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[FreeAllCourse.Com] Udemy- The Complete Machine Learning Course with Python

Magnet Download Download Torrent
File Name
Size
1. Introduction/1. What Does the Course Cover.mp4
54 MB
1. Introduction/1. What Does the Course Cover.vtt
3.0 kB
1. Introduction/2. How to Succeed in This Course.html
2.2 kB
1. Introduction/3. Project Files and Resources.html
1.7 kB
10. Unsupervised Learning Clustering/1. Clustering.mp4
126 MB
10. Unsupervised Learning Clustering/1. Clustering.vtt
19 kB
10. Unsupervised Learning Clustering/2. k_Means Clustering.mp4
58 MB
10. Unsupervised Learning Clustering/2. k_Means Clustering.vtt
10 kB
11. Deep Learning/1. Estimating Simple Function with Neural Networks.mp4
144 MB
11. Deep Learning/1. Estimating Simple Function with Neural Networks.vtt
24 kB
11. Deep Learning/2. Neural Network Architecture.mp4
22 MB
11. Deep Learning/2. Neural Network Architecture.vtt
7.2 kB
11. Deep Learning/3. Motivational Example - Project MNIST.mp4
145 MB
11. Deep Learning/3. Motivational Example - Project MNIST.vtt
24 kB
11. Deep Learning/4. Binary Classification Problem.mp4
72 MB
11. Deep Learning/4. Binary Classification Problem.vtt
12 kB
11. Deep Learning/5. Natural Language Processing - Binary Classification.mp4
76 MB
11. Deep Learning/5. Natural Language Processing - Binary Classification.vtt
12 kB
12. Appendix A1 Foundations of Deep Learning/1. Introduction to Neural Networks.mp4
14 MB
12. Appendix A1 Foundations of Deep Learning/1. Introduction to Neural Networks.vtt
2.5 kB
12. Appendix A1 Foundations of Deep Learning/10. Gradient Based Optimization.mp4
55 MB
12. Appendix A1 Foundations of Deep Learning/10. Gradient Based Optimization.vtt
13 kB
12. Appendix A1 Foundations of Deep Learning/11. Getting Started with Neural Network and Deep Learning Libraries.mp4
19 MB
12. Appendix A1 Foundations of Deep Learning/11. Getting Started with Neural Network and Deep Learning Libraries.vtt
5.1 kB
12. Appendix A1 Foundations of Deep Learning/12. Categories of Machine Learning.mp4
38 MB
12. Appendix A1 Foundations of Deep Learning/12. Categories of Machine Learning.vtt
11 kB
12. Appendix A1 Foundations of Deep Learning/13. Over and Under Fitting.mp4
70 MB
12. Appendix A1 Foundations of Deep Learning/13. Over and Under Fitting.vtt
17 kB
12. Appendix A1 Foundations of Deep Learning/14. Machine Learning Workflow.mp4
27 MB
12. Appendix A1 Foundations of Deep Learning/14. Machine Learning Workflow.vtt
5.3 kB
12. Appendix A1 Foundations of Deep Learning/2. Differences between Classical Programming and Machine Learning.mp4
21 MB
12. Appendix A1 Foundations of Deep Learning/2. Differences between Classical Programming and Machine Learning.vtt
4.9 kB
12. Appendix A1 Foundations of Deep Learning/3. Learning Representations.mp4
77 MB
12. Appendix A1 Foundations of Deep Learning/3. Learning Representations.vtt
12 kB
12. Appendix A1 Foundations of Deep Learning/4. What is Deep Learning.mp4
156 MB
12. Appendix A1 Foundations of Deep Learning/4. What is Deep Learning.vtt
23 kB
12. Appendix A1 Foundations of Deep Learning/5. Learning Neural Networks.mp4
41 MB
12. Appendix A1 Foundations of Deep Learning/5. Learning Neural Networks.vtt
11 kB
12. Appendix A1 Foundations of Deep Learning/6. Why Now.mp4
9.1 MB
12. Appendix A1 Foundations of Deep Learning/6. Why Now.vtt
3.0 kB
12. Appendix A1 Foundations of Deep Learning/7. Building Block Introduction.mp4
14 MB
12. Appendix A1 Foundations of Deep Learning/7. Building Block Introduction.vtt
5.1 kB
12. Appendix A1 Foundations of Deep Learning/8. Tensors.mp4
17 MB
12. Appendix A1 Foundations of Deep Learning/8. Tensors.vtt
4.3 kB
12. Appendix A1 Foundations of Deep Learning/9. Tensor Operations.mp4
89 MB
12. Appendix A1 Foundations of Deep Learning/9. Tensor Operations.vtt
19 kB
13. Computer Vision and Convolutional Neural Network (CNN)/1. Outline.mp4
64 MB
13. Computer Vision and Convolutional Neural Network (CNN)/1. Outline.vtt
4.1 kB
13. Computer Vision and Convolutional Neural Network (CNN)/10. Training Your CNN 1.mp4
125 MB
13. Computer Vision and Convolutional Neural Network (CNN)/10. Training Your CNN 1.vtt
15 kB
13. Computer Vision and Convolutional Neural Network (CNN)/11. Training Your CNN 2.mp4
128 MB
13. Computer Vision and Convolutional Neural Network (CNN)/11. Training Your CNN 2.vtt
22 kB
13. Computer Vision and Convolutional Neural Network (CNN)/12. Loading Previously Trained Model.mp4
11 MB
13. Computer Vision and Convolutional Neural Network (CNN)/12. Loading Previously Trained Model.vtt
1.6 kB
13. Computer Vision and Convolutional Neural Network (CNN)/13. Model Performance Comparison.mp4
80 MB
13. Computer Vision and Convolutional Neural Network (CNN)/13. Model Performance Comparison.vtt
11 kB
13. Computer Vision and Convolutional Neural Network (CNN)/14. Data Augmentation.mp4
28 MB
13. Computer Vision and Convolutional Neural Network (CNN)/14. Data Augmentation.vtt
3.3 kB
13. Computer Vision and Convolutional Neural Network (CNN)/15. Transfer Learning.mp4
97 MB
13. Computer Vision and Convolutional Neural Network (CNN)/15. Transfer Learning.vtt
12 kB
13. Computer Vision and Convolutional Neural Network (CNN)/16. Feature Extraction.mp4
111 MB
13. Computer Vision and Convolutional Neural Network (CNN)/16. Feature Extraction.vtt
13 kB
13. Computer Vision and Convolutional Neural Network (CNN)/17. State of the Art Tools.mp4
35 MB
13. Computer Vision and Convolutional Neural Network (CNN)/17. State of the Art Tools.vtt
6.0 kB
13. Computer Vision and Convolutional Neural Network (CNN)/2. Neural Network Revision.mp4
44 MB
13. Computer Vision and Convolutional Neural Network (CNN)/2. Neural Network Revision.vtt
9.2 kB
13. Computer Vision and Convolutional Neural Network (CNN)/3. Motivational Example.mp4
66 MB
13. Computer Vision and Convolutional Neural Network (CNN)/3. Motivational Example.vtt
8.7 kB
13. Computer Vision and Convolutional Neural Network (CNN)/4. Visualizing CNN.mp4
142 MB
13. Computer Vision and Convolutional Neural Network (CNN)/4. Visualizing CNN.vtt
15 kB
13. Computer Vision and Convolutional Neural Network (CNN)/5. Understanding CNN.mp4
30 MB
13. Computer Vision and Convolutional Neural Network (CNN)/5. Understanding CNN.vtt
6.7 kB
13. Computer Vision and Convolutional Neural Network (CNN)/6. Layer - Input.mp4
29 MB
13. Computer Vision and Convolutional Neural Network (CNN)/6. Layer - Input.vtt
6.2 kB
13. Computer Vision and Convolutional Neural Network (CNN)/7. Layer - Filter.mp4
84 MB
13. Computer Vision and Convolutional Neural Network (CNN)/7. Layer - Filter.vtt
18 kB
13. Computer Vision and Convolutional Neural Network (CNN)/8. Activation Function.mp4
32 MB
13. Computer Vision and Convolutional Neural Network (CNN)/8. Activation Function.vtt
6.9 kB
13. Computer Vision and Convolutional Neural Network (CNN)/9. Pooling, Flatten, Dense.mp4
88 MB
13. Computer Vision and Convolutional Neural Network (CNN)/9. Pooling, Flatten, Dense.vtt
12 kB
2. Getting Started with Anaconda/1. Installing Applications and Creating Environment.mp4
38 MB
2. Getting Started with Anaconda/1. Installing Applications and Creating Environment.vtt
6.0 kB
2. Getting Started with Anaconda/2. Hello World.mp4
51 MB
2. Getting Started with Anaconda/2. Hello World.vtt
12 kB
2. Getting Started with Anaconda/3. Iris Project 1 Working with Error Messages.mp4
90 MB
2. Getting Started with Anaconda/3. Iris Project 1 Working with Error Messages.vtt
14 kB
2. Getting Started with Anaconda/4. Iris Project 2 Reading CSV Data into Memory.mp4
65 MB
2. Getting Started with Anaconda/4. Iris Project 2 Reading CSV Data into Memory.vtt
10 kB
2. Getting Started with Anaconda/5. Iris Project 3 Loading data from Seaborn.mp4
56 MB
2. Getting Started with Anaconda/5. Iris Project 3 Loading data from Seaborn.vtt
9.9 kB
2. Getting Started with Anaconda/6. Iris Project 4 Visualization.mp4
94 MB
2. Getting Started with Anaconda/6. Iris Project 4 Visualization.vtt
12 kB
3. Regression/1. Scikit-Learn.mp4
48 MB
3. Regression/1. Scikit-Learn.vtt
10 kB
3. Regression/10. Multiple Regression 2.mp4
91 MB
3. Regression/10. Multiple Regression 2.vtt
14 kB
3. Regression/11. Regularized Regression.mp4
44 MB
3. Regression/11. Regularized Regression.vtt
7.8 kB
3. Regression/12. Polynomial Regression.mp4
111 MB
3. Regression/12. Polynomial Regression.vtt
20 kB
3. Regression/13. Dealing with Non-linear Relationships.mp4
63 MB
3. Regression/13. Dealing with Non-linear Relationships.vtt
10 kB
3. Regression/14. Feature Importance.mp4
36 MB
3. Regression/14. Feature Importance.vtt
5.4 kB
3. Regression/15. Data Preprocessing.mp4
136 MB
3. Regression/15. Data Preprocessing.vtt
26 kB
3. Regression/16. Variance-Bias Trade Off.mp4
69 MB
3. Regression/16. Variance-Bias Trade Off.vtt
14 kB
3. Regression/17. Learning Curve.mp4
56 MB
3. Regression/17. Learning Curve.vtt
10 kB
3. Regression/18. Cross Validation.mp4
48 MB
3. Regression/18. Cross Validation.vtt
9.7 kB
3. Regression/19. CV Illustration.mp4
127 MB
3. Regression/19. CV Illustration.vtt
20 kB
3. Regression/2. EDA.mp4
152 MB
3. Regression/2. EDA.vtt
22 kB
3. Regression/3. Correlation Analysis and Feature Selection.mp4
23 MB
3. Regression/3. Correlation Analysis and Feature Selection.vtt
9.8 kB
3. Regression/3.1 0305.zip.zip
2.1 MB
3. Regression/4. Correlation Analysis and Feature Selection.mp4
105 MB
3. Regression/4. Correlation Analysis and Feature Selection.vtt
14 kB
3. Regression/5. Linear Regression with Scikit-Learn.mp4
77 MB
3. Regression/5. Linear Regression with Scikit-Learn.vtt
15 kB
3. Regression/6. Five Steps Machine Learning Process.mp4
77 MB
3. Regression/6. Five Steps Machine Learning Process.vtt
9.2 kB
3. Regression/7. Robust Regression.mp4
119 MB
3. Regression/7. Robust Regression.vtt
20 kB
3. Regression/8. Evaluate Regression Model Performance.mp4
100 MB
3. Regression/8. Evaluate Regression Model Performance.vtt
18 kB
3. Regression/9. Multiple Regression 1.mp4
126 MB
3. Regression/9. Multiple Regression 1.vtt
22 kB
4. Classification/1. Logistic Regression.mp4
120 MB
4. Classification/1. Logistic Regression.vtt
24 kB
4. Classification/10. Precision Recall Tradeoff.mp4
102 MB
4. Classification/10. Precision Recall Tradeoff.vtt
21 kB
4. Classification/11. Altering the Precision Recall Tradeoff.mp4
21 MB
4. Classification/11. Altering the Precision Recall Tradeoff.vtt
3.5 kB
4. Classification/12. ROC.mp4
52 MB
4. Classification/12. ROC.vtt
7.6 kB
4. Classification/2. Introduction to Classification.mp4
42 MB
4. Classification/2. Introduction to Classification.vtt
5.7 kB
4. Classification/3. Understanding MNIST.mp4
109 MB
4. Classification/3. Understanding MNIST.vtt
16 kB
4. Classification/4. SGD.mp4
57 MB
4. Classification/4. SGD.vtt
11 kB
4. Classification/5. Performance Measure and Stratified k-Fold.mp4
52 MB
4. Classification/5. Performance Measure and Stratified k-Fold.vtt
8.1 kB
4. Classification/6. Confusion Matrix.mp4
55 MB
4. Classification/6. Confusion Matrix.vtt
11 kB
4. Classification/7. Precision.mp4
24 MB
4. Classification/7. Precision.vtt
4.1 kB
4. Classification/8. Recall.mp4
20 MB
4. Classification/8. Recall.vtt
3.7 kB
4. Classification/9. f1.mp4
12 MB
4. Classification/9. f1.vtt
2.3 kB
5. Support Vector Machine (SVM)/1. Support Vector Machine (SVM) Concepts.mp4
38 MB
5. Support Vector Machine (SVM)/1. Support Vector Machine (SVM) Concepts.vtt
8.0 kB
5. Support Vector Machine (SVM)/2. Linear SVM Classification.mp4
81 MB
5. Support Vector Machine (SVM)/2. Linear SVM Classification.vtt
12 kB
5. Support Vector Machine (SVM)/3. Polynomial Kernel.mp4
35 MB
5. Support Vector Machine (SVM)/3. Polynomial Kernel.vtt
5.5 kB
5. Support Vector Machine (SVM)/4. Radial Basis Function.mp4
70 MB
5. Support Vector Machine (SVM)/4. Radial Basis Function.vtt
8.8 kB
5. Support Vector Machine (SVM)/5. Support Vector Regression.mp4
60 MB
5. Support Vector Machine (SVM)/5. Support Vector Regression.vtt
9.3 kB
6. Tree/1. Introduction to Decision Tree.mp4
44 MB
6. Tree/1. Introduction to Decision Tree.vtt
7.9 kB
6. Tree/2. Training and Visualizing a Decision Tree.mp4
51 MB
6. Tree/2. Training and Visualizing a Decision Tree.vtt
7.0 kB
6. Tree/3. Visualizing Boundary.mp4
55 MB
6. Tree/3. Visualizing Boundary.vtt
8.8 kB
6. Tree/4. Tree Regression, Regularization and Over Fitting.mp4
40 MB
6. Tree/4. Tree Regression, Regularization and Over Fitting.vtt
5.3 kB
6. Tree/5. End to End Modeling.mp4
36 MB
6. Tree/5. End to End Modeling.vtt
5.3 kB
6. Tree/6. Project HR.mp4
178 MB
6. Tree/6. Project HR.vtt
28 kB
6. Tree/7. Project HR with Google Colab.mp4
67 MB
6. Tree/7. Project HR with Google Colab.vtt
11 kB
7. Ensemble Machine Learning/1. Ensemble Learning Methods Introduction.mp4
37 MB
7. Ensemble Machine Learning/1. Ensemble Learning Methods Introduction.vtt
5.6 kB
7. Ensemble Machine Learning/10. Ensemble of ensembles Part 2.mp4
38 MB
7. Ensemble Machine Learning/10. Ensemble of ensembles Part 2.vtt
5.7 kB
7. Ensemble Machine Learning/2. Bagging.mp4
165 MB
7. Ensemble Machine Learning/2. Bagging.vtt
21 kB
7. Ensemble Machine Learning/3. Random Forests and Extra-Trees.mp4
80 MB
7. Ensemble Machine Learning/3. Random Forests and Extra-Trees.vtt
11 kB
7. Ensemble Machine Learning/4. AdaBoost.mp4
50 MB
7. Ensemble Machine Learning/4. AdaBoost.vtt
7.9 kB
7. Ensemble Machine Learning/5. Gradient Boosting Machine.mp4
22 MB
7. Ensemble Machine Learning/5. Gradient Boosting Machine.vtt
3.6 kB
7. Ensemble Machine Learning/6. XGBoost Installation.mp4
22 MB
7. Ensemble Machine Learning/6. XGBoost Installation.vtt
2.8 kB
7. Ensemble Machine Learning/7. XGBoost.mp4
35 MB
7. Ensemble Machine Learning/7. XGBoost.vtt
5.1 kB
7. Ensemble Machine Learning/8. Project HR - Human Resources Analytics.mp4
59 MB
7. Ensemble Machine Learning/8. Project HR - Human Resources Analytics.vtt
9.5 kB
7. Ensemble Machine Learning/9. Ensemble of Ensembles Part 1.mp4
46 MB
7. Ensemble Machine Learning/9. Ensemble of Ensembles Part 1.vtt
7.3 kB
8. k-Nearest Neighbours (kNN)/1. kNN Introduction.mp4
63 MB
8. k-Nearest Neighbours (kNN)/1. kNN Introduction.vtt
11 kB
8. k-Nearest Neighbours (kNN)/2. Project Cancer Detection.mp4
76 MB
8. k-Nearest Neighbours (kNN)/2. Project Cancer Detection.vtt
10 kB
8. k-Nearest Neighbours (kNN)/3. Addition Materials.html
335 B
8. k-Nearest Neighbours (kNN)/4. Project Cancer Detection Part 1.mp4
49 MB
8. k-Nearest Neighbours (kNN)/4. Project Cancer Detection Part 1.vtt
22 kB
8. k-Nearest Neighbours (kNN)/4.1 0805.zip.zip
41 kB
9. Unsupervised Learning Dimensionality Reduction/1. Dimensionality Reduction Concept.mp4
31 MB
9. Unsupervised Learning Dimensionality Reduction/1. Dimensionality Reduction Concept.vtt
5.3 kB
9. Unsupervised Learning Dimensionality Reduction/2. PCA Introduction.mp4
49 MB
9. Unsupervised Learning Dimensionality Reduction/2. PCA Introduction.vtt
8.2 kB
9. Unsupervised Learning Dimensionality Reduction/3. Project Wine.mp4
48 MB
9. Unsupervised Learning Dimensionality Reduction/3. Project Wine.vtt
7.0 kB
9. Unsupervised Learning Dimensionality Reduction/4. Kernel PCA.mp4
37 MB
9. Unsupervised Learning Dimensionality Reduction/4. Kernel PCA.vtt
6.1 kB
9. Unsupervised Learning Dimensionality Reduction/5. Kernel PCA Demo.mp4
21 MB
9. Unsupervised Learning Dimensionality Reduction/5. Kernel PCA Demo.vtt
3.6 kB
9. Unsupervised Learning Dimensionality Reduction/6. LDA vs PCA.mp4
34 MB
9. Unsupervised Learning Dimensionality Reduction/6. LDA vs PCA.vtt
5.9 kB
9. Unsupervised Learning Dimensionality Reduction/7. Project Abalone.mp4
31 MB
9. Unsupervised Learning Dimensionality Reduction/7. Project Abalone.vtt
4.3 kB