Erinevus lehekülje "Machine learning ITI8565 (2017)" redaktsioonide vahel

Allikas: Kursused
Mine navigeerimisribale Mine otsikasti
P (Sven teisaldas lehekülje Machine learning ITI8565 pealkirja Machine learning ITI8565 (2017) alla)
 
(ei näidata sama kasutaja 16 vahepealset redaktsiooni)
1. rida: 1. rida:
Previous years: [https://courses.cs.ttu.ee/pages/Machine_learning 2015]
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Previous years: [https://courses.cs.ttu.ee/pages/Machine_learning 2016]
  
Spring 2015/2015
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Spring 2016/2017
  
 
ITI8565: Machine learning
 
ITI8565: Machine learning
9. rida: 9. rida:
 
EAP: 6.0
 
EAP: 6.0
  
Time and place: Thursdays
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Time and place:  
   Lectures: 14:00-15:30  ICT-A1
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   Lectures: Tuesdays 16:00-17:30  ICT-A1
   Labs: 16:00-17:30  ICT-402
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   Labs: Thursdays  16:00-17:30  ICT-402
  
Preliminary Information:
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Consultation: There is no scheduled time for consultation this semester. If you need consultation just drom me an e-mail and I will find time to answer your questions!
Examinations and consultations  ICT-405:
 
26.05 Consultation 14:00-15:30
 
02.06 Exam 1      14:00-15:30
 
10.06 Exam 2      16:00-17:30
 
14.06 Make-up Exam 14:00-15:30
 
  
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  Consultation: by appointment TBA
 
  
 
 
Additional information: sven.nomm@ttu.ee
 
Additional information: sven.nomm@ttu.ee
 
The course is organised by [http://cs.ttu.ee the Department of Comptuer Science]. The course is supported by [http://studyitin.ee/ IT Academy].
 
  
 
==Evaluation==
 
==Evaluation==
35. rida: 27. rida:
 
*61 < score < 70 -- grade 2 (satisfactory)
 
*61 < score < 70 -- grade 2 (satisfactory)
 
*51 < score < 60 -- grade 1 (acceptable)
 
*51 < score < 60 -- grade 1 (acceptable)
score ≤ 50 -- a student has failed to pass
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score ≤ 50 -- a student has failed the course
  
 
=Lectures =
 
=Lectures =
Lecture slides, necessary files, links and other necessary information would appear here before the lecture or practice.
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Lecture slides, necessary files, links and other necessary information would be provided by means of Moodle (To be set up by 10.02.2017)
 
 
=Lecture 1: Introduction and Decision Trees =
 
[[Media:Intro_and_DTrees_ML2016_1.pdf ‎|Slides]]
 
==Practice 1==
 
[[Media:Practice_1_ML2016.zip ‎|Code and data examples]]
 
 
 
= Please Observe the practice room change starting 12.02.2016 ICT-402 !!!=
 
=Lecture 2: k- Nearest Neighbors  =
 
[[Media:Lecture2_ML2016_kNN.pdf |Slides]]
 
 
 
[http://ciml.info/dl/v0_8/ciml-v0_8-ch02.pdf Reading]
 
 
 
==Practice 2==
 
[[Media:Data_lecture2.zip ‎|Data]]
 
 
 
 
 
=Lecture 3: K- Means  =
 
[[Media:Lecture3_ML2016_K_means.pdf |Slides]]
 
 
 
=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  =
 
[[Media:Lecture4_ML2016_Linear_Regression.pdf |Slides]]
 
 
 
= Home Assignment 1 =
 
Home Assignment 1 is available in Moodle! The deadline is 15.03.2016 23:55 !
 
 
 
=Lecture 5:  =
 
[[Media:Lecture5_ML2016_GMM_EM_Clusters.pdf |Slides]]
 
 
 
=Lecture 6:  =
 
[[Media:Lecture6_ML2016_Neural_Networks.pdf |Slides]]
 
  
=Lecture 7:   =
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== Lecture 1: Intro ==
[[Media:Lecture7_ML2016_Logistic_Regression.pdf |Slides]]
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[[Media:Intro_and_DTrees_ML2017_1.pdf |Slides]]
  
=Lecture 8:  =
 
[[Media:Lecture8_ML2016_Competitive_Learning.pdf |Slides]]
 
  
=Lecture 9:   =
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== Lecture 2: Distance and classification ==
Due to a number of requests to postpone the Test Nr1.
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[[Media:Lecture2_ML2017_kNN.pdf |Slides]]
Test Nr1. will take place on Thursday April the 7th.  
 
  
On march the 31st studies will take place as usually.
 
[[Media:Lecture9_ML2016_N_Markov_chains_and_hMm.pdf |Slides]]
 
  
=Test 1: 07.04.2016 =
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== Lecture 3: Clustering I ==
Nothing is scheduled for today  practice, but the room will be opened for your self practice. 
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[[Media:Lecture3_ML2017_Clustering.pdf |Slides]]
Sven will be around to answer your questions.  
 
There will be no consultation today
 
  
=28.04 =
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== Lecture 4: Clustering II ==
Test 1 Make-Up will take place on 28.04.2016 during the lecture.  
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[[Media:Lecture4_ML2017_Clustering2.pdf |Slides]]
  
Practice will take place at its usual time.
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Moodle environment at ained.ttu.ee has been updated.

Viimane redaktsioon: 29. jaanuar 2018, kell 13:44

Previous years: 2016

Spring 2016/2017

ITI8565: Machine learning

Taught by: Sven Nõmm

EAP: 6.0

Time and place:

 Lectures: Tuesdays 16:00-17:30  ICT-A1
 Labs:  Thursdays   16:00-17:30  ICT-402

Consultation: There is no scheduled time for consultation this semester. If you need consultation just drom me an e-mail and I will find time to answer your questions!



Additional information: sven.nomm@ttu.ee

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 the course

Lectures

Lecture slides, necessary files, links and other necessary information would be provided by means of Moodle (To be set up by 10.02.2017)

Lecture 1: Intro

Slides


Lecture 2: Distance and classification

Slides


Lecture 3: Clustering I

Slides

Lecture 4: Clustering II

Slides

Moodle environment at ained.ttu.ee has been updated.