Name [FreeTutorials.Eu] [UDEMY] Feature Selection for Machine Learning - [FTU]

File Type video

Size 397.11MB

UpdateDate 2024-10-27

hash *****338485097FF62F7925C2F6484415B2837C

Hot 2

Files 01 Introduction/001 Introduction-en.srt | 5.48KB 01 Introduction/001 Introduction.mp4 | 4.62MB 01 Introduction/002 Course Curriculum Overview-en.srt | 4.91KB 01 Introduction/002 Course Curriculum Overview.mp4 | 4.05MB 01 Introduction/003 Course requirements-en.srt | 4.43KB 01 Introduction/003 Course requirements.mp4 | 6.42MB 01 Introduction/004 Additional Requirements Nice to have.html | 1.51KB 01 Introduction/005 How to approach this course.html | 2.38KB 01 Introduction/006 Guide to setting up your computer.html | 4.11KB 01 Introduction/007 Installing XGBoost in windows.html | 2.93KB 01 Introduction/008 Feature-selection-presentations.zip | 5.97MB 01 Introduction/008 Presentations covered in this course.html | 994B 01 Introduction/009 Feature-selection-notebooks.zip | 915.13KB 01 Introduction/009 Jupyter notebooks covered in this course.html | 994B 01 Introduction/010 FAQ Data Science and Python programming.html | 1.81KB 02 Feature Selection/011 What is feature selection-en.srt | 7.42KB 02 Feature Selection/011 What is feature selection.mp4 | 7.82MB 02 Feature Selection/012 Feature selection methods Overview-en.srt | 7.30KB 02 Feature Selection/012 Feature selection methods Overview.mp4 | 15.55MB 02 Feature Selection/013 Filter Methods-en.srt | 3.91KB 02 Feature Selection/013 Filter Methods.mp4 | 4.87MB 02 Feature Selection/014 Wrapper methods-en.srt | 6.30KB 02 Feature Selection/014 Wrapper methods.mp4 | 7.30MB 02 Feature Selection/015 Embedded Methods-en.srt | 4.93KB 02 Feature Selection/015 Embedded Methods.mp4 | 9.53MB 03 Filter Methods Basics/016 Constant quasi constant and duplicated features Intro-en.srt | 4.95KB 03 Filter Methods Basics/016 Constant quasi constant and duplicated features Intro.mp4 | 8.87MB 03 Filter Methods Basics/017 Constant features-en.srt | 12.76KB 03 Filter Methods Basics/017 Constant features.mp4 | 14.50MB 03 Filter Methods Basics/018 Quasi-constant features-en.srt | 12.49KB 03 Filter Methods Basics/018 Quasi-constant features.mp4 | 15.38MB 03 Filter Methods Basics/019 Duplicated features-en.srt | 8.64KB 03 Filter Methods Basics/019 Duplicated features.mp4 | 20.70MB 03 Filter Methods Basics/020 Basic methods review.html | 4.61KB 04 Filter methods Correlation/021 Correlation Intro-en.srt | 6.63KB 04 Filter methods Correlation/021 Correlation Intro.mp4 | 13.96MB 04 Filter methods Correlation/022 Correlation-en.srt | 18.68KB 04 Filter methods Correlation/022 Correlation.mp4 | 24.38MB 04 Filter methods Correlation/023 Basic methods plus Correlation pipeline.html | 11.12KB 05 Filter methods Statistical measures/024 Statistical methods Intro-en.srt | 15.46KB 05 Filter methods Statistical measures/024 Statistical methods Intro.mp4 | 16.57MB 05 Filter methods Statistical measures/025 Mutual information-en.srt | 9.97KB 05 Filter methods Statistical measures/025 Mutual information.mp4 | 14.03MB 05 Filter methods Statistical measures/026 Chi-square for categorical variables Fisher score-en.srt | 5.57KB 05 Filter methods Statistical measures/026 Chi-square for categorical variables Fisher score.mp4 | 7.27MB 05 Filter methods Statistical measures/027 Univariate approaches-en.srt | 12.21KB 05 Filter methods Statistical measures/027 Univariate approaches.mp4 | 16.43MB 05 Filter methods Statistical measures/028 Univariate ROC-AUC-en.srt | 8.78KB 05 Filter methods Statistical measures/028 Univariate ROC-AUC.mp4 | 10.87MB 05 Filter methods Statistical measures/029 Basic methods Correlation univariate ROC-AUC pipeline.html | 14.04KB 05 Filter methods Statistical measures/030 BONUS select features by mean encoding KDD 2009.html | 19.21KB 06 Wrapper methods/031 Wrapper methods Intro-en.srt | 8.38KB 06 Wrapper methods/031 Wrapper methods Intro.mp4 | 15.55MB 06 Wrapper methods/032 Step forward feature selection-en.srt | 14.48KB 06 Wrapper methods/032 Step forward feature selection.mp4 | 29.59MB 06 Wrapper methods/033 Step backward feature selection-en.srt | 14.46KB 06 Wrapper methods/033 Step backward feature selection.mp4 | 32.07MB 06 Wrapper methods/034 Exhaustive search-en.srt | 10.26KB 06 Wrapper methods/034 Exhaustive search.mp4 | 18.68MB 07 Embedded methods Lasso regularisation/035 Least-angle-and-1-penalized-regression-A-review-.txt | 68B 07 Embedded methods Lasso regularisation/035 Machine-Learning-Explained-Regularization.txt | 71B 07 Embedded methods Lasso regularisation/035 Regularisation Intro-en.srt | 6.78KB 07 Embedded methods Lasso regularisation/035 Regularisation Intro.mp4 | 7.95MB 07 Embedded methods Lasso regularisation/036 Lasso-en.srt | 10.39KB 07 Embedded methods Lasso regularisation/036 Lasso.mp4 | 13.93MB 07 Embedded methods Lasso regularisation/037 Basic filter methods LASSO pipeline.html | 16.14KB 08 Embedded methods Linear models/038 Regression Coefficients Intro-en.srt | 5.22KB 08 Embedded methods Linear models/038 Regression Coefficients Intro.mp4 | 5.48MB 08 Embedded methods Linear models/039 Selection by Logistic Regression Coefficients-en.srt | 9.54KB 08 Embedded methods Linear models/039 Selection by Logistic Regression Coefficients.mp4 | 20.16MB 08 Embedded methods Linear models/040 Coefficients change with penalty-en.srt | 6.74KB 08 Embedded methods Linear models/040 Coefficients change with penalty.mp4 | 8.49MB 08 Embedded methods Linear models/041 Selection by Linear Regression Coefficients-en.srt | 3.94KB 08 Embedded methods Linear models/041 Selection by Linear Regression Coefficients.mp4 | 5.08MB 08 Embedded methods Linear models/042 Feature selection with linear models review.html | 15.52KB 09 Embedded methods Trees/043 Selecting Features by Tree importance Intro-en.srt | 8.22KB 09 Embedded methods Trees/043 Selecting Features by Tree importance Intro.mp4 | 9.28MB 09 Embedded methods Trees/044 Select by model importance random forests embedded.html | 15.11KB 09 Embedded methods Trees/045 Select by model importance random forests recursively.html | 11.08KB 09 Embedded methods Trees/046 Select by model importance gradient boosted machines.html | 9.64KB 09 Embedded methods Trees/047 Feature selection with decision trees review.html | 15.75KB 10 Reading Resources/048 Additional reading resources.html | 2.57KB 11 Hybrid feature selection methods/049 BONUS Shuffling features.html | 19.98KB 11 Hybrid feature selection methods/050 BONUS Hybrid method Recursive feature elimination.html | 48.79KB 11 Hybrid feature selection methods/051 BONUS Hybrid method Recursive feature addition.html | 51.08KB 12 Final section Next steps/052 Bonus Lecture Discounts on my other courses.html | 1.34KB Discuss.FreeTutorials.Us.html | 165.68KB FreeCoursesOnline.Me.html | 108.30KB FreeTutorials.Eu.html | 102.23KB Presented By SaM.txt | 33B [TGx]Downloaded from torrentgalaxy.org.txt | 524B Torrent Downloaded From GloDls.to.txt | 84B