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

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文件数目：227个文件
文件大小：6.79 GB
收录时间：2020-04-03
访问次数：4
相关内容：DesireCourse Udemy Complete Machine Learning Course with Python

文件meta

6. Tree/6. Project HR.mp4
177.83 MB
7. Ensemble Machine Learning/2. Bagging.mp4
165.44 MB
12. Appendix A1 Foundations of Deep Learning/4. What is Deep Learning.mp4
155.61 MB
3. Regression/2. EDA.mp4
151.67 MB
11. Deep Learning/3. Motivational Example - Project MNIST.mp4
144.96 MB
11. Deep Learning/1. Estimating Simple Function with Neural Networks.mp4
143.85 MB
13. Computer Vision and Convolutional Neural Network (CNN)/4. Visualizing CNN.mp4
141.94 MB
3. Regression/15. Data Preprocessing.mp4
135.55 MB
13. Computer Vision and Convolutional Neural Network (CNN)/11. Training Your CNN 2.mp4
128.54 MB
3. Regression/19. CV Illustration.mp4
127.23 MB
10. Unsupervised Learning Clustering/1. Clustering.mp4
125.68 MB
3. Regression/9. Multiple Regression 1.mp4
125.51 MB
13. Computer Vision and Convolutional Neural Network (CNN)/10. Training Your CNN 1.mp4
124.88 MB
4. Classification/1. Logistic Regression.mp4
119.59 MB
3. Regression/7. Robust Regression.mp4
119.06 MB
13. Computer Vision and Convolutional Neural Network (CNN)/16. Feature Extraction.mp4
111.14 MB
3. Regression/12. Polynomial Regression.mp4
110.78 MB
4. Classification/3. Understanding MNIST.mp4
108.98 MB
3. Regression/4. Correlation Analysis and Feature Selection.mp4
105.19 MB
4. Classification/10. Precision Recall Tradeoff.mp4
102.01 MB
3. Regression/8. Evaluate Regression Model Performance.mp4
99.66 MB
13. Computer Vision and Convolutional Neural Network (CNN)/15. Transfer Learning.mp4
97 MB
2. Getting Started with Anaconda/6. Iris Project 4 Visualization.mp4
93.49 MB
3. Regression/10. Multiple Regression 2.mp4
91.15 MB
2. Getting Started with Anaconda/3. Iris Project 1 Working with Error Messages.mp4
89.84 MB
12. Appendix A1 Foundations of Deep Learning/9. Tensor Operations.mp4
88.79 MB
13. Computer Vision and Convolutional Neural Network (CNN)/9. Pooling, Flatten, Dense.mp4
88.13 MB
13. Computer Vision and Convolutional Neural Network (CNN)/7. Layer - Filter.mp4
84.39 MB
5. Support Vector Machine (SVM)/2. Linear SVM Classification.mp4
80.94 MB
7. Ensemble Machine Learning/3. Random Forests and Extra-Trees.mp4
80.28 MB
13. Computer Vision and Convolutional Neural Network (CNN)/13. Model Performance Comparison.mp4
79.75 MB
3. Regression/6. Five Steps Machine Learning Process.mp4
77.27 MB
12. Appendix A1 Foundations of Deep Learning/3. Learning Representations.mp4
77.24 MB
3. Regression/5. Linear Regression with Scikit-Learn.mp4
76.98 MB
11. Deep Learning/5. Natural Language Processing - Binary Classification.mp4
76.05 MB
8. k-Nearest Neighbours (kNN)/2. Project Cancer Detection.mp4
75.73 MB
11. Deep Learning/4. Binary Classification Problem.mp4
72.11 MB
5. Support Vector Machine (SVM)/4. Radial Basis Function.mp4
70.13 MB
12. Appendix A1 Foundations of Deep Learning/13. Over and Under Fitting.mp4
70.06 MB
3. Regression/16. Variance-Bias Trade Off.mp4
68.7 MB
6. Tree/7. Project HR with Google Colab.mp4
66.57 MB
13. Computer Vision and Convolutional Neural Network (CNN)/3. Motivational Example.mp4
66.21 MB
2. Getting Started with Anaconda/4. Iris Project 2 Reading CSV Data into Memory.mp4
64.56 MB
13. Computer Vision and Convolutional Neural Network (CNN)/1. Outline.mp4
63.65 MB
8. k-Nearest Neighbours (kNN)/1. kNN Introduction.mp4
62.95 MB
3. Regression/13. Dealing with Non-linear Relationships.mp4
62.69 MB
5. Support Vector Machine (SVM)/5. Support Vector Regression.mp4
59.68 MB
7. Ensemble Machine Learning/8. Project HR - Human Resources Analytics.mp4
59.21 MB
10. Unsupervised Learning Clustering/2. k_Means Clustering.mp4
57.71 MB
4. Classification/4. SGD.mp4
57.3 MB