Udemy - Complete Bootcamp 2021 - Feature selection using Python

seeders: 0 leechers: 0
Added 4 years ago by freecoursewb in Other
Downloaded 4 times.
1337x.to
Udemy - Complete Bootcamp 2021 - Feature selection using Python

Torrent Contents Size: 1.4 GB

Udemy - Complete Bootcamp 2021 - Feature selection using Python
▼ show more 67 files
1. Feature Selection Introduction.mp4
MP4
8.7 MB
1. Feature Selection Introduction.srt
SRT
2.1 KB
1. Filter Method Introduction.mp4
MP4
6.9 MB
1. Filter Method Introduction.srt
SRT
2.3 KB
1. Introduction to Embedded Methods.mp4
MP4
3.4 MB
1. Introduction to Embedded Methods.srt
SRT
1.1 KB
1. Introduction to wrapper methods.mp4
MP4
1.5 MB
1. Introduction to wrapper methods.srt
SRT
614.4 B
1. Introduction.mp4
MP4
9.5 MB
1. Introduction.srt
SRT
2.8 KB
10. Mutual information to select features in a datasets with continuous target.mp4
MP4
41.3 MB
10. Mutual information to select features in a datasets with continuous target.srt
SRT
11.3 KB
10. Project 12 Backward feature elimination implementation.mp4
MP4
25.4 MB
10. Project 12 Backward feature elimination implementation.srt
SRT
2.7 KB
11. Backward feature selection mlxtend.mp4
MP4
8.4 MB
11. Backward feature selection mlxtend.srt
SRT
1.8 KB
11. Project 5 To select features from a dataset using Mutual Information.mp4
MP4
68.5 MB
11. Project 5 To select features from a dataset using Mutual Information.srt
SRT
8.5 KB
12. Mutual Information to select feature from a dataset where target variable discre.mp4
MP4
16.8 MB
12. Mutual Information to select feature from a dataset where target variable discre.srt
SRT
3.1 KB
12. Project 11 Backward feature selection implementation.mp4
MP4
59.2 MB
12. Project 11 Backward feature selection implementation.srt
SRT
6 KB
13. Exhaustive feature selection.mp4
MP4
15.8 MB
13. Exhaustive feature selection.srt
SRT
3.7 KB
13. Project 6 Mutual information implementation on a dataset with discrete target.mp4
MP4
79.3 MB
13. Project 6 Mutual information implementation on a dataset with discrete target.srt
SRT
9.9 KB
14. Chi2 test method to select feature.mp4
MP4
26.9 MB
14. Chi2 test method to select feature.srt
SRT
8.4 KB
14. Project 12 Implementation of Exhaustive feature selection.mp4
MP4
57.3 MB
14. Project 12 Implementation of Exhaustive feature selection.srt
SRT
5.6 KB
15. Project 7 Implementation of chi2.mp4
MP4
43.6 MB
15. Project 7 Implementation of chi2.srt
SRT
5 KB
2. Forward Feature Selection.mp4
MP4
35.5 MB
2. Forward Feature Selection.srt
SRT
7.1 KB
2. Tree based methods.mp4
MP4
6.7 MB
2. Tree based methods.srt
SRT
2.6 KB
2. Variance For Feature Selection.mp4
MP4
22.6 MB
2. Variance For Feature Selection.srt
SRT
5.8 KB
3. Project 1 Variance for Feature selection on data for classification.mp4
MP4
182.8 MB
3. Project 1 Variance for Feature selection on data for classification.srt
SRT
19.1 KB
3. Project 13 Implementation of Embedded Method using Decision Tree Classifier.mp4
MP4
40.4 MB
3. Project 13 Implementation of Embedded Method using Decision Tree Classifier.srt
SRT
4.7 KB
3. Project 8 Implementation of forward feature selection using sklearn.mp4
MP4
58.4 MB
3. Project 8 Implementation of forward feature selection using sklearn.srt
SRT
5.2 KB
4. Project 14 Implementation of Embedded Method using RandomForest Regressor.mp4
MP4
33.6 MB
4. Project 14 Implementation of Embedded Method using RandomForest Regressor.srt
SRT
3.6 KB
4. Project 2 Variance for Feature selection on data for regression.mp4
MP4
117.6 MB
4. Project 2 Variance for Feature selection on data for regression.srt
SRT
11.7 KB
4. Project 9 Implementation of forward feature selection using sklearn.mp4
MP4
29.3 MB
4. Project 9 Implementation of forward feature selection using sklearn.srt
SRT
3.2 KB
5. Forward Feature Selection in mlxtend.mp4
MP4
8.5 MB
5. Forward Feature Selection in mlxtend.srt
SRT
1.8 KB
5. Project 15 Implementation of Embedded Method using Extremely randomized trees.mp4
MP4
34.6 MB
5. Project 15 Implementation of Embedded Method using Extremely randomized trees.srt
SRT
3.5 KB
5. Project 2 Variance for Feature selection on data for regression part 2.mp4
MP4
25.6 MB
5. Project 2 Variance for Feature selection on data for regression part 2.srt
SRT
3.7 KB
6. Feature selection using F-Score.mp4
MP4
40.5 MB
6. Feature selection using F-Score.srt
SRT
12.2 KB
6. Introduction to Regularization Methods for feature selection.mp4
MP4
11.8 MB
6. Introduction to Regularization Methods for feature selection.srt
SRT
4.1 KB
6. Project 10 Implementation of forward feature selection mlxtend.mp4
MP4
51.6 MB
6. Project 10 Implementation of forward feature selection mlxtend.srt
SRT
5 KB
7. Backward Feature Elimination.mp4
MP4
3 MB
7. Backward Feature Elimination.srt
SRT
819.2 B
7. Project 16 Implementation of Lasso Regularization.mp4
MP4
26 MB
7. Project 16 Implementation of Lasso Regularization.srt
SRT
3.4 KB
7. Project 3 Feature selection using F Score.mp4
MP4
68 MB
7. Project 3 Feature selection using F Score.srt
SRT
7.3 KB
8. Backward Feature Elimination sklearn.mp4
MP4
4.3 MB
8. Backward Feature Elimination sklearn.srt
SRT
614.4 B
8. Feature Selection using Anova-F Score.mp4
MP4
22.1 MB
8. Feature Selection using Anova-F Score.srt
SRT
6.2 KB
8. Project 17 Implementation of Logistic Regression with Lasso Regularization.mp4
MP4
52.9 MB
8. Project 17 Implementation of Logistic Regression with Lasso Regularization.srt
SRT
5.7 KB
9. Benefits of Embedded Methods.mp4
MP4
2.9 MB
9. Benefits of Embedded Methods.srt
SRT
819.2 B
9. Project 11 Backward feature elimination implementation sklearn.mp4
MP4
45.7 MB
9. Project 11 Backward feature elimination implementation sklearn.srt
SRT
5.4 KB
9. Project 4 Feature selection using anova F-Score.mp4
MP4
77.4 MB
9. Project 4 Feature selection using anova F-Score.srt
SRT
7.5 KB
Bonus Resources.txt
TXT
307.2 B
Get Bonus Downloads Here.url
URL
204.8 B

Description

Related Torrents

Location

Trackers

Tracker name
udp://tracker.torrent.eu.org:451/announce
udp://tracker.tiny-vps.com:6969/announce
http://tracker.foreverpirates.co:80/announce
udp://tracker.cyberia.is:6969/announce
udp://exodus.desync.com:6969/announce
udp://explodie.org:6969/announce
udp://tracker.opentrackr.org:1337/announce
udp://9.rarbg.to:2780/announce
udp://tracker.internetwarriors.net:1337/announce
udp://ipv4.tracker.harry.lu:80/announce
udp://open.stealth.si:80/announce
udp://9.rarbg.to:2900/announce
udp://9.rarbg.me:2720/announce
udp://opentor.org:2710/announce
udp://tracker.zer0day.to:1337/announce
udp://tracker.leechers-paradise.org:6969/announce
udp://coppersurfer.tk:6969/announce
Torrent hash: