https://github.com/sskender/machine-learning-1
Machine Learning 1 FER labs
https://github.com/sskender/machine-learning-1
fer knn ldm linear-discriminant-classifier linear-regression linear-regression-classification logistic-regression logistic-regression-classifier machine-learning machine-learning-algorithms pgm struce svm
Last synced: 3 months ago
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Machine Learning 1 FER labs
- Host: GitHub
- URL: https://github.com/sskender/machine-learning-1
- Owner: sskender
- Created: 2021-10-04T10:09:58.000Z (over 3 years ago)
- Default Branch: master
- Last Pushed: 2023-10-04T00:51:51.000Z (over 1 year ago)
- Last Synced: 2025-01-26T20:26:01.790Z (4 months ago)
- Topics: fer, knn, ldm, linear-discriminant-classifier, linear-regression, linear-regression-classification, logistic-regression, logistic-regression-classifier, machine-learning, machine-learning-algorithms, pgm, struce, svm
- Language: Jupyter Notebook
- Homepage:
- Size: 6.59 MB
- Stars: 0
- Watchers: 2
- Forks: 0
- Open Issues: 5
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Metadata Files:
- Readme: README.md
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README
# Machine Learning 1
Machine Learning 1 FER labs
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Learning Outcomes:
- Define the basic concepts of machine learning
- Distinguish between generative and discriminative, parametric and nonparametric and probabilistic and nonprobabilistic models models
- Explain the theoretical assumptions, advantages, and disadvantages of basic machine learning algorithms
- Apply model selection and statistical evaluation of the learned model
- Apply various classification algorithms, inclusive generative, discriminative, and nonparametric ones
- Apply clustering algorithms and cluster validation
- Design and implement a machine learning method for classification/clustering and carry out its evalution
- Assess the suitability of a machine learning algorithm for a given task