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文件列表
02 Getting Started with Anaconda/attached_files/008 Navigating the Spyder Jupyter Notebook Interface/0204.zip
43.3 kB
02 Getting Started with Anaconda/attached_files/009 Downloading the IRIS Datasets/0205.zip
234.1 kB
02 Getting Started with Anaconda/attached_files/010 Data Exploration and Analysis/0206.zip
45.8 kB
02 Getting Started with Anaconda/attached_files/011 Presenting Your Data/0207.zip
1.1 MB
03 Regression/attached_files/014 Working with Scikit-Learn/0303.zip
933.8 kB
03 Regression/attached_files/015 Boston Housing Data - EDA/0304.zip
2.0 MB
03 Regression/attached_files/016 Correlation Analysis and Feature Selection/0305.zip
2.2 MB
03 Regression/attached_files/017 Simple Linear Regression Modelling with Boston Housing Data/0306.zip
2.7 MB
03 Regression/attached_files/018 Robust Regression/0307.zip
2.9 MB
03 Regression/attached_files/019 Evaluate Model Performance/0308.zip
3.1 MB
03 Regression/attached_files/020 Multiple Regression with statsmodel/0309.zip
2.7 MB
03 Regression/attached_files/021 Multiple Regression and Feature Importance/0310.zip
2.8 MB
03 Regression/attached_files/022 Ordinary Least Square Regression and Gradient Descent/0311.zip
144.8 kB
03 Regression/attached_files/023 Regularised Method for Regression/0312.zip
264.9 kB
03 Regression/attached_files/024 Polynomial Regression/0313.zip
383.9 kB
03 Regression/attached_files/025 Dealing with Non-linear relationships/0314.zip
185.1 kB
03 Regression/attached_files/026 Feature Importance Revisited/0315.zip
231.3 kB
03 Regression/attached_files/027 Data Pre-Processing 1/0316.zip
159.6 kB
03 Regression/attached_files/028 Data Pre-Processing 2/0317.zip
160.7 kB
03 Regression/attached_files/029 Variance Bias Trade Off - Validation Curve/0318.zip
540.8 kB
03 Regression/attached_files/030 Variance Bias Trade Off - Learning Curve/0319.zip
733.7 kB
03 Regression/attached_files/031 Cross Validation/0320.zip
97.0 kB
04 Classification/attached_files/033 Logistic Regression 1/0403.zip
19.9 kB
04 Classification/attached_files/034 Logistic Regression 2/0404.zip
20.5 kB
04 Classification/attached_files/035 MNIST Project 1 - Introduction/0405.zip
579.4 kB
04 Classification/attached_files/036 MNIST Project 2 - SGDClassifier/0406.zip
579.4 kB
04 Classification/attached_files/037 MNIST Project 3 - Performance Measures/0407.zip
579.8 kB
04 Classification/attached_files/038 MNIST Project 4 - Confusion Matrix Precision Recall and F1 Score/0408.zip
587.7 kB
04 Classification/attached_files/039 MNIST Project 5 - Precision and Recall Tradeoff/0409.zip
645.3 kB
04 Classification/attached_files/040 MNIST Project 6 - The ROC Curve/0410.zip
700.6 kB
05 Support Vector Machine SVM/attached_files/043 Support Vector Machine SVM Concepts/0502.zip
223.8 kB
05 Support Vector Machine SVM/attached_files/044 Linear SVM Classification/0503.zip
457.4 kB
05 Support Vector Machine SVM/attached_files/045 Polynomial Kernel/0504.zip
502.9 kB
05 Support Vector Machine SVM/attached_files/046 Gaussian Radial Basis Function/0505.zip
546.3 kB
05 Support Vector Machine SVM/attached_files/047 Support Vector Regression/0506.zip
586.8 kB
06 Tree/attached_files/050 What is Decision Tree/0602.zip
116.0 kB
06 Tree/attached_files/051 Training a Decision Tree/0603.zip
116.4 kB
06 Tree/attached_files/052 Visualising a Decision Trees/0604.zip
162.5 kB
06 Tree/attached_files/053 Decision Tree Learning Algorithm/0605.zip
234.8 kB
06 Tree/attached_files/054 Decision Tree Regression/0606.zip
284.6 kB
06 Tree/attached_files/055 Overfitting and Grid Search/0607.zip
305.1 kB
06 Tree/attached_files/056 Where to From Here/0608.zip
317.2 kB
06 Tree/attached_files/057 Project HR - Loading and preprocesing data/0609.zip
64.9 kB
06 Tree/attached_files/058 Project HR - Modelling/0610.zip
65.6 kB
07 Ensemble Machine Learning/attached_files/060 Ensemble Learning Methods Introduction/0702.zip
2.3 kB
07 Ensemble Machine Learning/attached_files/061 Bagging Part 1/0703.zip
7.8 kB
07 Ensemble Machine Learning/attached_files/062 Bagging Part 2/0704.zip
8.3 kB
07 Ensemble Machine Learning/attached_files/063 Random Forests/0705.zip
9.0 kB
07 Ensemble Machine Learning/attached_files/064 Extra-Trees/0706.zip
9.3 kB
07 Ensemble Machine Learning/attached_files/065 AdaBoost/0707.zip
9.0 kB
07 Ensemble Machine Learning/attached_files/066 Gradient Boosting Machine/0708.zip
61.9 kB
07 Ensemble Machine Learning/attached_files/067 XGBoost/0709.zip
3.0 kB
07 Ensemble Machine Learning/attached_files/068 Project HR - Human Resources Analytics/0710.zip
129.8 kB
07 Ensemble Machine Learning/attached_files/069 Ensemble of ensembles Part 1/0711.zip
3.7 kB
07 Ensemble Machine Learning/attached_files/070 Ensemble of ensembles Part 2/0712.zip
5.5 kB
08 k-Nearest Neighbours kNN/attached_files/072 kNN Concepts/0802.zip
1.6 kB
08 k-Nearest Neighbours kNN/attached_files/073 kNN and Iris Dataset Demo/0803.zip
26.8 kB
08 k-Nearest Neighbours kNN/attached_files/075 Project Cancer Detection Part 1/0805.zip
41.7 kB
08 k-Nearest Neighbours kNN/attached_files/076 Project Cancer Detection Part 2/0806.zip
41.7 kB
09 Dimensionality Reduction/attached_files/078 Dimensionality Reduction Concept/0902.zip
2.1 kB
09 Dimensionality Reduction/attached_files/079 PCA Introduction/0903.zip
89.4 kB
09 Dimensionality Reduction/attached_files/082 Project Abalone/09-Project-Abalone.zip
16.6 kB
09 Dimensionality Reduction/attached_files/083 Project Wine 2 Choosing the Number of Components/0906.zip
108.6 kB
09 Dimensionality Reduction/attached_files/084 Kernel PCA/0907.zip
110.8 kB
09 Dimensionality Reduction/attached_files/085 Kernel PCA Demo/0908.zip
110.8 kB
09 Dimensionality Reduction/attached_files/086 LDA Comparison between LDA and PCA/0909.zip
79.0 kB
10 Unsupervised Learning Clustering/attached_files/088 Clustering Concepts/1002.zip
450.2 kB
10 Unsupervised Learning Clustering/attached_files/089 MLextend/1003.zip
450.2 kB
10 Unsupervised Learning Clustering/attached_files/090 Wards Agglomerative Hierarchical Clustering/1004.zip
450.2 kB
10 Unsupervised Learning Clustering/attached_files/091 Truncating Dendrogram/1005.zip
450.2 kB
10 Unsupervised Learning Clustering/attached_files/092 k-Means Clustering/1006.zip
450.2 kB
10 Unsupervised Learning Clustering/attached_files/093 Elbow Method/1007.zip
450.2 kB
10 Unsupervised Learning Clustering/attached_files/094 Silhouette Analysis/1008.zip
450.2 kB
10 Unsupervised Learning Clustering/attached_files/095 Mean Shift/1009.zip
450.2 kB
02 Getting Started with Anaconda/quizzes/001 Getting Started.html
11.1 kB
03 Regression/quizzes/002 Machine Learning Basic Concepts.html
9.2 kB
03 Regression/quizzes/003 Section 3.html
11.7 kB
01 Introduction/001 What Does the Course Cover.mp4
10.4 MB
01 Introduction/002 How to Succeed in This Course.html
2.1 kB
01 Introduction/003 Project Files.html
1.9 kB
02 Getting Started with Anaconda/004 Windows OS Downloading Installing Anaconda.mp4
67.5 MB
02 Getting Started with Anaconda/005 Windows OS Managing Environment.mp4
19.7 MB
02 Getting Started with Anaconda/006 Mac OS Intructions on Installing Anaconda and Managing Environment.html
516 Bytes
02 Getting Started with Anaconda/007 Practice Activity Create a New Environment.html
737 Bytes
02 Getting Started with Anaconda/008 Navigating the Spyder Jupyter Notebook Interface.mp4
43.4 MB
02 Getting Started with Anaconda/009 Downloading the IRIS Datasets.mp4
11.0 MB
02 Getting Started with Anaconda/010 Data Exploration and Analysis.mp4
36.5 MB
02 Getting Started with Anaconda/011 Presenting Your Data.mp4
48.8 MB
03 Regression/012 Introduction.mp4
12.3 MB
03 Regression/013 Categories of Machine Learning.mp4
23.4 MB
03 Regression/014 Working with Scikit-Learn.mp4
48.2 MB
03 Regression/015 Boston Housing Data - EDA.mp4
64.4 MB
03 Regression/016 Correlation Analysis and Feature Selection.mp4
23.7 MB
03 Regression/017 Simple Linear Regression Modelling with Boston Housing Data.mp4
35.4 MB
03 Regression/018 Robust Regression.mp4
35.1 MB
03 Regression/019 Evaluate Model Performance.mp4
62.0 MB
03 Regression/020 Multiple Regression with statsmodel.mp4
62.5 MB
03 Regression/021 Multiple Regression and Feature Importance.mp4
46.8 MB
03 Regression/022 Ordinary Least Square Regression and Gradient Descent.mp4
52.5 MB
03 Regression/023 Regularised Method for Regression.mp4
50.1 MB
03 Regression/024 Polynomial Regression.mp4
45.9 MB
03 Regression/025 Dealing with Non-linear relationships.mp4
29.8 MB
03 Regression/026 Feature Importance Revisited.mp4
27.5 MB
03 Regression/027 Data Pre-Processing 1.mp4
36.6 MB
03 Regression/028 Data Pre-Processing 2.mp4
52.0 MB
03 Regression/029 Variance Bias Trade Off - Validation Curve.mp4
46.0 MB
03 Regression/030 Variance Bias Trade Off - Learning Curve.mp4
44.5 MB
03 Regression/031 Cross Validation.mp4
46.9 MB
04 Classification/032 Introduction.mp4
8.3 MB
04 Classification/033 Logistic Regression 1.mp4
28.2 MB
04 Classification/034 Logistic Regression 2.mp4
43.8 MB
04 Classification/035 MNIST Project 1 - Introduction.mp4
36.2 MB
04 Classification/036 MNIST Project 2 - SGDClassifier.mp4
26.7 MB
04 Classification/037 MNIST Project 3 - Performance Measures.mp4
27.7 MB
04 Classification/038 MNIST Project 4 - Confusion Matrix Precision Recall and F1 Score.mp4
48.3 MB
04 Classification/039 MNIST Project 5 - Precision and Recall Tradeoff.mp4
46.0 MB
04 Classification/040 MNIST Project 6 - The ROC Curve.mp4
35.4 MB
04 Classification/041 MNIST Exercise.html
826 Bytes
05 Support Vector Machine SVM/042 Introduction.mp4
4.9 MB
05 Support Vector Machine SVM/043 Support Vector Machine SVM Concepts.mp4
54.3 MB
05 Support Vector Machine SVM/044 Linear SVM Classification.mp4
33.1 MB
05 Support Vector Machine SVM/045 Polynomial Kernel.mp4
52.8 MB
05 Support Vector Machine SVM/046 Gaussian Radial Basis Function.mp4
47.0 MB
05 Support Vector Machine SVM/047 Support Vector Regression.mp4
18.2 MB
05 Support Vector Machine SVM/048 Advantages and Disadvantages of SVM.mp4
13.7 MB
06 Tree/049 Introduction.mp4
5.9 MB
06 Tree/050 What is Decision Tree.mp4
35.7 MB
06 Tree/051 Training a Decision Tree.mp4
17.4 MB
06 Tree/052 Visualising a Decision Trees.mp4
57.9 MB
06 Tree/053 Decision Tree Learning Algorithm.mp4
38.8 MB
06 Tree/054 Decision Tree Regression.mp4
35.4 MB
06 Tree/055 Overfitting and Grid Search.mp4
57.1 MB
06 Tree/056 Where to From Here.mp4
12.2 MB
06 Tree/057 Project HR - Loading and preprocesing data.mp4
59.5 MB
06 Tree/058 Project HR - Modelling.mp4
17.3 MB
07 Ensemble Machine Learning/059 Introduction.mp4
5.5 MB
07 Ensemble Machine Learning/060 Ensemble Learning Methods Introduction.mp4
29.0 MB
07 Ensemble Machine Learning/061 Bagging Part 1.mp4
58.2 MB
07 Ensemble Machine Learning/062 Bagging Part 2.mp4
39.1 MB
07 Ensemble Machine Learning/063 Random Forests.mp4
45.2 MB
07 Ensemble Machine Learning/064 Extra-Trees.mp4
22.6 MB
07 Ensemble Machine Learning/065 AdaBoost.mp4
41.8 MB
07 Ensemble Machine Learning/066 Gradient Boosting Machine.mp4
47.0 MB
07 Ensemble Machine Learning/067 XGBoost.mp4
53.8 MB
07 Ensemble Machine Learning/068 Project HR - Human Resources Analytics.mp4
92.4 MB
07 Ensemble Machine Learning/069 Ensemble of ensembles Part 1.mp4
54.6 MB
07 Ensemble Machine Learning/070 Ensemble of ensembles Part 2.mp4
47.1 MB
08 k-Nearest Neighbours kNN/071 kNN Introduction.mp4
4.6 MB
08 k-Nearest Neighbours kNN/072 kNN Concepts.mp4
15.7 MB
08 k-Nearest Neighbours kNN/073 kNN and Iris Dataset Demo.mp4
21.8 MB
08 k-Nearest Neighbours kNN/074 Distance Metric.mp4
13.7 MB
08 k-Nearest Neighbours kNN/075 Project Cancer Detection Part 1.mp4
51.8 MB
08 k-Nearest Neighbours kNN/076 Project Cancer Detection Part 2.mp4
51.0 MB
09 Dimensionality Reduction/077 Introduction.mp4
3.8 MB
09 Dimensionality Reduction/078 Dimensionality Reduction Concept.mp4
27.0 MB
09 Dimensionality Reduction/079 PCA Introduction.mp4
44.3 MB
09 Dimensionality Reduction/080 Dimensionality Reduction Demo.mp4
15.3 MB
09 Dimensionality Reduction/081 Project Wine 1 Dimensionality Reduction with PCA.mp4
48.4 MB
09 Dimensionality Reduction/082 Project Abalone.html
458 Bytes
09 Dimensionality Reduction/083 Project Wine 2 Choosing the Number of Components.mp4
19.7 MB
09 Dimensionality Reduction/084 Kernel PCA.mp4
37.6 MB
09 Dimensionality Reduction/085 Kernel PCA Demo.mp4
16.8 MB
09 Dimensionality Reduction/086 LDA Comparison between LDA and PCA.mp4
17.7 MB
10 Unsupervised Learning Clustering/087 Introduction.mp4
4.2 MB
10 Unsupervised Learning Clustering/088 Clustering Concepts.mp4
18.3 MB
10 Unsupervised Learning Clustering/089 MLextend.mp4
23.7 MB
10 Unsupervised Learning Clustering/090 Wards Agglomerative Hierarchical Clustering.mp4
46.3 MB
10 Unsupervised Learning Clustering/091 Truncating Dendrogram.mp4
59.2 MB
10 Unsupervised Learning Clustering/092 k-Means Clustering.mp4
38.4 MB
10 Unsupervised Learning Clustering/093 Elbow Method.mp4
16.5 MB
10 Unsupervised Learning Clustering/094 Silhouette Analysis.mp4
17.3 MB
10 Unsupervised Learning Clustering/095 Mean Shift.mp4
26.9 MB
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252 Bytes
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123 Bytes
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119 Bytes
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115 Bytes
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