APB-ML

Milestone Unit: Machine Learning

(Machine learning milestone)

 

Abstract:

This unit collects machine learning units into a milestone.

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Objectives: ...

Outcomes: ...

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Deliverables:

Time management: Before you begin, estimate how long it will take you to complete this unit. Then, record in your course journal: the number of hours you estimated, the number of hours you worked on the unit, and the amount of time that passed between start and completion of this unit.

Journal: Document your progress in your Course Journal. Some tasks may ask you to include specific items in your journal. Don't overlook these.

Insights: If you find something particularly noteworthy about this unit, make a note in your insights! page.

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Prerequisites:

• APB-ML-Deep_neural_networks (Deep Neural Networks)
• APB-ML-h2o (The h2o Machine Learning Toolkit)
• APB-ML-mlr (The mlr R Package)
• APB-ML-Random_forests (Random Forests)
• APB-ML-RWeka (The Weka Machine Learning Toolkit)
• APB-ML-Support_Vector_Machines (SVM (Support Vector Machines))

 

Sorry!

This page is only a stub; it is here as a placeholder to establish the logical framework of the site but there is no significant content as yet. Do not work with this material until it is updated to "live" status.

 

 

Evaluation

Evaluation: NA

This unit is not evaluated for course marks.

Contents

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Self-evaluation

Further reading, links and resources

Notes

 

About ...
 
Author:

Boris Steipe <boris.steipe@utoronto.ca>

Created:

2017-09-17

Modified:

2017-09-18

Version:

0.1

Version history:

• 0.1 First stub

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Sorry!

This page is only a stub; it is here as a placeholder to establish the logical framework of the site but there is no significant content as yet. Do not work with this material until it is updated to "live" status.