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courses
smu
tutorials
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Tutorials
T
Date
Tutor
Deadline
Contents
Materials
1
19.2.
PR
Introduction, Python environment
PDF
entrance test
sample solution
2
26.2.
JB
PEAS agent model, environment properties, input/output types of machine learning models, demos
Slides
3
5.3.
JB
Learning conjunctive and disjunctive concepts
tutorial3.pdf
cv3_student.py
cv3_referential_solution.py
4
12.3.
JB
Assignment of the first student project
project1.zip
smu_student_projects.pdf
5
19.3.
OH
Bayesian Networks - semantics
tutorial1.zip
6
26.3.
OH
Bayesian Networks - inference
tutorial2.zip
2.4
holiday
7
9.4.
OH
Assignment of the second student project
smu_project_2018.pdf
project_2018.zip
8
16.4.
MS
Inductive Logic Programming - learning from interpretations
smu_ilp_1.pdf
ilptutorial1.rar
9
23.4.
MS
Inductive Logic Programming - learning from entailment, ILP assignment
smu_ilp_2.pdf
ilptutorial2nhw.rar
10
30.4.
MS
RLGG, Propositionalization
smu_ilp_3.pdf
muta.txt
11
7.5.
PR
RL introduction, Assignment of the fourth project
rltutorial1.zip
,
slides
,
zip_HW (v 1.1.1)
,
pdf_HW (v 1.1.1)
12
14.5.
PR
Passive reinforcement learning agents, TD methods
zip
,
slides
13
21.5.
PR
Problems by hand
Notes on convergence
courses/smu/tutorials.txt
· Last modified: 2018/05/22 10:29 by
rysavpe1