Commit 4c419aa3 authored by Carsten Eie Frigaard's avatar Carsten Eie Frigaard
Browse files

update

parent 828c7f4a
...@@ -22,11 +22,6 @@ DEFS ...@@ -22,11 +22,6 @@ DEFS
CONTENT Litteratur CONTENT Litteratur
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%\header{Litteratur}
\sub{Hands-on Machine Learning [HOML]} \sub{Hands-on Machine Learning [HOML]}
\dl{ \dl{
...@@ -72,15 +67,11 @@ CONTENT Litteratur ...@@ -72,15 +67,11 @@ CONTENT Litteratur
} }
} }
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CONTENT Kursusforkortelser
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%\header{Kursusforkortelser} CONTENT Kursusforkortelser
\dl{ \dl{
\dt{[\b{AI}]:} \dt{[\b{AI}]:}
...@@ -154,14 +145,12 @@ CONTENT Kursusforkortelser ...@@ -154,14 +145,12 @@ CONTENT Kursusforkortelser
\dd{Et specifikt spørgsmål (Question) i en journal opgave, ala Qc for opgave 'c' i et journal spørgsmål.} \dd{Et specifikt spørgsmål (Question) i en journal opgave, ala Qc for opgave 'c' i et journal spørgsmål.}
} }
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CONTENT Dokumentation og links CONTENT Dokumentation og links
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\sub{Web sites} \sub{Web sites}
Primære Primære
...@@ -212,14 +201,12 @@ Guides etc. ...@@ -212,14 +201,12 @@ Guides etc.
\item{Scikit-learn cheat sheet XXX} \item{Scikit-learn cheat sheet XXX}
} }
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CONTENT GPU Cluster CONTENT GPU Cluster
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Der er adgang til en GPU baseret server ifbm kurset. Serveren består af en Der er adgang til en GPU baseret server ifbm kurset. Serveren består af en
'master' som kan tilgås via 'master' som kan tilgås via
...@@ -347,14 +334,12 @@ frigiver!} ...@@ -347,14 +334,12 @@ frigiver!}
\displaycode{! pkill <procesnavn>} \displaycode{! pkill <procesnavn>}
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CONTENT Kriterier for O4 CONTENT Kriterier for O4
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\sub{Kriterier for O4 rapport} \sub{Kriterier for O4 rapport}
\p{Til den sidst aflevering, O4, skal i præsentere jeres arbejde med jeres eget \p{Til den sidst aflevering, O4, skal i præsentere jeres arbejde med jeres eget
...@@ -443,14 +428,12 @@ font.} ...@@ -443,14 +428,12 @@ font.}
\p{De 15 siders grænser er primært indført for ikke at gøre O4 for omfattende i \p{De 15 siders grænser er primært indført for ikke at gøre O4 for omfattende i
projekt/afleverings tid.} projekt/afleverings tid.}
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CONTENT Journal afleveringsformat CONTENT Journal afleveringsformat
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\sub{Journal afleveringsformat [O1,O2,O3]} \sub{Journal afleveringsformat [O1,O2,O3]}
\p{I skal uploade opgaverne / journalerne i PDF format.} \p{I skal uploade opgaverne / journalerne i PDF format.}
...@@ -577,12 +560,7 @@ svært af få nok typografisk 'kvalitet' i en Jupyter Notebook aflevering.} ...@@ -577,12 +560,7 @@ svært af få nok typografisk 'kvalitet' i en Jupyter Notebook aflevering.}
CONTENT L00 CONTENT L00
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% \sub{Formål} %\header{Forberedelse inden kursusstart}
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%\header{Forberedelse inden kursusstart}
\sub{Formål}
\p{\i{Gruppe tilmelding:} tilmeld dig til en ITMAL gruppe (find link i Brightspace!).} \p{\i{Gruppe tilmelding:} tilmeld dig til en ITMAL gruppe (find link i Brightspace!).}
...@@ -660,17 +638,13 @@ rækkefølge:} ...@@ -660,17 +638,13 @@ rækkefølge:}
bruges/introduceres dog ikke formelt i dette kursus (du er velkommen til selv bruges/introduceres dog ikke formelt i dette kursus (du er velkommen til selv
at undersøg/bruge det).} at undersøg/bruge det).}
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CONTENT L01
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%\header{Introduktion} CONTENT L01
\sub{Formål} \sub{Formål} %\header{Introduktion}
Denne lektion har til formål at give indledende information om kurset. Dvs. Denne lektion har til formål at give indledende information om kurset. Dvs.
at vi præsentere de formelle rammer vdr. at vi præsentere de formelle rammer vdr.
...@@ -786,12 +760,7 @@ brug for en python og lineær algebra kick-start.} ...@@ -786,12 +760,7 @@ brug for en python og lineær algebra kick-start.}
CONTENT L02 CONTENT L02
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% \sub{Formål} %\header{Supervised classification, Cost function, Performance metrics}
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%\header{Supervised classification, Cost function, Performance metrics}
\sub{Formål}
\p{Vi lægger ud med at se på datamat-læring eller ML-læring via cost \p{Vi lægger ud med at se på datamat-læring eller ML-læring via cost
funktionen, J, dvs. hvordan en supervised ML algoritme i princippet kunne funktionen, J, dvs. hvordan en supervised ML algoritme i princippet kunne
...@@ -876,18 +845,12 @@ læring den pågældende algoritme har opnået på de pågældende data.} ...@@ -876,18 +845,12 @@ læring den pågældende algoritme har opnået på de pågældende data.}
} }
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CONTENT L03 CONTENT L03
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% \sub{Formål} %\header{End-to-end ML}
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%\header{End-to-end ML}
\sub{Formål}
\p{Opsamlingslektion: vi tager et genblik på \i{§ 2 End-to-End Machine Learning \p{Opsamlingslektion: vi tager et genblik på \i{§ 2 End-to-End Machine Learning
Project}, og samler op på dette brede kapitel.} Project}, og samler op på dette brede kapitel.}
...@@ -954,32 +917,25 @@ ser vi derfor til sidst på Scikit-learns Pipelines.} ...@@ -954,32 +917,25 @@ ser vi derfor til sidst på Scikit-learns Pipelines.}
\link**{[HOME]/L03/lesson03.pdf} \link**{[HOME]/L03/lesson03.pdf}
} }
END
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CONTENT L04 CONTENT L04
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% \sub{Formål} %\header{Regression og SGD}
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%\header{Regression og SGD}
\sub{Formål}
\p{Vi analysere supervised regressions modeller i ML i forhold til den nu kendte \p{Vi analysere \i{supervised regressions} modeller i ML i forhold til den nu
supervised klassifikation metode.} kendte supervised klassifikation metode.}
\p{Modellen lineær regression gennemanalyseres og der angives både analytiske \p{Modellen \i{lineær} regression gennemanalyseres og der angives både
og numeriske løsninger til træning af en lineær model.} analytiske og numeriske løsninger til træning af en lineær model.}
\p{For den numeriske løsning går vi i dybden med træningsmetoden \i{Stochastic \p{For den numeriske løsning går vi i dybden med træningsmetoden \i{Stochastic
Gradient Decent metoden} (SGD).} Gradient Decent metoden} (SGD).}
\p{Endelig sluttes af med korter introduktion til logistisk regression (der danner \p{Endelig sluttes af med korter introduktion til logistisk regression, der danner
grundlag for neuroner i neurale net.)} grundlag for neuroner i neurale net.}
\sub{Indhold} \sub{Indhold}
...@@ -991,8 +947,9 @@ grundlag for neuroner i neurale net.)} ...@@ -991,8 +947,9 @@ grundlag for neuroner i neurale net.)}
\sub{Litteratur} \sub{Litteratur}
\enumerate{ \itemize*{
\item{\i{§ x xx} [HOML]} \item{\i{§ 4 Training Models} (pp.111-134) [HOML]}
\subitem*{indtil og eksklusivt \i{Regularized Linear Models}}
} }
\sub{Forberedelse inden lektionen} \sub{Forberedelse inden lektionen}
...@@ -1003,17 +960,18 @@ grundlag for neuroner i neurale net.)} ...@@ -1003,17 +960,18 @@ grundlag for neuroner i neurale net.)}
\sub{På klassen} \sub{På klassen}
\itemize{ \enumerate{
\item{Almindelig forelæsning} \item{Almindelig forelæsning}
\item{\b{Opgave} (SGD): \link**{[HOME]/L04/sgd.ipynb}} \item{\b{Opgave} (SGD): \link**{[HOME]/L04/sgd.ipynb}}
} }
\sub{Slides} \sub{Slides}
\displaystyle{ \itemize*{
\link**{[HOME]/L04/lesson04.pdf} \item{\link**{[HOME]/L04/lesson04.pdf}}
} }
END END
Formål : Formål :
...@@ -1029,7 +987,8 @@ Emner : ...@@ -1029,7 +987,8 @@ Emner :
Lineær (til regression) og logistisk regression (til klassifikation) Lineær (til regression) og logistisk regression (til klassifikation)
Cost function, closed-form vs. iterative solutions, gradient descent, learning rate Cost function, closed-form vs. iterative solutions, gradient descent, learning
rate
Litteratur : Litteratur :
......
...@@ -6,7 +6,7 @@ PYPLAN = mk_plan.py ...@@ -6,7 +6,7 @@ PYPLAN = mk_plan.py
PWD = $(shell pwd) PWD = $(shell pwd)
COURSEFILES = ITMAL_E21 COURSEFILES = ITMAL_E21
MKDIFF=colordiff -dw Refs/$1 $1 && echo "DIFF OK" && rm $1 MKDIFF=printf "DIFF Ref/%-10s Test/ .. " $1 && colordiff -dw Refs/$1 Test/ && echo "DIFF OK" && rm Test/$1
build: build:
@ $(PYCOURSE) -c $(COURSEFILES)/course.tex -v -o ../../Html/ @ $(PYCOURSE) -c $(COURSEFILES)/course.tex -v -o ../../Html/
...@@ -21,21 +21,21 @@ sync: build ...@@ -21,21 +21,21 @@ sync: build
@ echo "SYNC..DONE" @ echo "SYNC..DONE"
TESTARGS=-v -v TESTARGS=-v
test: test: clean
@ $(PYCOURSE) -c Test/course.tex $(TESTARGS) -o ./ @ cd Test && $(PWD)/$(PYCOURSE) -c course.tex $(TESTARGS)
@ cd Test && $(PWD)/$(PYPLAN) -p plan.txt $(TESTARGS)
@ cd Test && $(PWD)/$(PYFILETREE) $(TESTARGS)
@ $(call MKDIFF,L00.html) @ $(call MKDIFF,L00.html)
@ $(call MKDIFF,L01.html) @ $(call MKDIFF,L01.html)
@ $(PYPLAN) -p Test/plan.txt $(TESTARGS) -o plan.html
@ $(call MKDIFF,plan.html) @ $(call MKDIFF,plan.html)
@ cd Test && $(PWD)/$(PYFILETREE) $(TESTARGS) -header "ITMAL Backend File Structure" -o $(PWD)/tree.html
@ $(call MKDIFF,tree.html) @ $(call MKDIFF,tree.html)
edit: edit:
joe course.tex #joe $(PYCOURSE) joe course.tex #joe $(PYCOURSE)
clean: clean:
@ rm -f index.html out.html test.html ../Html/L??.html @ rm -f Test/*.html ../Html/L??.html
#get: #get:
# wget https://gitlab.au.dk/au204573/brightspacemods/-/raw/master/JS/demo.js # wget https://gitlab.au.dk/au204573/brightspacemods/-/raw/master/JS/demo.js
......
...@@ -2,7 +2,7 @@ ...@@ -2,7 +2,7 @@
<html> <html>
<!-- AUTOGENERATED HTML from CourseBuilder, CEF --> <!-- AUTOGENERATED HTML from CourseBuilder, CEF -->
<meta http-equiv='Content-Type' content='text/html; charset=utf-8'/> <meta http-equiv='Content-Type' content='text/html; charset=utf-8'/>
<body style='font-family: times new roman, times, serif;font-size: 12pt;color: #424222;'> <body style='font-family: times new roman, times, serif;font-size: 12pt;color: #000000;'>
......
...@@ -2,7 +2,7 @@ ...@@ -2,7 +2,7 @@
<html> <html>
<!-- AUTOGENERATED HTML from CourseBuilder, CEF --> <!-- AUTOGENERATED HTML from CourseBuilder, CEF -->
<meta http-equiv='Content-Type' content='text/html; charset=utf-8'/> <meta http-equiv='Content-Type' content='text/html; charset=utf-8'/>
<body style='font-family: times new roman, times, serif;font-size: 12pt;color: #424222;'> <body style='font-family: times new roman, times, serif;font-size: 12pt;color: #000000;'>
......
...@@ -2,150 +2,175 @@ ...@@ -2,150 +2,175 @@
<html> <html>
<!-- AUTOGENERATED HTML from CourseBuilder, CEF --> <!-- AUTOGENERATED HTML from CourseBuilder, CEF -->
<meta http-equiv='Content-Type' content='text/html; charset=utf-8'/> <meta http-equiv='Content-Type' content='text/html; charset=utf-8'/>
<body style='font-family: times new roman, times, serif;font-size: 12pt;color: #424222;'> <body style='font-family: times new roman, times, serif;font-size: 12pt;color: #000000;'>
<style type='text/css'>
.ECE_coursebuilder_table { background-color:white; border-collapse:collapse; text-align:center }
.ECE_coursebuilder_table th { background-color:black; color:white; }
.ECE_coursebuilder_table th, .ECE_coursebuilder_table td { padding:5px; border:1px solid black; }
.ECE_coursebuilder_table tr:nth-child(even) { background: #DDD; }
.ECE_coursebuilder_table tr:nth-child(odd) { background: white; }
</style>
NOTES<br> NOTES<br>
none<br> none<br>
<br> <br>
<table cellspacing="0px" cellpadding="1px" border="1px" align="center"> <table class='ECE_coursebuilder_table'>
<tbody> <tbody>
<tr style="background-color: #000000;" align="center"> <tr>
<td width="40"><span style="background-color: #000000; color: #ffffff;"><strong>Uge</strong></span></td> <th width='40'>Uge</th>
<td width="110"><span style="background-color: #000000; color: #ffffff;"><strong>Dato</strong></span></td> <th width='110'>Dato</th>
<td width="20"><span style="background-color: #000000; color: #ffffff;"><strong>Lektion</strong></span></td> <th width='20'>Lektion</th>
<td width="200"><span style="background-color: #000000; color: #ffffff;"><strong>Emne</strong></span></td> <th width='200'>Emne</th>
<td width="90"><span style="background-color: #000000; color: #ffffff;"><strong>Opgave</strong></span></td> <th width='90'>Opgave</th>
<td width="65"><span style="background-color: #000000; color: #ffffff;"><strong>Underviser</strong></span></td> <th width='65'>Underviser</th>
<td width="150"><span style="background-color: #000000; color: #ffffff;"><strong>Kommentar</strong></span></td> <th width='150'>Kommentar</th>
</tr> </tr>
<tr align="center"> <tr>
<td width="40">05</td> <td>05</td>
<td width="110">02/02-2021</td> <td>02/02-2021</td>
<td width="20">L01</td> <td>L01</td>
<td width="200">Intro</td> <td>Intro</td>
<td width="90"></td> <td></td>
<td width="65">CEF</td> <td>CEF</td>
<td width="150"></td> <td></td>
</tr><tr align="center"> </tr>
<td width="40">06</td> <tr>
<td width="110">09/02-2021</td> <td>06</td>
<td width="20">L02</td> <td>09/02-2021</td>
<td width="200">Klassifikation</td> <td>L02</td>
<td width="90"></td> <td>Klassifikation</td>
<td width="65">CEF</td> <td></td>
<td width="150"></td> <td>CEF</td>
</tr><tr align="center"> <td></td>
<td width="40">07</td> </tr>
<td width="110">16/02-2021</td> <tr>
<td width="20">L03</td> <td>07</td>
<td width="200">End-to-end ML</td> <td>16/02-2021</td>
<td width="90"></td> <td>L03</td>
<td width="65">CEF</td> <td>End-to-end ML</td>
<td width="150"></td> <td></td>
</tr><tr align="center"> <td>CEF</td>
<td width="40">08</td> <td></td>
<td width="110">23/02-2021</td> </tr>
<td width="20">L04</td> <tr>
<td width="200">Regression</td> <td>08</td>
<td width="90">O1 (28/02)</td> <td>23/02-2021</td>
<td width="65">PAH</td> <td>L04</td>
<td width="150"></td> <td>Regression</td>
</tr><tr align="center"> <td>O1 (28/02)</td>
<td width="40">09</td> <td>PAH</td>
<td width="110">02/03-2021</td> <td></td>
<td width="20">L05</td> </tr>
<td width="200">Data analyse</td> <tr>
<td width="90"></td> <td>09</td>
<td width="65">PAH</td> <td>02/03-2021</td>
<td width="150"></td> <td>L05</td>
</tr><tr align="center"> <td>Data analyse</td>
<td width="40">10</td> <td></td>
<td width="110">09/03-2021</td> <td>PAH</td>
<td width="20">L06</td> <td></td>
<td width="200">Neurale netværk (NN)</td> </tr>
<td width="90"></td> <tr>
<td width="65">PAH</td> <td>10</td>
<td width="150"></td> <td>09/03-2021</td>
</tr><tr align="center"> <td>L06</td>
<td width="40">11</td> <td>Neurale netværk (NN)</td>
<td width="110">16/03-2021</td> <td></td>
<td width="20">L07</td> <td>PAH</td>
<td width="200">Træning og generalisering</td> <td></td>
<td width="90">O2 (17/03)</td> </tr>
<td width="65">CEF</td> <tr>
<td width="150"></td> <td>11</td>
</tr><tr align="center"> <td>16/03-2021</td>
<td width="40">12</td> <td>L07</td>
<td width="110">23/03-2021</td> <td>Træning og generalisering</td>
<td width="20">L08</td> <td>O2 (17/03)</td>
<td width="200">Regularisering og søgning</td> <td>CEF</td>
<td width="90"></td> <td></td>
<td width="65">CEF</td> </tr>
<td width="150"></td> <tr>
</tr><tr align="center"> <td>12</td>
<td width="40">13</td> <td>23/03-2021</td>
<td width="110">30/03-2021</td> <td>L08</td>
<td width="20"></td> <td>Regularisering og søgning</td>
<td width="200"></td> <td></td>
<td width="90"></td> <td>CEF</td>
<td width="65"></td> <td></td>
<td width="150">Påske (ingen undervisning)</td> </tr>
</tr><tr align="center"> <tr>
<td width="40">14</td> <td>13</td>
<td width="110">06/04-2021</td> <td>30/03-2021</td>
<td width="20">L09</td> <td></td>
<td width="200">Deep learning (CNN)</td> <td></td>
<td width="90"></td> <td></td>
<td width="65">CEF</td> <td></td>
<td width="150"></td> <td>Påske (ingen undervisning)</td>
</tr><tr align="center"> </tr>
<td width="40">15</td> <tr>
<td width="110">13/04-2021</td> <td>14</td>
<td width="20">L10</td> <td>06/04-2021</td>
<td width="200">Probabilistiske modeller</td> <td>L09</td>
<td width="90">O3 (14/04)</td> <td>Deep learning (CNN)</td>
<td width="65">PAH</td> <td></td>