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Udemy Complete Machine Learning Course With Python
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Udemy Complete Machine Learning Course With Python
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文件列表
1 - Introduction/6 - Basic Python Concepts.mp4
509.0 MB
18 - KMeans Clusteringunsupervised model/48 - KMeans Clustering Program1.mp4
218.8 MB
17 - Random Forest/46 - Random Forest Defination and its practice program1.mp4
204.5 MB
12 - Logistic Regression/39 - What is Logistic Regression and program1.mp4
200.0 MB
22 - Model Selection/57 - Model Selection Program1.mp4
199.9 MB
20 - Principle Component AnalysisPCA/51 - Principle Component Analysis Program1.mp4
179.1 MB
13 - Support Vector MachineSVM/40 - What is Support Vector Machine.mp4
171.4 MB
15 - KNN Classifier/44 - KNN Classifer defination and its practice program1.mp4
160.9 MB
9 - Ridge Regression/35 - Ridge RegressionProgram 1.mp4
151.6 MB
14 - Naive Bayes Classification/43 - Naive Bayes Classification Program2.mp4
149.6 MB
16 - Decision Trees/45 - Decision Trees Defination and its program1.mp4
143.8 MB
3 - Exploratory Data Analysis/14 - Drawing Graphs.mp4
141.3 MB
7 - One Hot Encoding/29 - One Hot EncodingProgram 1.mp4
135.1 MB
10 - Lasso Regression/37 - What is Lasso regression and practice program1.mp4
133.5 MB
11 - ElasticNet Regression/38 - what is ElasticNet Regression and practice program1.mp4
130.8 MB
11 - ElasticNet Regression/38 - 10.ElasticNet-Regression.mp4
130.2 MB
8 - Polynomial Linear Regression/32 - Polynomial Linear Regression Program1.mp4
130.0 MB
4 - Outliers/18 - IQR and handling the outliers.mp4
126.3 MB
6 - Multiple Linear Regression/25 - Multiple Linear Regression program 1.mp4
124.3 MB
2 - Introduction to Machine Learning and Anaconda Installation/7 - Introduction to Machine Learning.mp4
119.8 MB
5 - Simple Linear Regression/23 - Simple linear regression Program2train and test data.mp4
108.9 MB
14 - Naive Bayes Classification/42 - Naive Bayes Classification Program1.mp4
102.2 MB
5 - Simple Linear Regression/22 - Simple linear regression Program1.mp4
100.2 MB
7 - One Hot Encoding/30 - One Hot EncodingProgram 2Third way.mp4
91.1 MB
3 - Exploratory Data Analysis/13 - Statistical Information.mp4
87.1 MB
6 - Multiple Linear Regression/24 - What is Multiple Linear Regression.mp4
86.2 MB
19 - Apriori Algorithm/49 - What is Apriori Algorithm.mp4
77.5 MB
2 - Introduction to Machine Learning and Anaconda Installation/8 - Anconda Installation.mp4
72.2 MB
22 - Model Selection/56 - What is Model Selection.mp4
67.5 MB
3 - Exploratory Data Analysis/11 - Modifying or removing unwanted data.mp4
56.1 MB
3 - Exploratory Data Analysis/12 - Retrieving Data.mp4
53.5 MB
4 - Outliers/17 - Finding the Outliers.mp4
53.0 MB
21 - KFold Cross Validation/55 - KFold Cross Validation Program1.mp4
52.2 MB
18 - KMeans Clusteringunsupervised model/47 - What is KMeans Clustering.mp4
48.3 MB
20 - Principle Component AnalysisPCA/52 - Principle Component Analysis Program2.mp4
48.3 MB
20 - Principle Component AnalysisPCA/50 - what is Principle Component AnalysisPCA.mp4
47.0 MB
21 - KFold Cross Validation/54 - What is KFold Cross Validation.mp4
41.8 MB
9 - Ridge Regression/34 - What is Regularization.mp4
41.0 MB
14 - Naive Bayes Classification/41 - What is Naive Bayes Classification.mp4
38.9 MB
5 - Simple Linear Regression/20 - What is simple liner regression model.mp4
35.5 MB
3 - Exploratory Data Analysis/10 - knowing initial details of dataset.mp4
33.7 MB
1 - Introduction/3 - Supervised learning vs Unsupervised Learning.mp4
32.0 MB
8 - Polynomial Linear Regression/31 - What is Polynomial Linear Regression.mp4
27.6 MB
3 - Exploratory Data Analysis/9 - What is Exploratory Data AnalysisEDA.mp4
26.0 MB
4 - Outliers/16 - What is Outliers.mp4
24.1 MB
9 - Ridge Regression/33 - What is Bias and Variance.mp4
22.4 MB
7 - One Hot Encoding/27 - One Hot EncodingFirst way.mp4
19.0 MB
5 - Simple Linear Regression/21 - What is rsquared Value.mp4
18.3 MB
1 - Introduction/4 - Dependent Variable vs Independent Variable.mp4
16.1 MB
7 - One Hot Encoding/26 - What Is One Hot Encoding.mp4
15.7 MB
1 - Introduction/1 - What Is Machine learning.mp4
14.8 MB
1 - Introduction/5 - What Does This Course Cover.mp4
10.5 MB
7 - One Hot Encoding/28 - One Hot EncodingSecond way.mp4
10.2 MB
9 - Ridge Regression/36 - Ridge RegressionAssignment.mp4
10.0 MB
1 - Introduction/2 - Key Skills needed to learn Machine learning.mp4
9.0 MB
5 - Simple Linear Regression/19 - What is Regression.mp4
7.8 MB
3 - Exploratory Data Analysis/15 - EDA Assignment.mp4
5.2 MB
20 - Principle Component AnalysisPCA/53 - Principle Component AnalysisAssignment.mp4
4.7 MB
23 - Assignment Solutions/58 - Assignment Solutions.mp4
1.6 MB
12 - Logistic Regression/39 - HR-comma.csv
566.8 kB
14 - Naive Bayes Classification/43 - spam.csv
502.6 kB
19 - Apriori Algorithm/49 - market.csv
431.1 kB
1 - Introduction/6 - Complete-basic-Python-in-90-mins.docx
424.4 kB
18 - KMeans Clusteringunsupervised model/47 - 17.K-Means-Clustering.docx
400.0 kB
18 - KMeans Clusteringunsupervised model/48 - 17.K-Means-Clustering.docx
400.0 kB
13 - Support Vector MachineSVM/40 - 12.Support-vector-machine-SVM.docx
327.3 kB
17 - Random Forest/46 - 16.Random-Forest.docx
268.1 kB
1 - Introduction/1 - what-is-machine-learning.docx
251.6 kB
1 - Introduction/6 - Basic Python Concepts.srt
146.0 kB
9 - Ridge Regression/33 - 8.Ridge-Regression.docx
125.5 kB
2 - Introduction to Machine Learning and Anaconda Installation/7 - 1.Introduction-to-Machine-Learning.docx
111.8 kB
16 - Decision Trees/45 - 15.Decision-Trees.docx
71.9 kB
20 - Principle Component AnalysisPCA/50 - 19.Principal-Component-Analysis-PCA.docx
68.0 kB
3 - Exploratory Data Analysis/15 - titanic.csv
61.2 kB
5 - Simple Linear Regression/19 - 4.Simple-Linear-Regression.docx
56.5 kB
23 - Assignment Solutions/58 - Principle-component-analysis-Assignment-solution.docx
49.5 kB
15 - KNN Classifier/44 - 14.KNN-Classifier.docx
45.2 kB
3 - Exploratory Data Analysis/9 - 2.Exploratory-Data-Analysis.docx
43.5 kB
17 - Random Forest/46 - Random Forest Defination and its practice program1.srt
40.8 kB
1 - Introduction/1 - cars.csv
39.0 kB
12 - Logistic Regression/39 - What is Logistic Regression and program1.srt
38.1 kB
20 - Principle Component AnalysisPCA/51 - Principle Component Analysis Program1.srt
36.1 kB
13 - Support Vector MachineSVM/40 - What is Support Vector Machine.srt
36.1 kB
18 - KMeans Clusteringunsupervised model/48 - KMeans Clustering Program1.srt
35.4 kB
9 - Ridge Regression/36 - boston-houses.csv
35.0 kB
10 - Lasso Regression/37 - boston-houses.csv
35.0 kB
11 - ElasticNet Regression/38 - boston-houses.csv
35.0 kB
23 - Assignment Solutions/58 - K-Means-Clustering-Assignment-Solution.docx
34.6 kB
2 - Introduction to Machine Learning and Anaconda Installation/7 - Introduction to Machine Learning.srt
33.5 kB
23 - Assignment Solutions/58 - Logistic-regression-Assignment-solution.docx
31.6 kB
8 - Polynomial Linear Regression/31 - 7.Polynomial-Linear-Regression.docx
31.0 kB
6 - Multiple Linear Regression/25 - Housing.csv
30.0 kB
22 - Model Selection/57 - Model Selection Program1.srt
28.3 kB
9 - Ridge Regression/35 - Ridge RegressionProgram 1.srt
28.2 kB
7 - One Hot Encoding/29 - One Hot EncodingProgram 1.srt
28.0 kB
23 - Assignment Solutions/58 - Random-Forest-Assignment-solution.docx
27.8 kB
15 - KNN Classifier/44 - KNN Classifer defination and its practice program1.srt
27.2 kB
14 - Naive Bayes Classification/41 - 13.Naive-Bayes-Classification.docx
26.6 kB
8 - Polynomial Linear Regression/32 - Polynomial Linear Regression Program1.srt
25.5 kB
16 - Decision Trees/45 - Decision Trees Defination and its program1.srt
25.2 kB
14 - Naive Bayes Classification/43 - Naive Bayes Classification Program2.srt
25.1 kB
6 - Multiple Linear Regression/25 - Multiple Linear Regression program 1.srt
24.8 kB
5 - Simple Linear Regression/23 - Simple linear regression Program2train and test data.srt
24.8 kB
11 - ElasticNet Regression/38 - 10.ElasticNet-Regression.srt
24.6 kB
10 - Lasso Regression/37 - What is Lasso regression and practice program1.srt
24.4 kB
11 - ElasticNet Regression/38 - diabetes-Assignment.csv
23.9 kB
15 - KNN Classifier/44 - diabetes-Assignment.csv
23.9 kB
11 - ElasticNet Regression/38 - what is ElasticNet Regression and practice program1.srt
23.8 kB
22 - Model Selection/56 - 21.Model-Selection.docx
23.4 kB
4 - Outliers/18 - IQR and handling the outliers.srt
23.0 kB
5 - Simple Linear Regression/22 - Simple linear regression Program1.srt
21.7 kB
6 - Multiple Linear Regression/24 - 5.Mutiple-Linear-Regression.docx
21.2 kB
4 - Outliers/16 - 3.Outliers.docx
20.9 kB
7 - One Hot Encoding/26 - 6.One-Hot-Encoding.docx
20.8 kB
3 - Exploratory Data Analysis/14 - Drawing Graphs.srt
20.5 kB
15 - KNN Classifier/44 - breast-cancer.csv
20.3 kB
12 - Logistic Regression/39 - 11.Logistic-Regression.docx
19.1 kB
14 - Naive Bayes Classification/42 - Naive Bayes Classification Program1.srt
18.8 kB
6 - Multiple Linear Regression/24 - What is Multiple Linear Regression.srt
18.2 kB
10 - Lasso Regression/37 - 9.Lasso-Regression.docx
17.9 kB
7 - One Hot Encoding/30 - One Hot EncodingProgram 2Third way.srt
16.9 kB
19 - Apriori Algorithm/49 - 18.Apriori-Algorithm.docx
16.4 kB
22 - Model Selection/56 - What is Model Selection.srt
15.9 kB
3 - Exploratory Data Analysis/13 - Statistical Information.srt
15.4 kB
21 - KFold Cross Validation/54 - 20.K-Fold-Cross-Validation.docx
15.2 kB
19 - Apriori Algorithm/49 - What is Apriori Algorithm.srt
14.7 kB
23 - Assignment Solutions/58 - Outlier-Assignment-solution.docx
14.3 kB
23 - Assignment Solutions/58 - OneHotEncoding-Assignment-solution.docx
14.2 kB
23 - Assignment Solutions/58 - KNN-Classifier-Assignment-Solution.docx
14.2 kB
23 - Assignment Solutions/58 - Polynomial-Linear-Regression-Assignment-solution.docx
14.0 kB
23 - Assignment Solutions/58 - EDA-assignment-solution.docx
13.8 kB
23 - Assignment Solutions/58 - Simple-Linear-Regression-Assignment-Solution.docx
13.8 kB
23 - Assignment Solutions/58 - Ridge-regression-assignment-solution.docx
13.6 kB
23 - Assignment Solutions/58 - support-Vector-Machine-SVM-Assignment-solution.docx
13.4 kB
23 - Assignment Solutions/58 - Lasso-regression-Assignment-Solution.docx
13.4 kB
23 - Assignment Solutions/58 - ElasticNet-Regression-Assignment-solution.docx
12.9 kB
23 - Assignment Solutions/58 - Naive-Bayes-classification-Assignment-solution.docx
12.7 kB
2 - Introduction to Machine Learning and Anaconda Installation/8 - Anaconda-installation-machine-learning.docx
12.4 kB
23 - Assignment Solutions/58 - Decision-Trees-Assignment-solution.docx
12.3 kB
23 - Assignment Solutions/58 - Multiple-linear-regression-Assignment-solution.docx
12.3 kB
18 - KMeans Clusteringunsupervised model/47 - What is KMeans Clustering.srt
12.0 kB
23 - Assignment Solutions/58 - K-Fold-Cross-Validation-Assignment-solution.docx
11.9 kB
21 - KFold Cross Validation/55 - KFold Cross Validation Program1.srt
11.9 kB
4 - Outliers/18 - Outliers-Assignment.docx
11.5 kB
22 - Model Selection/57 - processed.csv
11.3 kB
3 - Exploratory Data Analysis/11 - Modifying or removing unwanted data.srt
11.3 kB
4 - Outliers/17 - Finding the Outliers.srt
11.2 kB
5 - Simple Linear Regression/20 - What is simple liner regression model.srt
9.7 kB
14 - Naive Bayes Classification/41 - What is Naive Bayes Classification.srt
9.1 kB
3 - Exploratory Data Analysis/12 - Retrieving Data.srt
9.0 kB
20 - Principle Component AnalysisPCA/52 - Principle Component Analysis Program2.srt
8.4 kB
1 - Introduction/3 - Supervised learning vs Unsupervised Learning.srt
8.2 kB
3 - Exploratory Data Analysis/10 - knowing initial details of dataset.srt
8.2 kB
21 - KFold Cross Validation/54 - What is KFold Cross Validation.srt
8.1 kB
20 - Principle Component AnalysisPCA/50 - what is Principle Component AnalysisPCA.srt
7.8 kB
8 - Polynomial Linear Regression/31 - What is Polynomial Linear Regression.srt
6.2 kB
9 - Ridge Regression/34 - What is Regularization.srt
5.9 kB
9 - Ridge Regression/33 - What is Bias and Variance.srt
5.8 kB
3 - Exploratory Data Analysis/9 - What is Exploratory Data AnalysisEDA.srt
5.5 kB
4 - Outliers/16 - What is Outliers.srt
4.9 kB
10 - Lasso Regression/37 - Advertising-Assignment.csv
4.8 kB
5 - Simple Linear Regression/21 - What is rsquared Value.srt
4.5 kB
1 - Introduction/1 - What Is Machine learning.srt
4.4 kB
7 - One Hot Encoding/26 - What Is One Hot Encoding.srt
4.3 kB
7 - One Hot Encoding/27 - One Hot EncodingFirst way.srt
4.2 kB
1 - Introduction/4 - Dependent Variable vs Independent Variable.srt
3.8 kB
1 - Introduction/2 - Key Skills needed to learn Machine learning.srt
2.7 kB
9 - Ridge Regression/36 - Ridge RegressionAssignment.srt
2.7 kB
7 - One Hot Encoding/28 - One Hot EncodingSecond way.srt
2.4 kB
1 - Introduction/5 - What Does This Course Cover.srt
2.2 kB
5 - Simple Linear Regression/19 - What is Regression.srt
2.2 kB
20 - Principle Component AnalysisPCA/53 - Principle Component AnalysisAssignment.srt
1.2 kB
3 - Exploratory Data Analysis/15 - EDA Assignment.srt
917 Bytes
5 - Simple Linear Regression/23 - canada-percapita-Assignment.csv
860 Bytes
16 - Decision Trees/45 - salaries-Assignment.csv
638 Bytes
4 - Outliers/16 - solid-waste.csv
618 Bytes
4 - Outliers/18 - solid-waste.csv
618 Bytes
8 - Polynomial Linear Regression/32 - salary-experience-Assignment.csv
445 Bytes
17 - Random Forest/46 - salary-experience-Assignment.csv
445 Bytes
14 - Naive Bayes Classification/42 - cricket.csv
438 Bytes
16 - Decision Trees/45 - cricket.csv
438 Bytes
18 - KMeans Clusteringunsupervised model/48 - income.csv
381 Bytes
7 - One Hot Encoding/30 - carprices-Assignment.csv
378 Bytes
7 - One Hot Encoding/29 - homeprices-3.csv
366 Bytes
7 - One Hot Encoding/30 - homeprices-3.csv
366 Bytes
8 - Polynomial Linear Regression/32 - salary-position.csv
308 Bytes
23 - Assignment Solutions/58 - Assignment Solutions.srt
293 Bytes
5 - Simple Linear Regression/23 - salary-data.csv
172 Bytes
12 - Logistic Regression/39 - insurance-data-Assignment.csv
155 Bytes
2 - Introduction to Machine Learning and Anaconda Installation/8 - Anconda Installation.srt
139 Bytes
6 - Multiple Linear Regression/25 - homeprices-2.csv
130 Bytes
5 - Simple Linear Regression/22 - homeprices.csv
71 Bytes
9 - Ridge Regression/35 - train.csv
59 Bytes
9 - Ridge Regression/35 - test.csv
55 Bytes
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