APB-ML
Milestone Unit: Machine Learning
Keywords: Machine learning milestone
Contents
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.
Abstract
This unit collects machine learning units into a milestone.
This unit ...
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))
Objectives
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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.
Evaluation
Evaluation: NA
- This unit is not evaluated for course marks.
Contents
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Further reading, links and resources
Notes
Self-evaluation
If in doubt, ask! If anything about this learning unit is not clear to you, do not proceed blindly but ask for clarification. Post your question on the course mailing list: others are likely to have similar problems. Or send an email to your instructor.
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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