Udemy Complete Machine Learning Course With Python

Creation Time	July 27, 2024, 2:40 p.m.
Last Access Time	Nov. 4, 2024, 11:22 p.m.
File Size	4.7 GB
Keywords	Complete Python Udemy Machine Course Learning With
Total Requests	48
Total Files	194
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1 - Introduction/6 - Basic Python Concepts.mp4 485.4 MB
18 - KMeans Clusteringunsupervised model/48 - KMeans Clustering Program1.mp4 208.7 MB
17 - Random Forest/46 - Random Forest Defination and its practice program1.mp4 195.1 MB
12 - Logistic Regression/39 - What is Logistic Regression and program1.mp4 190.8 MB
22 - Model Selection/57 - Model Selection Program1.mp4 190.6 MB
20 - Principle Component AnalysisPCA/51 - Principle Component Analysis Program1.mp4 170.8 MB
13 - Support Vector MachineSVM/40 - What is Support Vector Machine.mp4 163.5 MB
15 - KNN Classifier/44 - KNN Classifer defination and its practice program1.mp4 153.4 MB
9 - Ridge Regression/35 - Ridge RegressionProgram 1.mp4 144.6 MB
14 - Naive Bayes Classification/43 - Naive Bayes Classification Program2.mp4 142.6 MB
16 - Decision Trees/45 - Decision Trees Defination and its program1.mp4 137.2 MB
3 - Exploratory Data Analysis/14 - Drawing Graphs.mp4 134.7 MB
7 - One Hot Encoding/29 - One Hot EncodingProgram 1.mp4 128.9 MB
10 - Lasso Regression/37 - What is Lasso regression and practice program1.mp4 127.3 MB
11 - ElasticNet Regression/38 - what is ElasticNet Regression and practice program1.mp4 124.8 MB
11 - ElasticNet Regression/38 - 10.ElasticNet-Regression.mp4 124.2 MB
8 - Polynomial Linear Regression/32 - Polynomial Linear Regression Program1.mp4 124.0 MB
4 - Outliers/18 - IQR and handling the outliers.mp4 120.4 MB
6 - Multiple Linear Regression/25 - Multiple Linear Regression program 1.mp4 118.6 MB
2 - Introduction to Machine Learning and Anaconda Installation/7 - Introduction to Machine Learning.mp4 114.2 MB
5 - Simple Linear Regression/23 - Simple linear regression Program2train and test data.mp4 103.8 MB
14 - Naive Bayes Classification/42 - Naive Bayes Classification Program1.mp4 97.5 MB
5 - Simple Linear Regression/22 - Simple linear regression Program1.mp4 95.5 MB
7 - One Hot Encoding/30 - One Hot EncodingProgram 2Third way.mp4 86.9 MB
3 - Exploratory Data Analysis/13 - Statistical Information.mp4 83.1 MB
6 - Multiple Linear Regression/24 - What is Multiple Linear Regression.mp4 82.2 MB
19 - Apriori Algorithm/49 - What is Apriori Algorithm.mp4 73.9 MB
2 - Introduction to Machine Learning and Anaconda Installation/8 - Anconda Installation.mp4 68.9 MB
22 - Model Selection/56 - What is Model Selection.mp4 64.4 MB
3 - Exploratory Data Analysis/11 - Modifying or removing unwanted data.mp4 53.5 MB
3 - Exploratory Data Analysis/12 - Retrieving Data.mp4 51.0 MB
4 - Outliers/17 - Finding the Outliers.mp4 50.5 MB
21 - KFold Cross Validation/55 - KFold Cross Validation Program1.mp4 49.7 MB
18 - KMeans Clusteringunsupervised model/47 - What is KMeans Clustering.mp4 46.1 MB
20 - Principle Component AnalysisPCA/52 - Principle Component Analysis Program2.mp4 46.0 MB
20 - Principle Component AnalysisPCA/50 - what is Principle Component AnalysisPCA.mp4 44.8 MB
21 - KFold Cross Validation/54 - What is KFold Cross Validation.mp4 39.9 MB
9 - Ridge Regression/34 - What is Regularization.mp4 39.1 MB
14 - Naive Bayes Classification/41 - What is Naive Bayes Classification.mp4 37.1 MB
5 - Simple Linear Regression/20 - What is simple liner regression model.mp4 33.8 MB
3 - Exploratory Data Analysis/10 - knowing initial details of dataset.mp4 32.2 MB
1 - Introduction/3 - Supervised learning vs Unsupervised Learning.mp4 30.6 MB
8 - Polynomial Linear Regression/31 - What is Polynomial Linear Regression.mp4 26.3 MB
3 - Exploratory Data Analysis/9 - What is Exploratory Data AnalysisEDA.mp4 24.8 MB
4 - Outliers/16 - What is Outliers.mp4 23.0 MB
9 - Ridge Regression/33 - What is Bias and Variance.mp4 21.3 MB
7 - One Hot Encoding/27 - One Hot EncodingFirst way.mp4 18.1 MB
5 - Simple Linear Regression/21 - What is rsquared Value.mp4 17.5 MB
1 - Introduction/4 - Dependent Variable vs Independent Variable.mp4 15.3 MB
7 - One Hot Encoding/26 - What Is One Hot Encoding.mp4 14.9 MB
1 - Introduction/1 - What Is Machine learning.mp4 14.1 MB
1 - Introduction/5 - What Does This Course Cover.mp4 10.1 MB
7 - One Hot Encoding/28 - One Hot EncodingSecond way.mp4 9.7 MB
9 - Ridge Regression/36 - Ridge RegressionAssignment.mp4 9.5 MB
1 - Introduction/2 - Key Skills needed to learn Machine learning.mp4 8.6 MB
5 - Simple Linear Regression/19 - What is Regression.mp4 7.4 MB
3 - Exploratory Data Analysis/15 - EDA Assignment.mp4 5.0 MB
20 - Principle Component AnalysisPCA/53 - Principle Component AnalysisAssignment.mp4 4.5 MB
23 - Assignment Solutions/58 - Assignment Solutions.mp4 1.5 MB
12 - Logistic Regression/39 - HR-comma.csv 553.5 KB
14 - Naive Bayes Classification/43 - spam.csv 490.8 KB
19 - Apriori Algorithm/49 - market.csv 421.0 KB
1 - Introduction/6 - Complete-basic-Python-in-90-mins.docx 414.4 KB
18 - KMeans Clusteringunsupervised model/47 - 17.K-Means-Clustering.docx 390.7 KB
18 - KMeans Clusteringunsupervised model/48 - 17.K-Means-Clustering.docx 390.7 KB
13 - Support Vector MachineSVM/40 - 12.Support-vector-machine-SVM.docx 319.6 KB
17 - Random Forest/46 - 16.Random-Forest.docx 261.8 KB
1 - Introduction/1 - what-is-machine-learning.docx 245.7 KB
1 - Introduction/6 - Basic Python Concepts.srt 142.6 KB
9 - Ridge Regression/33 - 8.Ridge-Regression.docx 122.6 KB
2 - Introduction to Machine Learning and Anaconda Installation/7 - 1.Introduction-to-Machine-Learning.docx 109.2 KB
16 - Decision Trees/45 - 15.Decision-Trees.docx 70.2 KB
20 - Principle Component AnalysisPCA/50 - 19.Principal-Component-Analysis-PCA.docx 66.4 KB
3 - Exploratory Data Analysis/15 - titanic.csv 59.8 KB
5 - Simple Linear Regression/19 - 4.Simple-Linear-Regression.docx 55.2 KB
23 - Assignment Solutions/58 - Principle-component-analysis-Assignment-solution.docx 48.3 KB
15 - KNN Classifier/44 - 14.KNN-Classifier.docx 44.2 KB
3 - Exploratory Data Analysis/9 - 2.Exploratory-Data-Analysis.docx 42.5 KB
17 - Random Forest/46 - Random Forest Defination and its practice program1.srt 39.8 KB
1 - Introduction/1 - cars.csv 38.1 KB
12 - Logistic Regression/39 - What is Logistic Regression and program1.srt 37.2 KB
20 - Principle Component AnalysisPCA/51 - Principle Component Analysis Program1.srt 35.3 KB
13 - Support Vector MachineSVM/40 - What is Support Vector Machine.srt 35.3 KB
18 - KMeans Clusteringunsupervised model/48 - KMeans Clustering Program1.srt 34.6 KB
9 - Ridge Regression/36 - boston-houses.csv 34.2 KB
10 - Lasso Regression/37 - boston-houses.csv 34.2 KB
11 - ElasticNet Regression/38 - boston-houses.csv 34.2 KB
23 - Assignment Solutions/58 - K-Means-Clustering-Assignment-Solution.docx 33.8 KB
2 - Introduction to Machine Learning and Anaconda Installation/7 - Introduction to Machine Learning.srt 32.7 KB
23 - Assignment Solutions/58 - Logistic-regression-Assignment-solution.docx 30.8 KB
8 - Polynomial Linear Regression/31 - 7.Polynomial-Linear-Regression.docx 30.3 KB
6 - Multiple Linear Regression/25 - Housing.csv 29.3 KB
22 - Model Selection/57 - Model Selection Program1.srt 27.6 KB
9 - Ridge Regression/35 - Ridge RegressionProgram 1.srt 27.5 KB
7 - One Hot Encoding/29 - One Hot EncodingProgram 1.srt 27.3 KB
23 - Assignment Solutions/58 - Random-Forest-Assignment-solution.docx 27.1 KB
15 - KNN Classifier/44 - KNN Classifer defination and its practice program1.srt 26.6 KB
14 - Naive Bayes Classification/41 - 13.Naive-Bayes-Classification.docx 26.0 KB
8 - Polynomial Linear Regression/32 - Polynomial Linear Regression Program1.srt 24.9 KB
16 - Decision Trees/45 - Decision Trees Defination and its program1.srt 24.7 KB
14 - Naive Bayes Classification/43 - Naive Bayes Classification Program2.srt 24.5 KB
6 - Multiple Linear Regression/25 - Multiple Linear Regression program 1.srt 24.3 KB
5 - Simple Linear Regression/23 - Simple linear regression Program2train and test data.srt 24.2 KB
11 - ElasticNet Regression/38 - 10.ElasticNet-Regression.srt 24.1 KB
10 - Lasso Regression/37 - What is Lasso regression and practice program1.srt 23.8 KB
11 - ElasticNet Regression/38 - diabetes-Assignment.csv 23.3 KB
15 - KNN Classifier/44 - diabetes-Assignment.csv 23.3 KB
11 - ElasticNet Regression/38 - what is ElasticNet Regression and practice program1.srt 23.2 KB
22 - Model Selection/56 - 21.Model-Selection.docx 22.9 KB
4 - Outliers/18 - IQR and handling the outliers.srt 22.4 KB
5 - Simple Linear Regression/22 - Simple linear regression Program1.srt 21.2 KB
6 - Multiple Linear Regression/24 - 5.Mutiple-Linear-Regression.docx 20.7 KB
4 - Outliers/16 - 3.Outliers.docx 20.4 KB
7 - One Hot Encoding/26 - 6.One-Hot-Encoding.docx 20.3 KB
3 - Exploratory Data Analysis/14 - Drawing Graphs.srt 20.0 KB
15 - KNN Classifier/44 - breast-cancer.csv 19.8 KB
12 - Logistic Regression/39 - 11.Logistic-Regression.docx 18.6 KB
14 - Naive Bayes Classification/42 - Naive Bayes Classification Program1.srt 18.4 KB
6 - Multiple Linear Regression/24 - What is Multiple Linear Regression.srt 17.8 KB
10 - Lasso Regression/37 - 9.Lasso-Regression.docx 17.5 KB
7 - One Hot Encoding/30 - One Hot EncodingProgram 2Third way.srt 16.5 KB
19 - Apriori Algorithm/49 - 18.Apriori-Algorithm.docx 16.0 KB
22 - Model Selection/56 - What is Model Selection.srt 15.5 KB
3 - Exploratory Data Analysis/13 - Statistical Information.srt 15.0 KB
21 - KFold Cross Validation/54 - 20.K-Fold-Cross-Validation.docx 14.9 KB
19 - Apriori Algorithm/49 - What is Apriori Algorithm.srt 14.4 KB
23 - Assignment Solutions/58 - Outlier-Assignment-solution.docx 14.0 KB
23 - Assignment Solutions/58 - OneHotEncoding-Assignment-solution.docx 13.9 KB
23 - Assignment Solutions/58 - KNN-Classifier-Assignment-Solution.docx 13.9 KB
23 - Assignment Solutions/58 - Polynomial-Linear-Regression-Assignment-solution.docx 13.6 KB
23 - Assignment Solutions/58 - EDA-assignment-solution.docx 13.5 KB
23 - Assignment Solutions/58 - Simple-Linear-Regression-Assignment-Solution.docx 13.5 KB
23 - Assignment Solutions/58 - Ridge-regression-assignment-solution.docx 13.3 KB
23 - Assignment Solutions/58 - support-Vector-Machine-SVM-Assignment-solution.docx 13.1 KB
23 - Assignment Solutions/58 - Lasso-regression-Assignment-Solution.docx 13.1 KB
23 - Assignment Solutions/58 - ElasticNet-Regression-Assignment-solution.docx 12.6 KB
23 - Assignment Solutions/58 - Naive-Bayes-classification-Assignment-solution.docx 12.4 KB
2 - Introduction to Machine Learning and Anaconda Installation/8 - Anaconda-installation-machine-learning.docx 12.1 KB
23 - Assignment Solutions/58 - Decision-Trees-Assignment-solution.docx 12.0 KB
23 - Assignment Solutions/58 - Multiple-linear-regression-Assignment-solution.docx 12.0 KB
18 - KMeans Clusteringunsupervised model/47 - What is KMeans Clustering.srt 11.7 KB
23 - Assignment Solutions/58 - K-Fold-Cross-Validation-Assignment-solution.docx 11.7 KB
21 - KFold Cross Validation/55 - KFold Cross Validation Program1.srt 11.7 KB
4 - Outliers/18 - Outliers-Assignment.docx 11.2 KB
22 - Model Selection/57 - processed.csv 11.1 KB
3 - Exploratory Data Analysis/11 - Modifying or removing unwanted data.srt 11.0 KB
4 - Outliers/17 - Finding the Outliers.srt 10.9 KB
5 - Simple Linear Regression/20 - What is simple liner regression model.srt 9.5 KB
14 - Naive Bayes Classification/41 - What is Naive Bayes Classification.srt 8.9 KB
3 - Exploratory Data Analysis/12 - Retrieving Data.srt 8.8 KB
20 - Principle Component AnalysisPCA/52 - Principle Component Analysis Program2.srt 8.2 KB
1 - Introduction/3 - Supervised learning vs Unsupervised Learning.srt 8.0 KB
3 - Exploratory Data Analysis/10 - knowing initial details of dataset.srt 8.0 KB
21 - KFold Cross Validation/54 - What is KFold Cross Validation.srt 7.9 KB
20 - Principle Component AnalysisPCA/50 - what is Principle Component AnalysisPCA.srt 7.6 KB
8 - Polynomial Linear Regression/31 - What is Polynomial Linear Regression.srt 6.0 KB
9 - Ridge Regression/34 - What is Regularization.srt 5.8 KB
9 - Ridge Regression/33 - What is Bias and Variance.srt 5.6 KB
3 - Exploratory Data Analysis/9 - What is Exploratory Data AnalysisEDA.srt 5.3 KB
4 - Outliers/16 - What is Outliers.srt 4.8 KB
10 - Lasso Regression/37 - Advertising-Assignment.csv 4.6 KB
5 - Simple Linear Regression/21 - What is rsquared Value.srt 4.4 KB
1 - Introduction/1 - What Is Machine learning.srt 4.3 KB
7 - One Hot Encoding/26 - What Is One Hot Encoding.srt 4.2 KB
7 - One Hot Encoding/27 - One Hot EncodingFirst way.srt 4.1 KB
1 - Introduction/4 - Dependent Variable vs Independent Variable.srt 3.7 KB
1 - Introduction/2 - Key Skills needed to learn Machine learning.srt 2.6 KB
9 - Ridge Regression/36 - Ridge RegressionAssignment.srt 2.6 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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