[DesireCourse.Net] Udemy - The Complete Machine Learning Course with Python

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Creat Time：2024-07-01
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Last Active：2024-09-11
File Tags：DesireCourse Net Udemy The Complete Machine Learning Course with Python
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File List:

6. Tree/6. Project HR.mp4 182.10 MB
7. Ensemble Machine Learning/2. Bagging.mp4 169.42 MB
12. Appendix A1 Foundations of Deep Learning/4. What is Deep Learning.mp4 159.35 MB
3. Regression/2. EDA.mp4 155.31 MB
11. Deep Learning/3. Motivational Example - Project MNIST.mp4 148.44 MB
11. Deep Learning/1. Estimating Simple Function with Neural Networks.mp4 147.31 MB
13. Computer Vision and Convolutional Neural Network (CNN)/4. Visualizing CNN.mp4 145.35 MB
3. Regression/15. Data Preprocessing.mp4 138.80 MB
13. Computer Vision and Convolutional Neural Network (CNN)/11. Training Your CNN 2.mp4 131.63 MB
3. Regression/19. CV Illustration.mp4 130.29 MB
10. Unsupervised Learning Clustering/1. Clustering.mp4 128.70 MB
3. Regression/9. Multiple Regression 1.mp4 128.52 MB
13. Computer Vision and Convolutional Neural Network (CNN)/10. Training Your CNN 1.mp4 127.88 MB
4. Classification/1. Logistic Regression.mp4 122.46 MB
3. Regression/7. Robust Regression.mp4 121.92 MB
13. Computer Vision and Convolutional Neural Network (CNN)/16. Feature Extraction.mp4 113.81 MB
3. Regression/12. Polynomial Regression.mp4 113.44 MB
4. Classification/3. Understanding MNIST.mp4 111.59 MB
3. Regression/4. Correlation Analysis and Feature Selection.mp4 107.72 MB
4. Classification/10. Precision Recall Tradeoff.mp4 104.46 MB
3. Regression/8. Evaluate Regression Model Performance.mp4 102.05 MB
13. Computer Vision and Convolutional Neural Network (CNN)/15. Transfer Learning.mp4 99.33 MB
2. Getting Started with Anaconda/6. Iris Project 4 Visualization.mp4 95.73 MB
3. Regression/10. Multiple Regression 2.mp4 93.34 MB
2. Getting Started with Anaconda/3. Iris Project 1 Working with Error Messages.mp4 91.99 MB
12. Appendix A1 Foundations of Deep Learning/9. Tensor Operations.mp4 90.92 MB
13. Computer Vision and Convolutional Neural Network (CNN)/9. Pooling, Flatten, Dense.mp4 90.25 MB
13. Computer Vision and Convolutional Neural Network (CNN)/7. Layer - Filter.mp4 86.42 MB
5. Support Vector Machine (SVM)/2. Linear SVM Classification.mp4 82.88 MB
7. Ensemble Machine Learning/3. Random Forests and Extra-Trees.mp4 82.21 MB
13. Computer Vision and Convolutional Neural Network (CNN)/13. Model Performance Comparison.mp4 81.67 MB
3. Regression/6. Five Steps Machine Learning Process.mp4 79.12 MB
12. Appendix A1 Foundations of Deep Learning/3. Learning Representations.mp4 79.10 MB
3. Regression/5. Linear Regression with Scikit-Learn.mp4 78.83 MB
11. Deep Learning/5. Natural Language Processing - Binary Classification.mp4 77.87 MB
8. k-Nearest Neighbours (kNN)/2. Project Cancer Detection.mp4 77.55 MB
11. Deep Learning/4. Binary Classification Problem.mp4 73.84 MB
5. Support Vector Machine (SVM)/4. Radial Basis Function.mp4 71.82 MB
12. Appendix A1 Foundations of Deep Learning/13. Over and Under Fitting.mp4 71.74 MB
3. Regression/16. Variance-Bias Trade Off.mp4 70.35 MB
6. Tree/7. Project HR with Google Colab.mp4 68.16 MB
13. Computer Vision and Convolutional Neural Network (CNN)/3. Motivational Example.mp4 67.80 MB
2. Getting Started with Anaconda/4. Iris Project 2 Reading CSV Data into Memory.mp4 66.11 MB
13. Computer Vision and Convolutional Neural Network (CNN)/1. Outline.mp4 65.18 MB
8. k-Nearest Neighbours (kNN)/1. kNN Introduction.mp4 64.46 MB
3. Regression/13. Dealing with Non-linear Relationships.mp4 64.19 MB
5. Support Vector Machine (SVM)/5. Support Vector Regression.mp4 61.11 MB
7. Ensemble Machine Learning/8. Project HR - Human Resources Analytics.mp4 60.63 MB
10. Unsupervised Learning Clustering/2. k_Means Clustering.mp4 59.09 MB
4. Classification/4. SGD.mp4 58.67 MB

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