==== Tutorials =====

^   T^     Date^ Tutor  ^ Deadline   ^ Contents   ^  Materials   ^    
|   1|    4.10.| PR |   | Introduction, Python environment  | {{:courses:b4m36smu:tutorials:tutorial1.pdf|PDF}} |
|   2|    27.2.| JB |   | PEAS agent model, environment properties, input/output types of machine learning models, demos | {{:courses:b4m36smu:tutorials:introtestsolution.pdf|solution to entrance test}} {{:courses:b4m36smu:tutorial2.pdf|Slides}} |
|   3|     6.3.| JB |   | Learning conjunctive and disjunctive concepts | {{:courses:b4m36smu:tutorial3.pdf|}} {{:courses:b4m36smu:cv3_student.py|}}  {{:courses:b4m36smu:cv3_referential_solution.py|}}|
|   4|    13.3.| JB |   | Assignment of the first student project | {{:courses:b4m36smu:project1.zip|}} {{:courses:b4m36smu:smu_student_projects.pdf|}} |
|   5|    20.3.| OH  |   | Bayesian Networks - semantics   | {{:courses:b4m36smu:tutorial1.zip|}}  |
|   6|    27.3.| OH  |   | Bayesian Networks  - inference |{{:courses:b4m36smu:tutorial2.zip|}} |
|   7|     3.4.| OH   | 	  | Assignment of the second student project    |{{:courses:b4m36smu:smu_project_v1.01.pdf|}} {{:courses:b4m36smu:project.zip|}} |
|   8|    10.4.| MS   |   | Inductive Logic Programming - learning from interpretations    | {{:courses:b4m36smu:ilp1.pdf|}} {{:courses:b4m36smu:ilptutorial1.zip|}} |
|   9|    24.4.| MS   | 9. 5. 2017  | Inductive Logic Programming - learning from clauses    | {{:courses:b4m36smu:ilp2nassignment.pdf|}} {{:courses:b4m36smu:ilpassignment_1.0.2.zip|}} | |
|  10| **2.5.**| MS   |   | ILP, Q&A    | {{:courses:b4m36smu:ilp3_v1.1.pdf|}} |
|  11|**11.5.**| PR   |   | Reinforcement learning demos and introduction   | {{courses:b4m36smu:tutorials:rltutorial1.zip}}, {{courses:b4m36smu:tutorials:rltutorial1-handout.pdf|slides}} |
|  12|    15.5.| PR   | 06/02/2017 (5am)  | ILP example, Assignment of the fourth project    | {{courses:b4m36smu:tutorials:project4.zip| zip (v 1.0.3)}}, {{courses:b4m36smu:tutorials:project4spec.pdf| pdf (v 1.0.3)}} |
|  13|    22.5.| PR   |   | Passive reinforcement learning agents, TD methods    | {{courses:b4m36smu:tutorials:rltutorial3.zip|zip}}, {{courses:b4m36smu:tutorials:rltutorial3.pdf|slides}}  |