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[FreeAllCourse.Com] Udemy- The Complete Machine Learning Course with Python
magnet:?xt=urn:btih:be1c9559ddc8efb105665a8d97abca77b961d8c9&dn=[FreeAllCourse.Com] Udemy- The Complete Machine Learning Course with Python
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be1c9559ddc8efb105665a8d97abca77b961d8c9
infohash:
108
文件数量
6.79 GB
文件大小
2019-12-24 17:45
创建日期
2024-7-1 06:14
最后访问
相关分词
FreeAllCourse
Com
Udemy-
The
Complete
Machine
Learning
Course
with
Python
1. Introduction/1. What Does the Course Cover.mp4 54.4 MB
10. Unsupervised Learning Clustering/1. Clustering.mp4 125.68 MB
10. Unsupervised Learning Clustering/2. k_Means Clustering.mp4 57.72 MB
11. Deep Learning/1. Estimating Simple Function with Neural Networks.mp4 143.85 MB
11. Deep Learning/2. Neural Network Architecture.mp4 22.38 MB
11. Deep Learning/3. Motivational Example - Project MNIST.mp4 144.96 MB
11. Deep Learning/4. Binary Classification Problem.mp4 72.11 MB
11. Deep Learning/5. Natural Language Processing - Binary Classification.mp4 76.05 MB
12. Appendix A1 Foundations of Deep Learning/1. Introduction to Neural Networks.mp4 13.75 MB
12. Appendix A1 Foundations of Deep Learning/10. Gradient Based Optimization.mp4 54.96 MB
12. Appendix A1 Foundations of Deep Learning/11. Getting Started with Neural Network and Deep Learning Libraries.mp4 18.67 MB
12. Appendix A1 Foundations of Deep Learning/12. Categories of Machine Learning.mp4 37.47 MB
12. Appendix A1 Foundations of Deep Learning/13. Over and Under Fitting.mp4 70.06 MB
12. Appendix A1 Foundations of Deep Learning/14. Machine Learning Workflow.mp4 27.44 MB
12. Appendix A1 Foundations of Deep Learning/2. Differences between Classical Programming and Machine Learning.mp4 20.85 MB
12. Appendix A1 Foundations of Deep Learning/3. Learning Representations.mp4 77.24 MB
12. Appendix A1 Foundations of Deep Learning/4. What is Deep Learning.mp4 155.61 MB
12. Appendix A1 Foundations of Deep Learning/5. Learning Neural Networks.mp4 40.61 MB
12. Appendix A1 Foundations of Deep Learning/6. Why Now.mp4 9.07 MB
12. Appendix A1 Foundations of Deep Learning/7. Building Block Introduction.mp4 14.16 MB
12. Appendix A1 Foundations of Deep Learning/8. Tensors.mp4 16.88 MB
12. Appendix A1 Foundations of Deep Learning/9. Tensor Operations.mp4 88.79 MB
13. Computer Vision and Convolutional Neural Network (CNN)/1. Outline.mp4 63.66 MB
13. Computer Vision and Convolutional Neural Network (CNN)/10. Training Your CNN 1.mp4 124.88 MB
13. Computer Vision and Convolutional Neural Network (CNN)/11. Training Your CNN 2.mp4 128.54 MB
13. Computer Vision and Convolutional Neural Network (CNN)/12. Loading Previously Trained Model.mp4 11.21 MB
13. Computer Vision and Convolutional Neural Network (CNN)/13. Model Performance Comparison.mp4 79.75 MB
13. Computer Vision and Convolutional Neural Network (CNN)/14. Data Augmentation.mp4 28.48 MB
13. Computer Vision and Convolutional Neural Network (CNN)/15. Transfer Learning.mp4 97 MB
13. Computer Vision and Convolutional Neural Network (CNN)/16. Feature Extraction.mp4 111.14 MB
13. Computer Vision and Convolutional Neural Network (CNN)/17. State of the Art Tools.mp4 35.41 MB
13. Computer Vision and Convolutional Neural Network (CNN)/2. Neural Network Revision.mp4 43.81 MB
13. Computer Vision and Convolutional Neural Network (CNN)/3. Motivational Example.mp4 66.21 MB
13. Computer Vision and Convolutional Neural Network (CNN)/4. Visualizing CNN.mp4 141.94 MB
13. Computer Vision and Convolutional Neural Network (CNN)/5. Understanding CNN.mp4 30.03 MB
13. Computer Vision and Convolutional Neural Network (CNN)/6. Layer - Input.mp4 29.13 MB
13. Computer Vision and Convolutional Neural Network (CNN)/7. Layer - Filter.mp4 84.39 MB
13. Computer Vision and Convolutional Neural Network (CNN)/8. Activation Function.mp4 32.32 MB
13. Computer Vision and Convolutional Neural Network (CNN)/9. Pooling, Flatten, Dense.mp4 88.13 MB
2. Getting Started with Anaconda/1. Installing Applications and Creating Environment.mp4 38.42 MB
2. Getting Started with Anaconda/2. Hello World.mp4 51.22 MB
2. Getting Started with Anaconda/3. Iris Project 1 Working with Error Messages.mp4 89.84 MB
2. Getting Started with Anaconda/4. Iris Project 2 Reading CSV Data into Memory.mp4 64.56 MB
2. Getting Started with Anaconda/5. Iris Project 3 Loading data from Seaborn.mp4 55.87 MB
2. Getting Started with Anaconda/6. Iris Project 4 Visualization.mp4 93.49 MB
3. Regression/1. Scikit-Learn.mp4 48.45 MB
3. Regression/10. Multiple Regression 2.mp4 91.15 MB
3. Regression/11. Regularized Regression.mp4 44.35 MB
3. Regression/12. Polynomial Regression.mp4 110.78 MB
3. Regression/13. Dealing with Non-linear Relationships.mp4 62.69 MB
3. Regression/14. Feature Importance.mp4 36.25 MB
3. Regression/15. Data Preprocessing.mp4 135.55 MB
3. Regression/16. Variance-Bias Trade Off.mp4 68.7 MB
3. Regression/17. Learning Curve.mp4 56.37 MB
3. Regression/18. Cross Validation.mp4 48.04 MB
3. Regression/19. CV Illustration.mp4 127.23 MB
3. Regression/2. EDA.mp4 151.67 MB
3. Regression/3. Correlation Analysis and Feature Selection.mp4 22.58 MB
3. Regression/4. Correlation Analysis and Feature Selection.mp4 105.19 MB
3. Regression/5. Linear Regression with Scikit-Learn.mp4 76.98 MB
3. Regression/6. Five Steps Machine Learning Process.mp4 77.27 MB
3. Regression/7. Robust Regression.mp4 119.06 MB
3. Regression/8. Evaluate Regression Model Performance.mp4 99.66 MB
3. Regression/9. Multiple Regression 1.mp4 125.51 MB
4. Classification/1. Logistic Regression.mp4 119.59 MB
4. Classification/10. Precision Recall Tradeoff.mp4 102.01 MB
4. Classification/11. Altering the Precision Recall Tradeoff.mp4 20.93 MB
4. Classification/12. ROC.mp4 52.22 MB
4. Classification/2. Introduction to Classification.mp4 42.12 MB
4. Classification/3. Understanding MNIST.mp4 108.98 MB
4. Classification/4. SGD.mp4 57.3 MB
4. Classification/5. Performance Measure and Stratified k-Fold.mp4 51.54 MB
4. Classification/6. Confusion Matrix.mp4 54.71 MB
4. Classification/7. Precision.mp4 23.59 MB
4. Classification/8. Recall.mp4 19.64 MB
4. Classification/9. f1.mp4 12.11 MB
5. Support Vector Machine (SVM)/1. Support Vector Machine (SVM) Concepts.mp4 37.87 MB
5. Support Vector Machine (SVM)/2. Linear SVM Classification.mp4 80.94 MB
5. Support Vector Machine (SVM)/3. Polynomial Kernel.mp4 34.96 MB
5. Support Vector Machine (SVM)/4. Radial Basis Function.mp4 70.13 MB
5. Support Vector Machine (SVM)/5. Support Vector Regression.mp4 59.68 MB
6. Tree/1. Introduction to Decision Tree.mp4 43.86 MB
6. Tree/2. Training and Visualizing a Decision Tree.mp4 51.4 MB
6. Tree/3. Visualizing Boundary.mp4 54.72 MB
6. Tree/4. Tree Regression, Regularization and Over Fitting.mp4 40.05 MB
6. Tree/5. End to End Modeling.mp4 35.62 MB
6. Tree/6. Project HR.mp4 177.83 MB
6. Tree/7. Project HR with Google Colab.mp4 66.57 MB
7. Ensemble Machine Learning/1. Ensemble Learning Methods Introduction.mp4 37.17 MB
7. Ensemble Machine Learning/10. Ensemble of ensembles Part 2.mp4 37.85 MB
7. Ensemble Machine Learning/2. Bagging.mp4 165.44 MB
7. Ensemble Machine Learning/3. Random Forests and Extra-Trees.mp4 80.28 MB
7. Ensemble Machine Learning/4. AdaBoost.mp4 49.85 MB
7. Ensemble Machine Learning/5. Gradient Boosting Machine.mp4 21.96 MB
7. Ensemble Machine Learning/6. XGBoost Installation.mp4 22.26 MB
7. Ensemble Machine Learning/7. XGBoost.mp4 35.05 MB
7. Ensemble Machine Learning/8. Project HR - Human Resources Analytics.mp4 59.21 MB
7. Ensemble Machine Learning/9. Ensemble of Ensembles Part 1.mp4 46.4 MB
8. k-Nearest Neighbours (kNN)/1. kNN Introduction.mp4 62.95 MB
8. k-Nearest Neighbours (kNN)/2. Project Cancer Detection.mp4 75.73 MB
8. k-Nearest Neighbours (kNN)/4. Project Cancer Detection Part 1.mp4 49.4 MB
9. Unsupervised Learning Dimensionality Reduction/1. Dimensionality Reduction Concept.mp4 31.37 MB
9. Unsupervised Learning Dimensionality Reduction/2. PCA Introduction.mp4 49.03 MB
9. Unsupervised Learning Dimensionality Reduction/3. Project Wine.mp4 47.87 MB
9. Unsupervised Learning Dimensionality Reduction/4. Kernel PCA.mp4 36.61 MB
9. Unsupervised Learning Dimensionality Reduction/5. Kernel PCA Demo.mp4 21.44 MB
9. Unsupervised Learning Dimensionality Reduction/6. LDA vs PCA.mp4 34.15 MB
9. Unsupervised Learning Dimensionality Reduction/7. Project Abalone.mp4 30.74 MB
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