Erinevus lehekülje "Machine learning ITI8565 (2017)" redaktsioonide vahel
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=Lecture 5: = | =Lecture 5: = | ||
[[Media:Lecture5_ML2016_GMM_EM_Clusters.pdf |Slides]] | [[Media:Lecture5_ML2016_GMM_EM_Clusters.pdf |Slides]] | ||
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| + | =Lecture 6: = | ||
| + | [[Media:Lecture6_ML2016_Neural_Networks.pdf |Slides]] | ||
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| + | =Lecture 7: = | ||
| + | [[Media:Lecture7_ML2016_Logistic_Regression.pdf |Slides]] | ||
Redaktsioon: 21. märts 2016, kell 14:15
Previous years: 2015
Spring 2015/2015
ITI8565: Machine learning
Taught by: Sven Nõmm
EAP: 6.0
Time and place: Thursdays
Lectures: 14:00-15:30 ICT-A1 Labs: 16:00-17:30 ICT-402
Consultation: by appointment TBA
Additional information: sven.nomm@ttu.ee
The course is organised by the Department of Comptuer Science. The course is supported by IT Academy.
Evaluation
- 91 < score -- grade 5 (excellent)
- 81 < score < 90 -- grade 4 (very good)
- 71 < score < 80 -- grade 3 (good)
- 61 < score < 70 -- grade 2 (satisfactory)
- 51 < score < 60 -- grade 1 (acceptable)
score ≤ 50 -- a student has failed to pass
Lectures
Lecture slides, necessary files, links and other necessary information would appear here before the lecture or practice.
Lecture 1: Introduction and Decision Trees
Practice 1
Please Observe the practice room change starting 12.02.2016 ICT-402 !!!
Lecture 2: k- Nearest Neighbors
Practice 2
Lecture 3: K- Means
NB! Moodle environment for the course has been activated
If you need the code to enroll please contact the teacher by e-mail. I will continue to upload lecture slides here. All other resources including home assignments will be available thorough the moodle only!!!
Lecture 4: Linear Regression
Home Assignment 1
Home Assignment 1 is available in Moodle! The deadline is 15.03.2016 23:55 !