Introduction to Decision Trees | Decision Trees for Machine Learning | Part 1
The decision tree algorithm belongs to the family of supervised learning algorithms. Just like other supervised learning algorithms, decision trees model relationships, and dependencies between the predictive outputs and the input features. As the name suggests, the decision tree algorit
From playlist Introduction to Machine Learning 101
(ML 2.1) Classification trees (CART)
Basic intro to decision trees for classification using the CART approach. A playlist of these Machine Learning videos is available here: http://www.youtube.com/my_playlists?p=D0F06AA0D2E8FFBA
From playlist Machine Learning
Decision trees are powerful and surprisingly straightforward. Here's how they are grown. Code: https://github.com/brohrer/brohrer.github.io/blob/master/code/decision_tree.py Slides: https://docs.google.com/presentation/d/1fyGhGxdGcwt_eg-xjlMKiVxstLhw42XfGz3wftSzRjc/edit?usp=sharing PERM
From playlist Data Science
Decision Tree Examples | Edureka
( Data Science Training - https://www.edureka.co/data-science ) Watch Sample Class Recording: http://www.edureka.co/data-science?utm_source=youtube&utm_medium=referral&utm_campaign=introduction-decision-tree-examples A decision tree is a tree-like structure in which internal node repres
From playlist Data Science Training Videos
Introduction to Decision Tree | Edureka
( Data Science Training - https://www.edureka.co/data-science ) Watch Sample Class Recording: http://www.edureka.co/data-science?utm_source=youtube&utm_medium=referral&utm_campaign=introduction-decision-trees A decision tree is a tree-like structure in which internal node represents tes
From playlist Data Science Training Videos
Decision trees - A friendly introduction
A video about decision trees, and how to train them on a simple example. Accompanying blog post: https://medium.com/@luis.serrano/splitting-data-by-asking-questions-decision-trees-74afed9cd849 Helper videos: - Gini index: https://www.youtube.com/watch?v=u4IxOk2ijSs - Entropy and informat
From playlist Supervised Learning
Fundamental Machine Learning Algorithms - Decision Trees
The code is accessible at https://github.com/sepinouda/Machine-Learning/
From playlist Machine Learning Course
Data Science - Part V - Decision Trees & Random Forests
For downloadable versions of these lectures, please go to the following link: http://www.slideshare.net/DerekKane/presentations https://github.com/DerekKane/YouTube-Tutorials This lecture provides an overview of decision tree machine learning algorithms and random forest ensemble techniq
From playlist Data Science
Python for Data Analysis: Decision Trees
This video covers the basics of decision trees and how to make decision trees for classification in Python. Subscribe: ► https://www.youtube.com/c/DataDaft?sub_confirmation=1 This is lesson 29 of a 30-part introduction to the Python programming language for data analysis and predictive m
From playlist Python for Data Analysis
Introduction to R: Decision Trees
This lesson covers the basics of decision trees in R. This is lesson 29 of a 30-part introduction to the R programming language for data analysis and predictive modeling. Link to the code notebook below: Intro to R: Decision Trees https://www.kaggle.com/hamelg/intro-to-r-part-29-Decision
From playlist Introduction to R
Python for Data Analysis: Random Forests
This video covers the basics of random forests and how to make random forest models for classification in Python. Subscribe: ► https://www.youtube.com/c/DataDaft?sub_confirmation=1 This is lesson 30 of a 30-part introduction to the Python programming language for data analysis and predic
From playlist Python for Data Analysis
20 Data Analytics: Decision Tree
Lecture on decision tree-based machine learning with workflows in R and Python and linkages to bagging, boosting and random forest.
From playlist Data Analytics and Geostatistics
Automating Annotation Process Using Rule-Based Algorithm
Install NLP Libraries https://www.johnsnowlabs.com/install/ Register for Healthcare NLP Summit 2023: https://www.nlpsummit.org/#register Watch all NLP Summit 2022 sessions: https://www.nlpsummit.org/nlp-summit-2022-watch-now/ Presented by Priya Shaji, Data Scientist at MEMORIAL SLOAN
From playlist NLP Summit 2022
14 Machine Learning: Decision Tree
Lecture on machine learning prediction with decision trees. A simple, intuitive prerequisite for more powerful ensemble tree methods. Follow along with the demonstration in Python: https://github.com/GeostatsGuy/PythonNumericalDemos/blob/master/SubsurfaceDataAnalytics_DecisionTree.ipynb
From playlist Machine Learning
Introduction to R: Random Forests
This lesson covers the basics of random forests in R. This is lesson 30 of a 30-part introduction to the R programming language for data analysis and predictive modeling. Link to the code notebook below: Intro to R: Random Forests https://www.kaggle.com/hamelg/intro-to-r-part-30-Random-F
From playlist Introduction to R
Random Forests : Data Science Concepts
How do random forests work? Decision trees video: https://www.youtube.com/watch?v=kakLu2is3ds Decision tree pruning video: https://www.youtube.com/watch?v=t56Nid85Thg Overfitting video: https://www.youtube.com/watch?v=-JopeGg60QY
From playlist Data Science Concepts
Decision Tree 7: continuous, multi-class, regression
Full lecture: http://bit.ly/D-Tree Decision trees are interpretable, they can handle real-valued attributes (by finding appropriate thresholds), and handle multi-class classification and regression with minimal changes.
From playlist Decision Tree