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[FreeTutorials.Us] [UDEMY] Fundamentals of Decision Trees in Machine Learning [FTU]

[FreeTutorials.Us] [UDEMY] Fundamentals of Decision Trees in Machine Learning [FTU]

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Description
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Learn the fundamentals of decision trees in maching learning

Created by : Tech Lab
Last updated : 4/2018
Language : English
Torrent Contains : 39 Files, 10 Folders
Course Source : https://www.udemy.com/course/fundamentals-of-machine-learning/

What you'll learn

• Learn the fundamentals of decision trees in machine learning
• Using the SPSS Modeler
• Building a CHAID model
• Using a lift and gains chart
• Exploring algorithms
• Building a tree interactively

Course content
all 31 lectures 02:27:32

Requirements

• Basic understanding of statistics

Description

A tree has many analogies in real life, and turns out that it has influenced a wide area of machine learning, covering both classification and regression. In decision analysis, a decision tree can be used to visually and explicitly represent decisions and decision making.

If you're working towards an understanding of machine learning, it's important to know how to work with decision trees. This course covers the essentials of machine learning, including predictive analytics and working with decision trees.

In this course, we'll explore several popular tree algorithms and learn how to use reverse engineering to identify specific variables. Demonstrations of using the IBM SPSS Modeler are included so you can understand how decisions trees work.

We'll also explore advanced concepts and details of decision tree algorithms.

This course is designed to give you a solid foundation on which to build more advanced data science skills.

Who this course is for :

• Anyone interested in learning machine learning
• Data science specialists.




File list
  • [FreeTutorials.Us] [UDEMY] Fundamentals of Decision Trees in Machine Learning [FTU]
  • 0. Websites you may like/How you can help Team-FTU.txt 229 B
  • 01 Introduction/001 Welcome.mp4 14.1 MB
  • 01 Introduction/002 Introduction.mp4 10.6 MB
  • 01 Introduction/003 Getting started.mp4 20.8 MB
  • 01 Introduction/attached files/003 Ex-Files-MachineLearning-Trees.zip 76.1 KB
  • 02 Decision Trees in IBM SPSS Modeler/004 Decision tree options in SPSS Modeler.mp4 30.3 MB
  • 02 Decision Trees in IBM SPSS Modeler/005 Building CHAID model and add a second model with CRT.mp4 64.1 MB
  • 02 Decision Trees in IBM SPSS Modeler/006 Analysis nodes.mp4 26.8 MB
  • 02 Decision Trees in IBM SPSS Modeler/007 Lift and gains chart.mp4 38.8 MB
  • 03 CHAID/008 Whats an algorithm.mp4 17 MB
  • 03 CHAID/009 Chi-squared.mp4 28.8 MB
  • 03 CHAID/010 Buliding a tree interactively.mp4 30.2 MB
  • 03 CHAID/011 Bonferonni adjustment and level of measurement.mp4 64.6 MB
  • 03 CHAID/012 CHAID.mp4 92.4 MB
  • 04 CRT/013 Gini coefficient.mp4 21.3 MB
  • 04 CRT/014 Understanding CRT.mp4 84 MB
  • 04 CRT/015 The complete CRT tree.mp4 26.6 MB
  • 04 CRT/016 Stopping rules in CHAID and CRT.mp4 47.2 MB
  • 04 CRT/017 Improving your model.mp4 61 MB
  • 05 QUEST/018 Understanding QUEST.mp4 6.6 MB
  • 05 QUEST/019 How QUEST handles variables.mp4 72.2 MB
  • 05 QUEST/020 How QUEST handles missing data.mp4 26.5 MB
  • 05 QUEST/021 Pruning and stopping rules in QUEST.mp4 44.9 MB
  • 05 QUEST/attached files/018 Ex-Files-ML-Adv-DecisionTrees.zip 873.3 KB
  • 06 C5.0/022 ID3 and C4.5.mp4 16.1 MB
  • 06 C5.0/023 Winnowing attributes and rule sets.mp4 63.1 MB
  • 06 C5.0/024 Understanding information gain.mp4 24.9 MB
  • 06 C5.0/025 Pruning in C5.0.mp4 77.4 MB
  • 06 C5.0/026 How C5.0 handles missing data.mp4 15.3 MB
  • 07 Advanced Topics/027 Ensembles.mp4 61.7 MB
  • 07 Advanced Topics/028 Bagging.mp4 101.4 MB
  • 07 Advanced Topics/029 Random forests.mp4 28.1 MB
  • 07 Advanced Topics/030 Boosting.mp4 41.9 MB
  • 07 Advanced Topics/031 Costs and priors.mp4 41.6 MB

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