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