Download Linkedin - Machine Learning and AI Foundations - Decision Trees with KNIME torrent

Linkedin - Machine Learning and AI Foundations - Decision Trees with KNIME

Torrent:	Linkedin - Machine Learning and AI Foundations - Decision Trees with KNIME
Description:	Machine Learning and AI Foundations: Decision Trees with KNIME https://FreeCourseWeb.com Released 06/2022 MP4 \| Video: h264, 1280x720 \| Audio: AAC, 44.1 KHz, 2 Ch Skill Level: Intermediate \| Genre: eLearning \| Language: English + srt \| Duration: 1h 59m \| Size: 311 MB Many data science specialists are looking to pivot toward focusing on machine learning. In this course, Keith McCormick covers the essentials of machine learning pertaining to predictive analytics and working with decision trees. Explore several popular tree algorithms and learn how to use reverse engineering to identify specific variables. nstrations of using the KNIME modeler are included so you can understand how decision trees work. This course is designed to give you a solid foundation on which to build more advanced data science skills.
Downloads:	73
Category:	Other /Tutorials
Size:	311 MB
Show Files »	[ FreeCourseWeb.com ] Linkedin - Machine Learning and AI Foundations - Decision Trees with KNIME Get Bonus Downloads Here.url (0.2 KB) ~Get Your Files Here ! 01 - Introduction 01 - The basics of decision trees.mp4 (7.2 MB) 01 - The basics of decision trees.srt (2.1 KB) 02 - What you should know.mp4 (2.0 MB) 02 - What you should know.srt (1.6 KB) 03 - How to use the practice files.mp4 (4.5 MB) 03 - How to use the practice files.srt (2.2 KB) 02 - 1. Introducing Decision Trees 01 - What is a decision tree.mp4 (7.2 MB) 01 - What is a decision tree.srt (4.9 KB) 02 - The pros and cons of decision trees.mp4 (10.1 MB) 02 - The pros and cons of decision trees.srt (8.1 KB) 03 - Introducing KNIME.mp4 (12.8 MB) 03 - Introducing KNIME.srt (6.0 KB) 04 - A quick review of machine learning basics with examples.mp4 (20.3 MB) 04 - A quick review of machine learning basics with examples.srt (10.4 KB) 05 - An overview of decision tree algorithms.mp4 (12.5 MB) 05 - An overview of decision tree algorithms.srt (5.8 KB) 03 - 2. Introducing the C5.0 Algorithm 01 - Ross Quinlan, ID3, C4.5, and C5.0.mp4 (5.7 MB) 01 - Ross Quinlan, ID3, C4.5, and C5.0.srt (3.6 KB) 02 - Understanding the entropy calculation.mp4 (11.7 MB) 02 - Understanding the entropy calculation.srt (9.1 KB) 03 - How C4.5 handles missing data.mp4 (6.0 MB) 03 - How C4.5 handles missing data.srt (4.4 KB) 04 - The Give Me Some Credit data set.mp4 (7.9 MB) 04 - The Give Me Some Credit data set.srt (4.6 KB) 05 - Working with the prebuilt example.mp4 (15.9 MB) 05 - Working with the prebuilt example.srt (8.8 KB) 06 - KNIME settings for C4.5.mp4 (8.6 MB) 06 - KNIME settings for C4.5.srt (4.9 KB) 07 - How C4.5 handles nominal variables.mp4 (7.4 MB) 07 - How C4.5 handles nominal variables.srt (3.6 KB) 08 - How C4.5 handles continuous variables.mp4 (4.2 MB) 08 - How C4.5 handles continuous variables.srt (2.3 KB) 09 - Equal size sampling.mp4 (6.4 MB) 09 - Equal size sampling.srt (3.3 KB) 10 - A quick look at the complete C4.5 tree.mp4 (6.4 MB) 10 - A quick look at the complete C4.5 tree.srt (4.3 KB) 11 - Evaluating the accuracy of your C4.5 tree.mp4 (9.3 MB) 11 - Evaluating the accuracy of your C4.5 tree.srt (4.4 KB) 12 - When to turn off pruning.mp4 (16.4 MB) 12 - When to turn off pruning.srt (8.6 KB) 04 - 3. Introducing Classification Trees 01 - Introducing Leo Breiman and CART.mp4 (11.6 MB) 01 - Introducing Leo Breiman and CART.srt (5.9 KB) 02 - What is the Gini coefficient.mp4 (7.0 MB) 02 - What is the Gini coefficient.srt (4.0 KB) 03 - How CART handles missing data using surrogates.mp4 (9.8 MB) 03 - How CART handles missing data using surrogates.srt (8.0 KB) 04 - Changing the settings in KNIME.mp4 (7.8 MB) 04 - Changing the settings in KNIME.srt (4.5 KB) 05 - How CART handles nominal variables.mp4 (4.6 MB) 05 - How CART handles nominal variables.srt (2.6 KB) 06 - A quick look at the complete CART tree.mp4 (7.2 MB) 06 - A quick look at the complete CART tree.srt (3.6 KB) 07 - Evaluating the accuracy of your CART tree.mp4 (3.4 MB) 07 - Evaluating the accuracy of your CART tree.srt (2.0 KB) 05 - 4. Introducing Regression Trees 01 - MPG data set.mp4 (4.5 MB) 01 - MPG data set.srt (1.9 KB) 02 - The regression tree prebuilt example.mp4 (12.0 MB) 02 - The regression tree prebuilt example.srt (6.3 KB) 03 - The math behind regression trees.mp4 (4.0 MB) 03 - The math behind regression trees.srt (3.6 KB) 04 - How RT handles nominal variables.mp4 (11.1 MB) 04 - How RT handles nominal variables.srt (6.5 KB) 05 - Ordinal variable handling.mp4 (10.1 MB) 05 - Ordinal variable handling.srt (5.4 KB) 06 - Closer look at a full regression tree.mp4 (9.1 MB) 06 - Closer look at a full regression tree.srt (5.3 KB) 07 - KNIME's missing data options for regression trees.mp4 (7.7 MB) 07 - KNIME's missing data options for regression trees.srt (4.5 KB) 08 - Line plot.mp4 (7.9 MB) 08 - Line plot.srt (3.8 KB) 09 - Accuracy.mp4 (6.6 MB) 09 - Accuracy.srt (3.6 KB) 06 - Conclusion 01 - Next steps.mp4 (1.7 MB) 01 - Next steps.srt (1.6 KB) Bonus Resources.txt (0.4 KB) Ex_Files_ML_and_AI_Foundations_Decision_Trees_KNIME Exercise Files Chapter_2_Example_for_Learning_a_Decision_Tree.knwf (787.2 KB) Chapter_3_Example_for_Learning_a_Decision_Tree.knwf (787.2 KB) Chapter_4_Example_for_Learning_a_Decision_Tree.knwf (787.2 KB) files
Added:	2022-07-02 10:02:21
Language:	English
Peers:	Seeders : 8 , Leechers : 3
Release name:	Linkedin - Machine Learning and AI Foundations - Decision Trees with KNIME
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