| 1. Clustering.mp4 | 125.7 MB | ||
| 1. Clustering.vtt | 18.7 KB | ||
| 1. Dimensionality Reduction Concept.mp4 | 31.4 MB | ||
| 1. Dimensionality Reduction Concept.vtt | 5.3 KB | ||
| 1. Ensemble Learning Methods Introduction.mp4 | 37.2 MB | ||
| 1. Ensemble Learning Methods Introduction.vtt | 5.6 KB | ||
| 1. Estimating Simple Function with Neural Networks.mp4 | 143.9 MB | ||
| 1. Estimating Simple Function with Neural Networks.vtt | 24.4 KB | ||
| 1. Installing Applications and Creating Environment.mp4 | 38.4 MB | ||
| 1. Installing Applications and Creating Environment.vtt | 6 KB | ||
| 1. Introduction to Decision Tree.mp4 | 43.9 MB | ||
| 1. Introduction to Decision Tree.vtt | 7.9 KB | ||
| 1. Introduction to Neural Networks.mp4 | 13.8 MB | ||
| 1. Introduction to Neural Networks.vtt | 2.5 KB | ||
| 1. Logistic Regression.mp4 | 119.6 MB | ||
| 1. Logistic Regression.vtt | 23.5 KB | ||
| 1. Outline.mp4 | 63.7 MB | ||
| 1. Outline.vtt | 4.1 KB | ||
| 1. Scikit-Learn.mp4 | 48.5 MB | ||
| 1. Scikit-Learn.vtt | 10 KB | ||
| 1. Support Vector Machine (SVM) Concepts.mp4 | 37.9 MB | ||
| 1. Support Vector Machine (SVM) Concepts.vtt | 8 KB | ||
| 1. What Does the Course Cover.mp4 | 54.4 MB | ||
| 1. What Does the Course Cover.vtt | 3 KB | ||
| 1. kNN Introduction.mp4 | 62.9 MB | ||
| 1. kNN Introduction.vtt | 11 KB | ||
| 10. Ensemble of ensembles Part 2.mp4 | 37.8 MB | ||
| 10. Ensemble of ensembles Part 2.vtt | 5.7 KB | ||
| 10. Gradient Based Optimization.mp4 | 55 MB | ||
| 10. Gradient Based Optimization.vtt | 12.6 KB | ||
| 10. Multiple Regression 2.mp4 | 91.2 MB | ||
| 10. Multiple Regression 2.vtt | 13.8 KB | ||
| 10. Precision Recall Tradeoff.mp4 | 102 MB | ||
| 10. Precision Recall Tradeoff.vtt | 20.8 KB | ||
| 10. Training Your CNN 1.mp4 | 124.9 MB | ||
| 10. Training Your CNN 1.vtt | 15.2 KB | ||
| 11. Altering the Precision Recall Tradeoff.mp4 | 20.9 MB | ||
| 11. Altering the Precision Recall Tradeoff.vtt | 3.5 KB | ||
| 11. Getting Started with Neural Network and Deep Learning Libraries.mp4 | 18.7 MB | ||
| 11. Getting Started with Neural Network and Deep Learning Libraries.vtt | 5.1 KB | ||
| 11. Regularized Regression.mp4 | 44.3 MB | ||
| 11. Regularized Regression.vtt | 7.8 KB | ||
| 11. Training Your CNN 2.mp4 | 128.5 MB | ||
| 11. Training Your CNN 2.vtt | 22.4 KB | ||
| 12. Categories of Machine Learning.mp4 | 37.5 MB | ||
| 12. Categories of Machine Learning.vtt | 11.2 KB | ||
| 12. Loading Previously Trained Model.mp4 | 11.2 MB | ||
| 12. Loading Previously Trained Model.vtt | 1.6 KB | ||
| 12. Polynomial Regression.mp4 | 110.8 MB | ||
| 12. Polynomial Regression.vtt | 19.7 KB | ||
| 12. ROC.mp4 | 52.2 MB | ||
| 12. ROC.vtt | 7.6 KB | ||
| 13. Dealing with Non-linear Relationships.mp4 | 62.7 MB | ||
| 13. Dealing with Non-linear Relationships.vtt | 10.3 KB | ||
| 13. Model Performance Comparison.mp4 | 79.8 MB | ||
| 13. Model Performance Comparison.vtt | 10.7 KB | ||
| 13. Over and Under Fitting.mp4 | 70.1 MB | ||
| 13. Over and Under Fitting.vtt | 16.7 KB | ||
| 14. Data Augmentation.mp4 | 28.5 MB | ||
| 14. Data Augmentation.vtt | 3.3 KB | ||
| 14. Feature Importance.mp4 | 36.3 MB | ||
| 14. Feature Importance.vtt | 5.4 KB | ||
| 14. Machine Learning Workflow.mp4 | 27.4 MB | ||
| 14. Machine Learning Workflow.vtt | 5.3 KB | ||
| 15. Data Preprocessing.mp4 | 135.5 MB | ||
| 15. Data Preprocessing.vtt | 25.5 KB | ||
| 15. Transfer Learning.mp4 | 97 MB | ||
| 15. Transfer Learning.vtt | 12.1 KB | ||
| 16. Feature Extraction.mp4 | 111.1 MB | ||
| 16. Feature Extraction.vtt | 12.9 KB | ||
| 16. Variance-Bias Trade Off.mp4 | 68.7 MB | ||
| 16. Variance-Bias Trade Off.vtt | 13.7 KB | ||
| 17. Learning Curve.mp4 | 56.4 MB | ||
| 17. Learning Curve.vtt | 10.2 KB | ||
| 17. State of the Art Tools.mp4 | 35.4 MB | ||
| 17. State of the Art Tools.vtt | 6 KB | ||
| 18. Cross Validation.mp4 | 48 MB | ||
| 18. Cross Validation.vtt | 9.7 KB | ||
| 19. CV Illustration.mp4 | 127.2 MB | ||
| 19. CV Illustration.vtt | 19.9 KB | ||
| 2. Bagging.mp4 | 165.4 MB | ||
| 2. Bagging.vtt | 21.1 KB | ||
| 2. Differences between Classical Programming and Machine Learning.mp4 | 20.9 MB | ||
| 2. Differences between Classical Programming and Machine Learning.vtt | 4.9 KB | ||
| 2. EDA.mp4 | 151.7 MB | ||
| 2. EDA.vtt | 22.4 KB | ||
| 2. Hello World.mp4 | 51.2 MB | ||
| 2. Hello World.vtt | 12.5 KB | ||
| 2. How to Succeed in This Course.html | 2.2 KB | ||
| 2. Introduction to Classification.mp4 | 42.1 MB | ||
| 2. Introduction to Classification.vtt | 5.7 KB | ||
| 2. Linear SVM Classification.mp4 | 80.9 MB | ||
| 2. Linear SVM Classification.vtt | 12.1 KB | ||
| 2. Neural Network Architecture.mp4 | 22.4 MB | ||
| 2. Neural Network Architecture.vtt | 7.2 KB | ||
| 2. Neural Network Revision.mp4 | 43.8 MB | ||
| 2. Neural Network Revision.vtt | 9.2 KB | ||
| 2. PCA Introduction.mp4 | 49 MB | ||
| 2. PCA Introduction.vtt | 8.2 KB | ||
| 2. Project Cancer Detection.mp4 | 75.7 MB | ||
| 2. Project Cancer Detection.vtt | 10 KB | ||
| 2. Training and Visualizing a Decision Tree.mp4 | 51.4 MB | ||
| 2. Training and Visualizing a Decision Tree.vtt | 7 KB | ||
| 2. k_Means Clustering.mp4 | 57.7 MB | ||
| 2. k_Means Clustering.vtt | 10 KB | ||
| 3. Addition Materials.html | 307 B | ||
| 3. Correlation Analysis and Feature Selection.mp4 | 22.6 MB | ||
| 3. Correlation Analysis and Feature Selection.vtt | 9.8 KB | ||
| 3. Iris Project 1 Working with Error Messages.mp4 | 89.8 MB | ||
| 3. Iris Project 1 Working with Error Messages.vtt | 14.5 KB | ||
| 3. Learning Representations.mp4 | 77.2 MB | ||
| 3. Learning Representations.vtt | 11.5 KB | ||
| 3. Motivational Example - Project MNIST.mp4 | 145 MB | ||
| 3. Motivational Example - Project MNIST.vtt | 23.5 KB | ||
| 3. Motivational Example.mp4 | 66.2 MB | ||
| 3. Motivational Example.vtt | 8.7 KB | ||
| 3. Polynomial Kernel.mp4 | 35 MB | ||
| 3. Polynomial Kernel.vtt | 5.5 KB | ||
| 3. Project Files and Resources.html | 1.7 KB | ||
| 3. Project Wine.mp4 | 47.9 MB | ||
| 3. Project Wine.vtt | 7 KB | ||
| 3. Random Forests and Extra-Trees.mp4 | 80.3 MB | ||
| 3. Random Forests and Extra-Trees.vtt | 11.1 KB | ||
| 3. Understanding MNIST.mp4 | 109 MB | ||
| 3. Understanding MNIST.vtt | 16.4 KB | ||
| 3. Visualizing Boundary.mp4 | 54.7 MB | ||
| 3. Visualizing Boundary.vtt | 8.8 KB | ||
| 3.1 0305.zip.zip | 2.1 MB | ||
| 4. AdaBoost.mp4 | 49.8 MB | ||
| 4. AdaBoost.vtt | 7.9 KB | ||
| 4. Binary Classification Problem.mp4 | 72.1 MB | ||
| 4. Binary Classification Problem.vtt | 11.5 KB | ||
| 4. Correlation Analysis and Feature Selection.mp4 | 105.2 MB | ||
| 4. Correlation Analysis and Feature Selection.vtt | 13.9 KB | ||
| 4. Iris Project 2 Reading CSV Data into Memory.mp4 | 64.6 MB | ||
| 4. Iris Project 2 Reading CSV Data into Memory.vtt | 10 KB | ||
| 4. Kernel PCA.mp4 | 36.6 MB | ||
| 4. Kernel PCA.vtt | 6.1 KB | ||
| 4. Project Cancer Detection Part 1.mp4 | 49.4 MB | ||
| 4. Project Cancer Detection Part 1.vtt | 22.1 KB | ||
| 4. Radial Basis Function.mp4 | 70.1 MB | ||
| 4. Radial Basis Function.vtt | 8.8 KB | ||
| 4. SGD.mp4 | 57.3 MB | ||
| 4. SGD.vtt | 10.6 KB | ||
| 4. Tree Regression, Regularization and Over Fitting.mp4 | 40.1 MB | ||
| 4. Tree Regression, Regularization and Over Fitting.vtt | 5.3 KB | ||
| 4. Visualizing CNN.mp4 | 141.9 MB | ||
| 4. Visualizing CNN.vtt | 15.4 KB | ||
| 4. What is Deep Learning.mp4 | 155.6 MB | ||
| 4. What is Deep Learning.vtt | 23.1 KB | ||
| 4.1 0805.zip.zip | 40.8 KB | ||
| 5. End to End Modeling.mp4 | 35.6 MB | ||
| 5. End to End Modeling.vtt | 5.3 KB | ||
| 5. Gradient Boosting Machine.mp4 | 22 MB | ||
| 5. Gradient Boosting Machine.vtt | 3.6 KB | ||
| 5. Iris Project 3 Loading data from Seaborn.mp4 | 55.9 MB | ||
| 5. Iris Project 3 Loading data from Seaborn.vtt | 9.9 KB | ||
| 5. Kernel PCA Demo.mp4 | 21.4 MB | ||
| 5. Kernel PCA Demo.vtt | 3.6 KB | ||
| 5. Learning Neural Networks.mp4 | 40.6 MB | ||
| 5. Learning Neural Networks.vtt | 11.4 KB | ||
| 5. Linear Regression with Scikit-Learn.mp4 | 77 MB | ||
| 5. Linear Regression with Scikit-Learn.vtt | 14.9 KB | ||
| 5. Natural Language Processing - Binary Classification.mp4 | 76 MB | ||
| 5. Natural Language Processing - Binary Classification.vtt | 11.7 KB | ||
| 5. Performance Measure and Stratified k-Fold.mp4 | 51.5 MB | ||
| 5. Performance Measure and Stratified k-Fold.vtt | 8.1 KB | ||
| 5. Support Vector Regression.mp4 | 59.7 MB | ||
| 5. Support Vector Regression.vtt | 9.3 KB | ||
| 5. Understanding CNN.mp4 | 30 MB | ||
| 5. Understanding CNN.vtt | 6.7 KB | ||
| 6. Confusion Matrix.mp4 | 54.7 MB | ||
| 6. Confusion Matrix.vtt | 11 KB | ||
| 6. Five Steps Machine Learning Process.mp4 | 77.3 MB | ||
| 6. Five Steps Machine Learning Process.vtt | 9.2 KB | ||
| 6. Iris Project 4 Visualization.mp4 | 93.5 MB | ||
| 6. Iris Project 4 Visualization.vtt | 11.5 KB | ||
| 6. LDA vs PCA.mp4 | 34.1 MB | ||
| 6. LDA vs PCA.vtt | 5.9 KB | ||
| 6. Layer - Input.mp4 | 29.1 MB | ||
| 6. Layer - Input.vtt | 6.2 KB | ||
| 6. Project HR.mp4 | 177.8 MB | ||
| 6. Project HR.vtt | 28.1 KB | ||
| 6. Why Now.mp4 | 9.1 MB | ||
| 6. Why Now.vtt | 3 KB | ||
| 6. XGBoost Installation.mp4 | 22.3 MB | ||
| 6. XGBoost Installation.vtt | 2.8 KB | ||
| 7. Building Block Introduction.mp4 | 14.2 MB | ||
| 7. Building Block Introduction.vtt | 5.1 KB | ||
| 7. Layer - Filter.mp4 | 84.4 MB | ||
| 7. Layer - Filter.vtt | 18.5 KB | ||
| 7. Precision.mp4 | 23.6 MB | ||
| 7. Precision.vtt | 4.1 KB | ||
| 7. Project Abalone.mp4 | 30.7 MB | ||
| 7. Project Abalone.vtt | 4.3 KB | ||
| 7. Project HR with Google Colab.mp4 | 66.6 MB | ||
| 7. Project HR with Google Colab.vtt | 11.4 KB | ||
| 7. Robust Regression.mp4 | 119.1 MB | ||
| 7. Robust Regression.vtt | 20.1 KB | ||
| 7. XGBoost.mp4 | 35.1 MB | ||
| 7. XGBoost.vtt | 5.1 KB | ||
| 8. Activation Function.mp4 | 32.3 MB | ||
| 8. Activation Function.vtt | 6.9 KB | ||
| 8. Evaluate Regression Model Performance.mp4 | 99.7 MB | ||
| 8. Evaluate Regression Model Performance.vtt | 17.9 KB | ||
| 8. Project HR - Human Resources Analytics.mp4 | 59.2 MB | ||
| 8. Project HR - Human Resources Analytics.vtt | 9.5 KB | ||
| 8. Recall.mp4 | 19.6 MB | ||
| 8. Recall.vtt | 3.7 KB | ||
| 8. Tensors.mp4 | 16.9 MB | ||
| 8. Tensors.vtt | 4.3 KB | ||
| 9. Ensemble of Ensembles Part 1.mp4 | 46.4 MB | ||
| 9. Ensemble of Ensembles Part 1.vtt | 7.3 KB | ||
| 9. Multiple Regression 1.mp4 | 125.5 MB | ||
| 9. Multiple Regression 1.vtt | 22.5 KB | ||
| 9. Pooling, Flatten, Dense.mp4 | 88.1 MB | ||
| 9. Pooling, Flatten, Dense.vtt | 12.5 KB | ||
| 9. Tensor Operations.mp4 | 88.8 MB | ||
| 9. Tensor Operations.vtt | 18.9 KB | ||
| 9. f1.mp4 | 12.1 MB | ||
| 9. f1.vtt | 2.3 KB | ||
| [CourseClub.Me].url | 0 B | ||
| [DesireCourse.Net].url | 0 B | ||
| ▲ 223 total files | |||
The Complete Machine Learning Course with Python
Build a Portfolio of 12 Machine Learning Projects with Python, SVM, Regression, Unsupervised Machine Learning & More!
For More Courses Visit: https://desirecourse.net
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