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[FTUForum.com] [UDEMY] A-Z Machine Learning using Azure Machine Learning (AzureML) [FTU]
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[FTUForum.com] [UDEMY] A-Z Machine Learning using Azure Machine Learning (AzureML) [FTU]
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文件列表
07. Regression Analysis/3. [Hands On] - Linear Regression model using OLS.mp4
95.5 MB
12. Text Analytics and Natural Language Processing/5. [Hands On] - Classify Customer Complaints using Text Analytics.mp4
95.4 MB
12. Text Analytics and Natural Language Processing/4. Feature Hashing.mp4
78.8 MB
01. Basics of Machine Learning/4. Why Machine Learning is the Future.mp4
72.1 MB
10. Feature Selection - Select a subset of Variables or features with highest impact/9. [Hands On] - Fisher Based LDA - Experiment.mp4
64.1 MB
01. Basics of Machine Learning/5. What is Machine Learning.mp4
57.4 MB
12. Text Analytics and Natural Language Processing/2. Text Pre-Processing.mp4
57.3 MB
04. Classification/2. [Hands On] -Logistic Regression - Build Two-Class Loan Approval Prediction Model.mp4
54.7 MB
12. Text Analytics and Natural Language Processing/3. Bag Of Words and N-Gram Models for Text features.mp4
52.4 MB
13. Thank You and Bonus Lecture/1. Way Forward.mp4
51.6 MB
10. Feature Selection - Select a subset of Variables or features with highest impact/2. Pearson Correlation Coefficient.mp4
49.5 MB
12. Text Analytics and Natural Language Processing/1. What is Text Analytics or Natural Language Processing.mp4
42.7 MB
03. Data Processing/5. [Hands On] - Apply SQL Transformation, Clean Missing Data, Edit Metadata.mp4
40.8 MB
11. Recommendation System/5. [Hands On] - Restaurant Recommendation Experiment.mp4
37.9 MB
03. Data Processing/6. [Hands On] - Sample and Split Data - Partition or Sample, Train and Test Data.mp4
37.2 MB
04. Classification/12. [Hands On] - Two Class Decision Forest - Adult Census Income Prediction.mp4
36.8 MB
11. Recommendation System/1. What is a Recommendation System.mp4
36.7 MB
08. Clustering/2. [Hands On] - Cluster Analysis Experiment 1.mp4
32.4 MB
04. Classification/4. Understanding the Confusion Matrix, AUC, Accuracy, Precision, Recall and F1Score.mp4
30.9 MB
07. Regression Analysis/5. Gradient Descent.mp4
29.0 MB
03. Data Processing/4. [Hands On] -Data Transform - Add RowsColumns, Remove Duplicates, Select Columns.mp4
27.8 MB
04. Classification/10. [Hands On] Two-Class Boosted Decision Tree - Build Bank Telemarketing Prediction.mp4
26.4 MB
10. Feature Selection - Select a subset of Variables or features with highest impact/8. Fisher Based LDA - Intuition.mp4
25.3 MB
02. Getting Started with Azure ML/2. What is Azure ML and high level architecture..mp4
24.0 MB
08. Clustering/1. What is Cluster Analysis.mp4
23.5 MB
03. Data Processing/2. [Hands On] - Data Input-Output - Convert and Unpack.mp4
23.2 MB
05. Hyperparameter Tuning/1. [Hands On] - Tune Hyperparameter for Best Parameter Selection.mp4
23.0 MB
04. Classification/6. [Hands On] Logistic Regression - Build Multi-Class Wine Quality Prediction Model.mp4
20.6 MB
04. Classification/3. Logistic Regression - Understand Parameters and Their Impact.mp4
20.5 MB
01. Basics of Machine Learning/8. Types of Machine Learning Models - Classification, Regression, Clustering etc.mp4
20.0 MB
01. Basics of Machine Learning/1. What You Will Learn in This Section.mp4
19.8 MB
01. Basics of Machine Learning/3. Important Message About Udemy Reviews.mp4
19.8 MB
03. Data Processing/1. [Hands On] - Data Input-Output - Upload Data.mp4
19.5 MB
04. Classification/13. [Hands On] - Decision Tree - Multi Class Decision Forest IRIS Data.mp4
19.5 MB
08. Clustering/3. [Hands On] - Cluster Analysis Experiment 2 - Score and Evaluate.mp4
19.3 MB
09. Data Processing - Solving Data Processing Challenges/5. [Hands On] - Outliers Treatment - Clip Values.mp4
18.5 MB
11. Recommendation System/6. Understanding the Matchbox Recommendation Results.mp4
18.3 MB
07. Regression Analysis/10. [Hands On] - Decision Tree - Experiment Boosted Decision Tree.mp4
18.1 MB
06. Deploy Webservice/3. [Hands On] - Use the Web Service - Example of Excel.mp4
17.4 MB
09. Data Processing - Solving Data Processing Challenges/7. [Hands On] - Clean Missing Data with MICE.mp4
16.7 MB
09. Data Processing - Solving Data Processing Challenges/9. [Hands On] - SMOTE.mp4
16.3 MB
11. Recommendation System/2. Data Preparation using Recommender Split.mp4
15.6 MB
11. Recommendation System/3. What is Matchbox Recommender and Train Matchbox Recommender.mp4
15.3 MB
04. Classification/7. Decision Tree - What is Decision Tree.mp4
15.0 MB
09. Data Processing - Solving Data Processing Challenges/8. SMOTE - Create New Synthetic Observations.mp4
14.9 MB
07. Regression Analysis/1. What is Linear Regression.mp4
14.7 MB
04. Classification/15. [Hands On] - SVM - Adult Census Income Prediction.mp4
14.5 MB
04. Classification/5. Logistic Regression - Model Selection and Impact Analysis.mp4
14.4 MB
01. Basics of Machine Learning/6. Understanding various aspects of data - Type, Variables, Category.mp4
14.3 MB
02. Getting Started with Azure ML/1. What You Will Learn in This Section.mp4
14.0 MB
01. Basics of Machine Learning/7. Common Machine Learning Terms - Probability, Mean, Mode, Median, Range.mp4
14.0 MB
02. Getting Started with Azure ML/5. Azure ML Experiment Workflow.mp4
13.9 MB
10. Feature Selection - Select a subset of Variables or features with highest impact/6. [Hands On] - Comparison Experiment for Correlation Coefficients.mp4
13.8 MB
03. Data Processing/3. [Hands On] - Data Input-Output - Import Data.mp4
13.8 MB
09. Data Processing - Solving Data Processing Challenges/6. Clean Missing Data with MICE.mp4
13.7 MB
04. Classification/8. Decision Tree - Ensemble Learning - Bagging and Boosting.mp4
13.5 MB
07. Regression Analysis/2. Regression Analysis - Common Metrics.mp4
13.2 MB
07. Regression Analysis/8. Decision Tree - What is Regression Tree.mp4
12.8 MB
02. Getting Started with Azure ML/4. Azure ML Studio Overview and walk-through.mp4
12.8 MB
04. Classification/9. Decision Tree - Parameters - Two Class Boosted Decision Tree.mp4
12.7 MB
09. Data Processing - Solving Data Processing Challenges/2. How to Summarize Data.mp4
12.3 MB
09. Data Processing - Solving Data Processing Challenges/4. Outliers Treatment - Clip Values.mp4
12.1 MB
04. Classification/1. Logistic Regression - What is Logistic Regression.mp4
12.0 MB
02. Getting Started with Azure ML/6. Azure ML Cheat Sheet for Model Selection.mp4
11.8 MB
11. Recommendation System/4. How to Score the Matchbox Recommender.mp4
11.5 MB
07. Regression Analysis/7. [Hands On] - Experiment Online Gradient.mp4
11.4 MB
09. Data Processing - Solving Data Processing Challenges/12. PCA - What is PCA and Curse of Dimensionality.mp4
11.3 MB
09. Data Processing - Solving Data Processing Challenges/14. Join Data - Join Multiple Datasets based on common keys.mp4
11.0 MB
07. Regression Analysis/4. [Hands On] - Linear Regression - R Squared.mp4
10.8 MB
06. Deploy Webservice/2. [Hands On] - Deploy Machine Learning Model As a Web Service.vtt
9.6 MB
06. Deploy Webservice/2. [Hands On] - Deploy Machine Learning Model As a Web Service.mp4
9.6 MB
10. Feature Selection - Select a subset of Variables or features with highest impact/3. Chi Square Test of Independence.mp4
8.7 MB
09. Data Processing - Solving Data Processing Challenges/3. [Hands On] - Summarize Data - Experiment.mp4
8.5 MB
10. Feature Selection - Select a subset of Variables or features with highest impact/1. Feature Selection - Section Introduction.mp4
8.1 MB
09. Data Processing - Solving Data Processing Challenges/13. [Hands On] - Principal Component Analysis.mp4
7.8 MB
04. Classification/14. SVM - What is Support Vector Machine.mp4
7.5 MB
07. Regression Analysis/6. Linear Regression Online Gradient Descent.mp4
7.0 MB
10. Feature Selection - Select a subset of Variables or features with highest impact/4. Kendall Correlation Coefficient.mp4
7.0 MB
10. Feature Selection - Select a subset of Variables or features with highest impact/7. [Hands On] - Filter Based Selection - AzureML Experiment.mp4
6.7 MB
10. Feature Selection - Select a subset of Variables or features with highest impact/5. Spearman's Rank Correlation.mp4
6.7 MB
09. Data Processing - Solving Data Processing Challenges/11. [Hands On] - Data Normalization.mp4
6.2 MB
04. Classification/11. Decision Forest - Parameters Explained.mp4
6.1 MB
09. Data Processing - Solving Data Processing Challenges/15. [Hands On] - Join Data - Experiment.mp4
5.8 MB
06. Deploy Webservice/1. Azure ML Webservice - Prepare the experiment for webservice.mp4
5.8 MB
02. Getting Started with Azure ML/3. Creating a Free Azure ML Account.mp4
5.7 MB
09. Data Processing - Solving Data Processing Challenges/1. Section Introduction.mp4
5.7 MB
09. Data Processing - Solving Data Processing Challenges/10. Data Normalization - Scale and Reduce.mp4
5.6 MB
04. Classification/10.1 Bank Telemarketing.csv.csv
4.9 MB
07. Regression Analysis/9. Decision Tree - What is Boosted Decision Tree Regression.mp4
4.5 MB
01. Basics of Machine Learning/2.11 Section 04 - Classification - 002 - Decision Tree.pdf.pdf
3.6 MB
01. Basics of Machine Learning/2.12 Section 11 - Recommendation System.pdf.pdf
3.2 MB
01. Basics of Machine Learning/2.9 Section 10 - Feature Selection.pdf.pdf
3.1 MB
01. Basics of Machine Learning/2.10 Section 09 - Data Processing.pdf.pdf
3.0 MB
01. Basics of Machine Learning/2.8 Section 07 - Regression.pdf.pdf
2.9 MB
01. Basics of Machine Learning/2.4 Section 02 - Getting Started with AzureML.pdf.pdf
2.8 MB
02. Getting Started with Azure ML/6.2 ml_studio_overview_v1.1.pdf.pdf
2.4 MB
01. Basics of Machine Learning/2.13 Section - Text Analytics.pdf.pdf
2.1 MB
01. Basics of Machine Learning/2.1 Section 01 - Basics of Machine Learning.pdf.pdf
1.9 MB
01. Basics of Machine Learning/2.6 Section 08 - Clustering.pdf.pdf
1.6 MB
01. Basics of Machine Learning/2.3 Section 04 - Classification - 001 - Logistic Regression.pdf.pdf
1.5 MB
01. Basics of Machine Learning/2.7 Section 05 - Tune Hyperparameter.pdf.pdf
1.2 MB
01. Basics of Machine Learning/2.5 Section 04 - Classification - 003 - SVM.pdf.pdf
1.2 MB
01. Basics of Machine Learning/2.14 Section 03 - Data Pre-processing.pdf.pdf
1.1 MB
01. Basics of Machine Learning/2.2 Section 06 - Deploy Webservice.pdf.pdf
719.3 kB
02. Getting Started with Azure ML/6.1 microsoft-machine-learning-algorithm-cheat-sheet-v6.pdf.pdf
413.8 kB
13. Thank You and Bonus Lecture/1.1 Links for datasets.pdf.pdf
267.7 kB
FreeCoursesOnline.Me.html
110.9 kB
FTUForum.com.html
102.8 kB
10. Feature Selection - Select a subset of Variables or features with highest impact/9.1 Wine-Low-Medium-High.csv.csv
97.6 kB
03. Data Processing/5.1 Wine Quality Dataset.csv.csv
85.7 kB
04. Classification/6.1 winequality-red.csv.csv
85.7 kB
12. Text Analytics and Natural Language Processing/5.1 two-class complaints modified.txt.txt
48.5 kB
04. Classification/2.1 Loan Approval Prediction.csv.csv
38.0 kB
09. Data Processing - Solving Data Processing Challenges/7.1 MICE Loan Dataset.csv.csv
38.0 kB
Discuss.FTUForum.com.html
32.7 kB
04. Classification/4.1 004 - Logistic Regression - Understanding the results.xlsx.xlsx
24.5 kB
04. Classification/2. [Hands On] -Logistic Regression - Build Two-Class Loan Approval Prediction Model.vtt
20.2 kB
03. Data Processing/5. [Hands On] - Apply SQL Transformation, Clean Missing Data, Edit Metadata.vtt
16.6 kB
11. Recommendation System/1. What is a Recommendation System.vtt
14.9 kB
03. Data Processing/6. [Hands On] - Sample and Split Data - Partition or Sample, Train and Test Data.vtt
14.9 kB
12. Text Analytics and Natural Language Processing/2. Text Pre-Processing.vtt
13.5 kB
12. Text Analytics and Natural Language Processing/4. Feature Hashing.vtt
13.0 kB
04. Classification/12. [Hands On] - Two Class Decision Forest - Adult Census Income Prediction.vtt
12.8 kB
08. Clustering/2. [Hands On] - Cluster Analysis Experiment 1.vtt
12.2 kB
04. Classification/4. Understanding the Confusion Matrix, AUC, Accuracy, Precision, Recall and F1Score.vtt
12.1 kB
11. Recommendation System/5. [Hands On] - Restaurant Recommendation Experiment.vtt
11.6 kB
04. Classification/3. Logistic Regression - Understand Parameters and Their Impact.vtt
11.5 kB
03. Data Processing/4. [Hands On] -Data Transform - Add RowsColumns, Remove Duplicates, Select Columns.vtt
10.6 kB
08. Clustering/1. What is Cluster Analysis.vtt
10.0 kB
01. Basics of Machine Learning/5. What is Machine Learning.vtt
10.0 kB
07. Regression Analysis/3. [Hands On] - Linear Regression model using OLS.vtt
9.9 kB
12. Text Analytics and Natural Language Processing/5. [Hands On] - Classify Customer Complaints using Text Analytics.vtt
9.8 kB
01. Basics of Machine Learning/4. Why Machine Learning is the Future.vtt
9.4 kB
01. Basics of Machine Learning/8. Types of Machine Learning Models - Classification, Regression, Clustering etc.vtt
9.4 kB
07. Regression Analysis/5. Gradient Descent.vtt
9.3 kB
04. Classification/10. [Hands On] Two-Class Boosted Decision Tree - Build Bank Telemarketing Prediction.vtt
9.2 kB
05. Hyperparameter Tuning/1. [Hands On] - Tune Hyperparameter for Best Parameter Selection.vtt
8.9 kB
03. Data Processing/2. [Hands On] - Data Input-Output - Convert and Unpack.vtt
8.3 kB
12. Text Analytics and Natural Language Processing/3. Bag Of Words and N-Gram Models for Text features.vtt
7.7 kB
04. Classification/6. [Hands On] Logistic Regression - Build Multi-Class Wine Quality Prediction Model.vtt
7.7 kB
01. Basics of Machine Learning/7. Common Machine Learning Terms - Probability, Mean, Mode, Median, Range.vtt
7.6 kB
12. Text Analytics and Natural Language Processing/1. What is Text Analytics or Natural Language Processing.vtt
7.6 kB
11. Recommendation System/2. Data Preparation using Recommender Split.vtt
7.5 kB
09. Data Processing - Solving Data Processing Challenges/8. SMOTE - Create New Synthetic Observations.vtt
7.4 kB
11. Recommendation System/3. What is Matchbox Recommender and Train Matchbox Recommender.vtt
7.4 kB
11. Recommendation System/6. Understanding the Matchbox Recommendation Results.vtt
7.4 kB
03. Data Processing/1. [Hands On] - Data Input-Output - Upload Data.vtt
7.3 kB
01. Basics of Machine Learning/6. Understanding various aspects of data - Type, Variables, Category.vtt
7.3 kB
10. Feature Selection - Select a subset of Variables or features with highest impact/6. [Hands On] - Comparison Experiment for Correlation Coefficients.vtt
7.2 kB
04. Classification/13. [Hands On] - Decision Tree - Multi Class Decision Forest IRIS Data.vtt
7.2 kB
04. Classification/7. Decision Tree - What is Decision Tree.vtt
7.2 kB
02. Getting Started with Azure ML/5. Azure ML Experiment Workflow.vtt
6.9 kB
08. Clustering/3. [Hands On] - Cluster Analysis Experiment 2 - Score and Evaluate.vtt
6.8 kB
10. Feature Selection - Select a subset of Variables or features with highest impact/2. Pearson Correlation Coefficient.vtt
6.7 kB
04. Classification/8. Decision Tree - Ensemble Learning - Bagging and Boosting.vtt
6.7 kB
09. Data Processing - Solving Data Processing Challenges/5. [Hands On] - Outliers Treatment - Clip Values.vtt
6.6 kB
10. Feature Selection - Select a subset of Variables or features with highest impact/1. Feature Selection - Section Introduction.vtt
6.4 kB
09. Data Processing - Solving Data Processing Challenges/9.1 LoanSMOTE.csv.csv
6.3 kB
09. Data Processing - Solving Data Processing Challenges/7. [Hands On] - Clean Missing Data with MICE.vtt
6.3 kB
09. Data Processing - Solving Data Processing Challenges/6. Clean Missing Data with MICE.vtt
6.2 kB
06. Deploy Webservice/3. [Hands On] - Use the Web Service - Example of Excel.vtt
6.2 kB
09. Data Processing - Solving Data Processing Challenges/4. Outliers Treatment - Clip Values.vtt
6.0 kB
02. Getting Started with Azure ML/6. Azure ML Cheat Sheet for Model Selection.vtt
6.0 kB
04. Classification/1. Logistic Regression - What is Logistic Regression.vtt
6.0 kB
10. Feature Selection - Select a subset of Variables or features with highest impact/9. [Hands On] - Fisher Based LDA - Experiment.vtt
6.0 kB
03. Data Processing/3. [Hands On] - Data Input-Output - Import Data.vtt
5.9 kB
07. Regression Analysis/10. [Hands On] - Decision Tree - Experiment Boosted Decision Tree.vtt
5.8 kB
09. Data Processing - Solving Data Processing Challenges/2. How to Summarize Data.vtt
5.7 kB
07. Regression Analysis/2. Regression Analysis - Common Metrics.vtt
5.7 kB
09. Data Processing - Solving Data Processing Challenges/12. PCA - What is PCA and Curse of Dimensionality.vtt
5.7 kB
07. Regression Analysis/8. Decision Tree - What is Regression Tree.vtt
5.6 kB
09. Data Processing - Solving Data Processing Challenges/14. Join Data - Join Multiple Datasets based on common keys.vtt
5.6 kB
10. Feature Selection - Select a subset of Variables or features with highest impact/3. Chi Square Test of Independence.vtt
5.6 kB
04. Classification/9. Decision Tree - Parameters - Two Class Boosted Decision Tree.vtt
5.5 kB
07. Regression Analysis/1. What is Linear Regression.vtt
5.4 kB
11. Recommendation System/4. How to Score the Matchbox Recommender.vtt
5.3 kB
04. Classification/5. Logistic Regression - Model Selection and Impact Analysis.vtt
5.1 kB
09. Data Processing - Solving Data Processing Challenges/9. [Hands On] - SMOTE.vtt
5.1 kB
10. Feature Selection - Select a subset of Variables or features with highest impact/8. Fisher Based LDA - Intuition.vtt
5.1 kB
04. Classification/15. [Hands On] - SVM - Adult Census Income Prediction.vtt
5.1 kB
13. Thank You and Bonus Lecture/1. Way Forward.vtt
5.1 kB
02. Getting Started with Azure ML/4. Azure ML Studio Overview and walk-through.vtt
4.7 kB
10. Feature Selection - Select a subset of Variables or features with highest impact/4. Kendall Correlation Coefficient.vtt
4.1 kB
07. Regression Analysis/7. [Hands On] - Experiment Online Gradient.vtt
4.0 kB
07. Regression Analysis/4. [Hands On] - Linear Regression - R Squared.vtt
3.9 kB
01. Basics of Machine Learning/3. Important Message About Udemy Reviews.vtt
3.9 kB
10. Feature Selection - Select a subset of Variables or features with highest impact/5. Spearman's Rank Correlation.vtt
3.7 kB
04. Classification/14. SVM - What is Support Vector Machine.vtt
3.6 kB
10. Feature Selection - Select a subset of Variables or features with highest impact/7. [Hands On] - Filter Based Selection - AzureML Experiment.vtt
3.6 kB
02. Getting Started with Azure ML/2. What is Azure ML and high level architecture..vtt
3.6 kB
04. Classification/11. Decision Forest - Parameters Explained.vtt
3.5 kB
09. Data Processing - Solving Data Processing Challenges/13. [Hands On] - Principal Component Analysis.vtt
3.3 kB
09. Data Processing - Solving Data Processing Challenges/3. [Hands On] - Summarize Data - Experiment.vtt
2.9 kB
09. Data Processing - Solving Data Processing Challenges/1. Section Introduction.vtt
2.8 kB
09. Data Processing - Solving Data Processing Challenges/10. Data Normalization - Scale and Reduce.vtt
2.7 kB
09. Data Processing - Solving Data Processing Challenges/15. [Hands On] - Join Data - Experiment.vtt
2.5 kB
01. Basics of Machine Learning/1. What You Will Learn in This Section.vtt
2.4 kB
06. Deploy Webservice/1. Azure ML Webservice - Prepare the experiment for webservice.vtt
2.3 kB
02. Getting Started with Azure ML/3. Creating a Free Azure ML Account.vtt
2.2 kB
09. Data Processing - Solving Data Processing Challenges/11. [Hands On] - Data Normalization.vtt
2.2 kB
02. Getting Started with Azure ML/1. What You Will Learn in This Section.vtt
2.2 kB
07. Regression Analysis/6. Linear Regression Online Gradient Descent.vtt
2.0 kB
03. Data Processing/1.1 Employee Dataset - Full.csv.csv
1.9 kB
03. Data Processing/4.5 Employee Dataset - TSV.txt.txt
1.9 kB
07. Regression Analysis/9. Decision Tree - What is Boosted Decision Tree Regression.vtt
1.8 kB
03. Data Processing/4.1 Employee Dataset - AC1.csv.csv
1.7 kB
13. Thank You and Bonus Lecture/2. Bonus Lecture.html
1.4 kB
03. Data Processing/4.2 Employee Dataset - AR2.csv.csv
1.4 kB
08. Clustering/2.1 Callcenter Data.csv.csv
831 Bytes
03. Data Processing/2.1 Employee Dataset - Full.zip.zip
773 Bytes
03. Data Processing/4.4 Employee Dataset - AR1.csv.csv
672 Bytes
[TGx]Downloaded from torrentgalaxy.org.txt
524 Bytes
01. Basics of Machine Learning/2. The course slides for all sections.html
336 Bytes
03. Data Processing/4.3 Employee Dataset - AC2.csv.csv
260 Bytes
How you can help Team-FTU.txt
235 Bytes
03. Data Processing/5.2 SQL Statement - Wine.txt.txt
141 Bytes
06. Deploy Webservice/4. AzureML Web Service.html
137 Bytes
07. Regression Analysis/11. Regression Analysis.html
137 Bytes
08. Clustering/4. Clustering or Cluster Analysis.html
137 Bytes
11. Recommendation System/7. Recommendation System.html
137 Bytes
01. Basics of Machine Learning/9. Basics of Machine Learning.html
136 Bytes
02. Getting Started with Azure ML/7. Getting Started with AzureML.html
136 Bytes
03. Data Processing/7. Data Processing.html
136 Bytes
04. Classification/16. Classification Quiz.html
136 Bytes
05. Hyperparameter Tuning/2. Hyperparameter Tuning.html
136 Bytes
09. Data Processing - Solving Data Processing Challenges/15.1 EmpSalaryJC.csv.csv
110 Bytes
09. Data Processing - Solving Data Processing Challenges/15.2 EmpDeptJC.csv.csv
108 Bytes
Torrent Downloaded From GloDls.to.txt
84 Bytes
03. Data Processing/3.1 Adult Dataset URL.txt.txt
74 Bytes
04. Classification/13.1 IRIS Dataset Link.txt.txt
74 Bytes
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