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  3. Decision Trees

Machine Learning with Python: Decision Trees [Updated: 4/23/2024]

Posted By: IrGens
Date: 23 Apr 2024 18:17:00
Machine Learning with Python: Decision Trees [Updated: 4/23/2024]

Machine Learning with Python: Decision Trees [Updated: 4/23/2024]
.MP4, AVC, 1280x800, 30 fps | English, AAC, 2 Ch | 1h 14m | 186 MB
Instructor: Frederick Nwanganga
Details

Decision Trees, Random Forests & Gradient Boosting In R

Posted By: Sigha
Date: 19 Apr 2024 07:35:33
Decision Trees, Random Forests & Gradient Boosting In R

Decision Trees, Random Forests & Gradient Boosting In R
Last updated 7/2023
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
Language: English (US) | Size: 2.89 GB | Duration: 5h 57m

Predictive models with machine learning wit Rstudio´s ROCR, XGBoost, rparty. Bonus: Neural Networks for Credit Scoring
Details

Machine Learning and AI: Advanced Decision Trees with SPSS

Posted By: IrGens
Date: 7 Feb 2024 18:14:52
Machine Learning and AI: Advanced Decision Trees with SPSS

Machine Learning and AI: Advanced Decision Trees with SPSS
.MP4, AVC, 1280x720, 30 fps | English, AAC, 2 Ch | 1h 23m | 193 MB
Instructor: Keith McCormick
Details

Machine Learning and AI Foundations: Decision Trees with SPSS [Updated: 2/2/2024]

Posted By: IrGens
Date: 5 Feb 2024 23:12:49
Machine Learning and AI Foundations: Decision Trees with SPSS [Updated: 2/2/2024]

Machine Learning and AI Foundations: Decision Trees with SPSS [Updated: 2/2/2024]
.MP4, AVC, 1280x720, 30 fps | English, AAC, 2 Ch | 1h 27m | 198 MB
Instructor: Keith McCormick
Details

Decision Trees, Random Forests, Bagging & XGBoost: R Studio

Posted By: lucky_aut
Date: 10 Jan 2023 18:27:44
Decision Trees, Random Forests, Bagging & XGBoost: R Studio

Decision Trees, Random Forests, Bagging & XGBoost: R Studio
Last updated 2022-11-03
Duration: 05:53:20 | .MP4 1280x720, 30 fps(r) | AAC, 44100 Hz, 2ch | 2.45 GB
Genre: eLearning | Language: English [Auto]

Decision Trees and Ensembling techinques in R studio. Bagging, Random Forest, GBM, AdaBoost & XGBoost in R programming
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Decision Trees, Random Forests, AdaBoost & XGBoost in Python

Posted By: lucky_aut
Date: 10 Jan 2023 18:24:07
Decision Trees, Random Forests, AdaBoost & XGBoost in Python

Decision Trees, Random Forests, AdaBoost & XGBoost in Python
Last updated 2022-11-03
Duration: 07:13:39 | .MP4 1280x720, 30 fps(r) | AAC, 44100 Hz, 2ch | 2.27 GB
Genre: eLearning | Language: English

Decision Trees and Ensembling techniques in Python. How to run Bagging, Random Forest, GBM, AdaBoost & XGBoost in Python
Details

Machine Learning and AI Foundations: Advanced Decision Trees with KNIME

Posted By: lucky_aut
Date: 15 Nov 2022 02:56:48
Machine Learning and AI Foundations: Advanced Decision Trees with KNIME

Machine Learning and AI Foundations: Advanced Decision Trees with KNIME
Duration: 1h 33m | .MP4 1280x720, 30 fps(r) | AAC, 48000 Hz, 2ch | 270 MB
Genre: eLearning | Language: English
Details

Decision Trees, Random Forests: get ready with Python

Posted By: BlackDove
Date: 23 Aug 2022 23:31:52
Decision Trees, Random Forests: get ready with Python

Decision Trees, Random Forests: get ready with Python
Published 08/2022
Genre: eLearning | MP4 | Video: h264, 1280x720 | Audio: AAC, 48.0 KHz
Language: English | Size: 1.32 GB | Duration: 90 lectures • 3h 38m


Learn to make and understand predictions with decision trees and random forests. Includes detailed Python demos.
Details

Decision tree models in Python

Posted By: lucky_aut
Date: 2 Jun 2022 15:25:02
Decision tree models in Python

Decision tree models in Python
Duration: 1h 24m | .MP4 1280x720, 30 fps(r) | AAC, 44100 Hz, 2ch | 464 MB
Genre: eLearning | Language: English

A course about decision trees, random forest, gradient boosting decision trees, XGBoost and extra trees in Python
Details

Machine Learning with Python: Decision Trees

Posted By: lucky_aut
Date: 22 May 2022 17:42:31
Machine Learning with Python: Decision Trees

Machine Learning with Python: Decision Trees
Duration: 1h 13m | .MP4 1280x720, 30 fps(r) | AAC, 48000 Hz, 2ch | 186 MB
Genre: eLearning | Language: English
Details

The Complete Intro to Machine Learning with Python

Posted By: lucky_aut
Date: 21 Oct 2021 05:54:35
The Complete Intro to Machine Learning with Python

The Complete Intro to Machine Learning with Python
Duration: 5h 6m | .MP4 1280x720, 30 fps(r) | AAC, 44100 Hz, 2ch | 2.3 GB
Genre: eLearning | Language: English

Hands-on Machine Learning boot-camp with Python, Numpy, Pandas, Regression, Decision Trees, Neural Networks, and more!
Details

Decision Trees : Beginner to Advanced using Machine learning

Posted By: lucky_aut
Date: 14 Jul 2021 18:25:12
Decision Trees : Beginner to Advanced using Machine learning

Decision Trees : Beginner to Advanced using Machine learning
Duration: 1h 49m | .MP4 1280x720, 30 fps(r) | AAC, 44100 Hz, 2ch | 670 MB
Genre: eLearning | Language: English

Everything you need to know about Random forest and decision trees
Details

Decision Trees, Random Forests & Gradient Boosting in R

Posted By: IrGens
Date: 26 Mar 2021 18:48:54
Decision Trees, Random Forests & Gradient Boosting in R

Decision Trees, Random Forests & Gradient Boosting in R
.MKV, AVC, 1280x720, 30 fps | English, AAC, 2 Ch | 3h 24m | 1.78 GB
Instructor: Carlos Martinez
Details

Machine Learning : Random Forest with Python from Scratch©

Posted By: ELK1nG
Date: 4 Mar 2021 13:22:41
Machine Learning : Random Forest with Python from Scratch©

Machine Learning : Random Forest with Python from Scratch©
MP4 | h264, 1280x720 | Lang: English | Audio: aac, 48000 Hz | 8h 45m | 3.09 GB

The Complet Decision Tree & Random Forest Course with Python-Mastering Decision Tree & Random Forest using real data
Details

Mathematical Foundations of Big Data Analytics

Posted By: AvaxGenius
Date: 12 Feb 2021 05:03:10
Mathematical Foundations of Big Data Analytics

Mathematical Foundations of Big Data Analytics by Vladimir Shikhman
English | PDF,EPUB | 2021 | 274 Pages | ISBN : 3662625202 | 18.6 MB

In this textbook, basic mathematical models used in Big Data Analytics are presented and application-oriented references to relevant practical issues are made. Necessary mathematical tools are examined and applied to current problems of data analysis, such as brand loyalty, portfolio selection, credit investigation, quality control, product clustering, asset pricing etc. – mainly in an economic context.
Details
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