3. How Does Deep Learning Work.srt |
5.71Кб |
| 3. Introduction to Data Mining.mp4 |
42.80Мб |
| 3. Introduction to Data Mining.srt |
10.84Кб |
| 30.1 PR.py |
1.73Кб |
| 30. Create Polynomial Regression Model in Python-Part 1.mp4 |
79.39Мб |
| 30. Create Polynomial Regression Model in Python-Part 1.srt |
9.69Кб |
| 31. Create Polynomial Regression Model in Python-Part 2.mp4 |
124.44Мб |
| 31. Create Polynomial Regression Model in Python-Part 2.srt |
13.43Кб |
| 32. Course Rating.html |
508б |
| 33. Introduction to Classification.mp4 |
19.88Мб |
| 33. Introduction to Classification.srt |
4.71Кб |
| 34. Introduction to Logistic Regression.mp4 |
29.10Мб |
| 34. Introduction to Logistic Regression.srt |
8.87Кб |
| 35. Confusion Matrix.mp4 |
15.56Мб |
| 35. Confusion Matrix.srt |
4.48Кб |
| 36. Standard Scaler.mp4 |
12.16Мб |
| 36. Standard Scaler.srt |
3.34Кб |
| 37.1 Bank_Data.csv |
17.25Кб |
| 37. Overview on the business problem data.mp4 |
10.28Мб |
| 37. Overview on the business problem data.srt |
1.82Кб |
| 38.1 LR.py |
1.09Кб |
| 38. Create Logistic Regression Model in Python-Part 1.mp4 |
112.00Мб |
| 38. Create Logistic Regression Model in Python-Part 1.srt |
12.85Кб |
| 39. Create Logistic Regression Model in Python-Part 2.mp4 |
59.59Мб |
| 39. Create Logistic Regression Model in Python-Part 2.srt |
6.84Кб |
| 4. Activation Functions.mp4 |
34.80Мб |
| 4. Activation Functions.srt |
7.30Кб |
| 4. Data Mining Definition.html |
165б |
| 4. Introduction to Regression Model.mp4 |
21.26Мб |
| 4. Introduction to Regression Model.srt |
4.86Кб |
| 4. Overview on the business problem data.mp4 |
4.18Мб |
| 4. Overview on the business problem data.srt |
812б |
| 40. KNN Classification Algorithm.mp4 |
15.32Мб |
| 40. KNN Classification Algorithm.srt |
4.45Кб |
| 41.1 K-NN.py |
1.23Кб |
| 41.2 Bank_Data.csv |
17.25Кб |
| 41. Create KNN Model in Python.mp4 |
65.22Мб |
| 41. Create KNN Model in Python.srt |
8.23Кб |
| 42. Support Vector Machine (SVM) Classification Algorithm.mp4 |
17.82Мб |
| 42. Support Vector Machine (SVM) Classification Algorithm.srt |
3.98Кб |
| 43.1 SVM.py |
1.16Кб |
| 43. Create Support Vector Machine in Python.mp4 |
53.11Мб |
| 43. Create Support Vector Machine in Python.srt |
7.71Кб |
| 44. Naive Bayes Algorithm Part 1.mp4 |
19.83Мб |
| 44. Naive Bayes Algorithm Part 1.srt |
5.21Кб |
| 45. Naive Bayes Algorithm Part 2.mp4 |
27.92Мб |
| 45. Naive Bayes Algorithm Part 2.srt |
6.96Кб |
| 46.1 Naive_Bayes.py |
1.07Кб |
| 46. Create Naive Bayes Model in Python.mp4 |
28.88Мб |
| 46. Create Naive Bayes Model in Python.srt |
3.77Кб |
| 47. Decision Tree Algorithm.mp4 |
34.46Мб |
| 47. Decision Tree Algorithm.srt |
7.94Кб |
| 48.1 Bank_Data.csv |
17.25Кб |
| 48.2 Decision Tree.py |
1.14Кб |
| 48. Create Decision Tree Model in Python.mp4 |
33.63Мб |
| 48. Create Decision Tree Model in Python.srt |
3.48Кб |
| 49. Random Forest Algorithm.mp4 |
6.07Мб |
| 49. Random Forest Algorithm.srt |
1.41Кб |
| 5.1 Hierarchical Clustering.py |
1.19Кб |
| 5.2 Movies.csv |
1.66Кб |
| 5. Create Hierarchical Clustering Algorithm in Python-1.mp4 |
128.29Мб |
| 5. Create Hierarchical Clustering Algorithm in Python-1.srt |
13.65Кб |
| 5. Introduction to Machine Learning.mp4 |
14.31Мб |
| 5. Introduction to Machine Learning.srt |
3.05Кб |
| 5. Regression Model.html |
165б |
| 5. What is Tensorflow.mp4 |
6.97Мб |
| 5. What is Tensorflow.srt |
2.56Кб |
| 50.1 Random_Forest.py |
1.19Кб |
| 50. Create Random Forest Model in Python.mp4 |
69.38Мб |
| 50. Create Random Forest Model in Python.srt |
6.40Кб |
| 51. Course Rating.html |
508б |
| 6. Create Hierarchical Clustering Algorithm in Python-2.mp4 |
72.07Мб |
| 6. Create Hierarchical Clustering Algorithm in Python-2.srt |
7.28Кб |
| 6. Introduction to the Deep Learning Problem and Dataset.mp4 |
8.95Мб |
| 6. Introduction to the Deep Learning Problem and Dataset.srt |
1.13Кб |
| 6. Machine Leaning Sub-fields..html |
165б |
| 6. Regression Model Slope.mp4 |
31.15Мб |
| 6. Regression Model Slope.srt |
7.37Кб |
| 7.1 M_ANN.py |
1.50Кб |
| 7.2 Medical_data.csv |
23.45Кб |
| 7. Create Artificial Neural Network Model in Python Part-1.mp4 |
64.94Мб |
| 7. Create Artificial Neural Network Model in Python Part-1.srt |
6.97Кб |
| 7. How Does Machine Learning Work.mp4 |
19.45Мб |
| 7. How Does Machine Learning Work.srt |
4.46Кб |
| 7. K-means Clustering Algorithm.mp4 |
16.17Мб |
| 7. K-means Clustering Algorithm.srt |
3.99Кб |
| 7. Regression Slope.html |
165б |
| 8. Create Artificial Neural Network Model in Python Part-2.mp4 |
68.96Мб |
| 8. Create Artificial Neural Network Model in Python Part-2.srt |
9.88Кб |
| 8. The Intercept Value.html |
165б |
| 8. Train and Test Sets..html |
165б |
| 8. Using Elbow Method to Determine Optimal Number of Clusters.mp4 |
48.80Мб |
| 8. Using Elbow Method to Determine Optimal Number of Clusters.srt |
11.30Кб |
| 9.1 kmeans.py |
1.19Кб |
| 9.1 Link to the Keras documentation website..html |
78б |
| 9.2 Movies.csv |
1.66Кб |
| 9. Create Artificial Neural Network Model in Python Part-3.mp4 |
65.64Мб |
| 9. Create Artificial Neural Network Model in Python Part-3.srt |
6.46Кб |
| 9. Create K-means Clustering Algorithm Model in Python - 1.mp4 |
78.62Мб |
| 9. Create K-means Clustering Algorithm Model in Python - 1.srt |
8.64Кб |
| 9. Machine Learning Algorithms Types.mp4 |
40.80Мб |
| 9. Machine Learning Algorithms Types.srt |
8.18Кб |
| 9. R-Squared.mp4 |
29.06Мб |
| 9. R-Squared.srt |
8.17Кб |
| TutsNode.com.txt |
63б |