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  • U: Anonymous
  • D: 2019-06-03 17:45:11
  • C: APPS
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ReScene version pyReScene Auto 0.7 ELOHiM File size CRC
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22,944
Stored files
1,518 09B54832
975 125FC43C
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01 Introduction\001 Welcome to the course-en.srt 3,423 28811112
01 Introduction\001 Welcome to the course.mp4 17,059,091 C3D207D8
01 Introduction\002 Course contents-en.srt 9,259 F9733A4B
01 Introduction\002 Course contents.mp4 50,172,680 073494D1
02 Basics of Statistics\003 Types of Data-en.srt 5,004 9FE62C06
02 Basics of Statistics\003 Types of Data.mp4 27,116,949 F925A7F8
02 Basics of Statistics\004 Types of Statistics-en.srt 3,077 249D895F
02 Basics of Statistics\004 Types of Statistics.mp4 13,875,539 385A657F
02 Basics of Statistics\005 Describing data Graphically-en.srt 13,164 ED0744D3
02 Basics of Statistics\005 Describing data Graphically.mp4 86,195,573 08661E19
02 Basics of Statistics\006 Measures of Centers-en.srt 7,351 60B5EC06
02 Basics of Statistics\006 Measures of Centers.mp4 47,886,199 7854CDF1
02 Basics of Statistics\007 Practice Exercise 1.html 1,217 E6556B77
02 Basics of Statistics\008 Measures of Dispersion-en.srt 5,479 8E81E90E
02 Basics of Statistics\008 Measures of Dispersion.mp4 29,759,276 01022942
02 Basics of Statistics\009 Practice Exercise 2.html 1,160 57ABAE38
03 Setting up Python and Jupyter Notebook\010 Installing Python and Anaconda-en.srt 2,671 6D0D75AF
03 Setting up Python and Jupyter Notebook\010 Installing Python and Anaconda.mp4 19,517,370 272F4041
03 Setting up Python and Jupyter Notebook\011 Opening Jupyter Notebook-en.srt 9,361 2CA8DFB7
03 Setting up Python and Jupyter Notebook\011 Opening Jupyter Notebook.mp4 76,614,689 9E5D3631
03 Setting up Python and Jupyter Notebook\012 Introduction to Jupyter-en.srt 12,650 B9A3D9A4
03 Setting up Python and Jupyter Notebook\012 Introduction to Jupyter.mp4 53,792,544 684C56BF
03 Setting up Python and Jupyter Notebook\013 Arithmetic operators in Python Python Basics-en.srt 4,087 AFC63103
03 Setting up Python and Jupyter Notebook\013 Arithmetic operators in Python Python Basics.mp4 16,696,250 65FCA0C8
03 Setting up Python and Jupyter Notebook\014 Strings in Python Python Basics-en.srt 16,780 DE1813E2
03 Setting up Python and Jupyter Notebook\014 Strings in Python Python Basics.mp4 84,542,570 D525B7CD
03 Setting up Python and Jupyter Notebook\015 Lists Tuples and Directories Python Basics-en.srt 17,390 89A81674
03 Setting up Python and Jupyter Notebook\015 Lists Tuples and Directories Python Basics.mp4 77,250,826 599D8FF0
03 Setting up Python and Jupyter Notebook\016 Working with Numpy Library of Python-en.srt 10,717 416CF747
03 Setting up Python and Jupyter Notebook\016 Working with Numpy Library of Python.mp4 56,750,905 B642CB6D
03 Setting up Python and Jupyter Notebook\017 Working with Pandas Library of Python-en.srt 8,384 95E0DEB3
03 Setting up Python and Jupyter Notebook\017 Working with Pandas Library of Python.mp4 59,201,472 2ED39621
03 Setting up Python and Jupyter Notebook\018 Working with Seaborn Library of Python-en.srt 7,788 8A18C213
03 Setting up Python and Jupyter Notebook\018 Working with Seaborn Library of Python.mp4 51,246,979 8CF2A67E
04 Introduction to Machine Learning\019 Introduction to Machine Learning-en.srt 18,897 E47931C0
04 Introduction to Machine Learning\019 Introduction to Machine Learning.mp4 129,907,859 66057D65
04 Introduction to Machine Learning\020 Building a Machine Learning Model-en.srt 9,921 6942C97D
04 Introduction to Machine Learning\020 Building a Machine Learning Model.mp4 47,459,838 979FF092
05 Data Preprocessing\021 Gathering Business Knowledge-en.srt 3,993 511363F7
05 Data Preprocessing\021 Gathering Business Knowledge.mp4 26,333,912 2FC1C19C
05 Data Preprocessing\022 Data Exploration-en.srt 3,686 76D4E3E1
05 Data Preprocessing\022 Data Exploration.mp4 24,549,674 7092BC23
05 Data Preprocessing\023 The Dataset and the Data Dictionary-en.srt 7,970 2F6A9888
05 Data Preprocessing\023 The Dataset and the Data Dictionary.mp4 82,397,440 6679752B
05 Data Preprocessing\024 Importing Data in Python-en.srt 5,719 ABD577EB
05 Data Preprocessing\024 Importing Data in Python.mp4 34,034,714 9AA5AB02
05 Data Preprocessing\025 Project exercise 1.html 1,290 E94F2C89
05 Data Preprocessing\026 Univariate analysis and EDD-en.srt 3,521 DA0846B5
05 Data Preprocessing\026 Univariate analysis and EDD.mp4 28,612,043 E5999E88
05 Data Preprocessing\027 EDD in Python-en.srt 10,572 247A164C
05 Data Preprocessing\027 EDD in Python.mp4 78,712,648 4BFC2E35
05 Data Preprocessing\028 Project Exercise 2.html 1,036 580900C0
05 Data Preprocessing\029 Outlier Treatment-en.srt 4,562 B04E1560
05 Data Preprocessing\029 Outlier Treatment.mp4 29,127,496 1248DE66
05 Data Preprocessing\030 Outlier Treatment in Python-en.srt 13,312 6ADC2CB7
05 Data Preprocessing\030 Outlier Treatment in Python.mp4 90,776,801 1F4398AB
05 Data Preprocessing\031 Project Exercise 3.html 1,092 E073BA96
05 Data Preprocessing\032 Missing Value Imputation-en.srt 4,175 5DC81B17
05 Data Preprocessing\032 Missing Value Imputation.mp4 28,893,680 869EDB47
05 Data Preprocessing\033 Missing Value Imputation in Python-en.srt 4,161 9CEE1B4D
05 Data Preprocessing\033 Missing Value Imputation in Python.mp4 29,980,638 79D77B20
05 Data Preprocessing\034 Project Exercise 4.html 1,097 5A183A4F
05 Data Preprocessing\035 Seasonality in Data-en.srt 3,867 00B14874
05 Data Preprocessing\035 Seasonality in Data.mp4 21,890,113 3462784F
05 Data Preprocessing\036 Bi-variate analysis and Variable transformation-en.srt 18,724 1830034A
05 Data Preprocessing\036 Bi-variate analysis and Variable transformation.mp4 119,257,644 D876AD88
05 Data Preprocessing\037 Variable transformation and deletion in Python-en.srt 7,678 732630E7
05 Data Preprocessing\037 Variable transformation and deletion in Python.mp4 55,990,029 471FC77A
05 Data Preprocessing\038 Project Exercise 5.html 1,144 E408D9B9
05 Data Preprocessing\039 Non-usable variables-en.srt 5,524 792F3BF0
05 Data Preprocessing\039 Non-usable variables.mp4 25,101,820 25C2F25E
05 Data Preprocessing\040 Dummy variable creation Handling qualitative data-en.srt 4,981 E4E94A4C
05 Data Preprocessing\040 Dummy variable creation Handling qualitative data.mp4 42,593,806 17A8B384
05 Data Preprocessing\041 Dummy variable creation in Python-en.srt 5,632 7961E5E7
05 Data Preprocessing\041 Dummy variable creation in Python.mp4 35,541,213 164B69F6
05 Data Preprocessing\042 Project Exercise 6.html 1,061 D67AE3E7
05 Data Preprocessing\043 Correlation Analysis-en.srt 11,306 370846E2
05 Data Preprocessing\043 Correlation Analysis.mp4 85,249,045 D43BC79D
05 Data Preprocessing\044 Correlation Analysis in Python-en.srt 6,712 8A40C235
05 Data Preprocessing\044 Correlation Analysis in Python.mp4 71,322,952 8351540D
05 Data Preprocessing\045 Project Exercise 7.html 1,147 A1F516C2
06 Linear Regression\046 The Problem Statement-en.srt 1,654 39528CA0
06 Linear Regression\046 The Problem Statement.mp4 11,199,023 11912308
06 Linear Regression\047 Basic Equations and Ordinary Least Squares (OLS) method-en.srt 10,123 830A54AD
06 Linear Regression\047 Basic Equations and Ordinary Least Squares (OLS) method.mp4 52,704,165 BAF9F489
06 Linear Regression\048 Assessing accuracy of predicted coefficients-en.srt 16,211 12861A4C
06 Linear Regression\048 Assessing accuracy of predicted coefficients.mp4 109,484,933 5ECC1B2A
06 Linear Regression\049 Assessing Model Accuracy RSE and R squared-en.srt 8,208 5143D9B4
06 Linear Regression\049 Assessing Model Accuracy RSE and R squared.mp4 52,122,148 9AE4DA23
06 Linear Regression\050 Simple Linear Regression in Python-en.srt 11,564 1D859A4B
06 Linear Regression\050 Simple Linear Regression in Python.mp4 82,450,465 C50E9AD2
06 Linear Regression\051 Project Exercise 8.html 1,181 AA940769
06 Linear Regression\052 Multiple Linear Regression-en.srt 5,865 D38240AB
06 Linear Regression\052 Multiple Linear Regression.mp4 40,786,619 73C6023D
06 Linear Regression\053 The F - statistic-en.srt 9,243 A783E51A
06 Linear Regression\053 The F - statistic.mp4 67,237,133 1A2E171E
06 Linear Regression\054 Interpreting results of Categorical variables-en.srt 5,420 1127E962
06 Linear Regression\054 Interpreting results of Categorical variables.mp4 28,448,043 911C263B
06 Linear Regression\055 Multiple Linear Regression in Python-en.srt 12,649 7404DC66
06 Linear Regression\055 Multiple Linear Regression in Python.mp4 92,415,618 62DC25D0
06 Linear Regression\056 Project Exercise 9.html 1,186 54A41896
06 Linear Regression\057 Test-train split-en.srt 10,334 3C77AD28
06 Linear Regression\057 Test-train split.mp4 51,517,653 A6CB4D7E
06 Linear Regression\058 Bias Variance trade-off-en.srt 6,560 E6F92FCC
06 Linear Regression\058 Bias Variance trade-off.mp4 31,031,747 0201D49B
06 Linear Regression\059 Test train split in Python-en.srt 8,285 2CB5C1A6
06 Linear Regression\059 Test train split in Python.mp4 60,577,837 244D0503
06 Linear Regression\060 Linear models other than OLS-en.srt 4,463 FB9158EC
06 Linear Regression\060 Linear models other than OLS.mp4 20,110,876 7A34EC48
06 Linear Regression\061 Subset selection techniques-en.srt 13,086 5B831E5D
06 Linear Regression\061 Subset selection techniques.mp4 91,372,583 F0DA5106
06 Linear Regression\062 Shrinkage methods Ridge and Lasso-en.srt 8,241 4484D2F7
06 Linear Regression\062 Shrinkage methods Ridge and Lasso.mp4 40,519,318 923176F4
06 Linear Regression\063 Ridge regression and Lasso in Python-en.srt 19,508 8BD90E73
06 Linear Regression\063 Ridge regression and Lasso in Python.mp4 164,234,153 503D5C13
06 Linear Regression\064 Project Exercise 10.html 1,284 BC5AA125
06 Linear Regression\065 Final Project Exercise.html 1,164 7867D29D
06 Linear Regression\066 Course Conclusion.html 2,530 1E6BAC8C
Resources\002 00-Introduction-01.pdf 810,489 7C670FAE
Resources\003 01-01-Lecture-TypesOfData.pdf 182,006 1E63D49C
Resources\004 01-02-Lecture-TypesOfStatistics.pdf 175,856 8341E3EF
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Resources\006 01-04-Lecture-Centers.pdf 320,491 E173E8E3
Resources\007 Exercise-1.pdf 567,127 7DCABC53
Resources\008 01-05-Lecture-Dispersion.pdf 215,605 50D55AC2
Resources\009 Exercise-2.pdf 481,211 78C4CF0C
Resources\017 Customer.csv 65,561 29620111
Resources\019 Lecture-machineLearning.pdf 1,015,404 3FE43B49
Resources\020 Lecture-machineLearning.pdf 1,015,404 3FE43B49
Resources\021 03-01-PDE-Business-knowledge.pdf 157,637 0619760B
Resources\022 03-02-PDE-Data-exploration.pdf 330,663 72941731
Resources\023 03-03-PDE-Raw-Data-Analysis-Uni.pdf 339,946 C7BCB5FA
Resources\023 House-Price.csv 54,773 8F652E86
Resources\024 House-Price.csv 54,773 8F652E86
Resources\025 Movie-collection-train.csv 44,354 9D45CF11
Resources\026 03-04-PDE-Univariate-Analysis-Uni.pdf 341,387 59F94153
Resources\029 04-06-PDE-Outlier-Treatment.pdf 363,664 FB6F54C9
Resources\032 04-05-PDE-Missing-value.pdf 323,254 3818727F
Resources\035 04-07-PDE-Seasonality.pdf 372,828 A7E4C879
Resources\036 04-07-Variable-Transformation.pdf 432,951 350931BD
Resources\039 04-08-PDE-Non-Usable-var.pdf 141,669 3A217E4C
Resources\040 04-11-Dummy-Var.pdf 166,882 4B446EF9
Resources\043 04-10-Correlation.pdf 263,080 82520E29
Resources\046 05-01-Intro.pdf 245,064 06615463
Resources\047 05-02-Simple-lin-reg.pdf 291,608 4AC80EF6
Resources\048 05-03-Simple-lin-reg-Accuracy.pdf 340,705 1A6C3B39
Resources\049 05-03-Simple-lin-reg-Accuracy.pdf 340,705 1A6C3B39
Resources\052 05-04-Multiple-lin-reg.pdf 225,066 8014A4C8
Resources\053 05-05-F-stat.pdf 336,362 85D338C7
Resources\054 05-06-Cat-var.pdf 159,225 0E35BD83
Resources\057 05-12-Test-Train.pdf 244,514 557F924F
Resources\058 05-13-Bias-Var-tradeoff.pdf 207,235 D8AAFBE6
Resources\060 05-09-Other-lin-model.pdf 160,266 7D7F5CED
Resources\061 05-10-Subset-Selection.pdf 203,287 8D6D1CCB
Resources\062 05-11-Shrinkage-methods.pdf 192,621 15B5BC86
Resources\065 Movie-collection-test.csv 11,997 D4FF14AD
01 Introduction 0 00000000
02 Basics of Statistics 0 00000000
03 Setting up Python and Jupyter Notebook 0 00000000
04 Introduction to Machine Learning 0 00000000
05 Data Preprocessing 0 00000000
06 Linear Regression 0 00000000
Resources 0 00000000
Total size: 2,863,606,242
RAR Recovery
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Execution time: 0.0135 - Memory usage: 0.78MB
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