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| author | schneefux <schneefux+commit@schneefux.xyz> | 2016-04-10 15:23:14 +0200 |
|---|---|---|
| committer | schneefux <schneefux+commit@schneefux.xyz> | 2016-04-10 15:23:14 +0200 |
| commit | 5674b4f788b88c0d69c48b78eab6abf1b2ccb8ff (patch) | |
| tree | 03d9ed7a9f4c9e7fa1560ad1362a0f7a6626c589 /index.html | |
| parent | b8a00780d8949d5211e982a41962f3b0549b5113 (diff) | |
| download | vortrag-knn-5674b4f788b88c0d69c48b78eab6abf1b2ccb8ff.tar.gz vortrag-knn-5674b4f788b88c0d69c48b78eab6abf1b2ccb8ff.zip | |
add sources; layout
Diffstat (limited to 'index.html')
| -rw-r--r-- | index.html | 41 |
1 files changed, 36 insertions, 5 deletions
@@ -80,7 +80,7 @@ winH = window.innerHeight, picW = me.node().naturalWidth, picH = me.node().naturalHeight, - ratioH = 0.7*extraRatio, ratioW = 0.7; + ratioH = 0.7*extraRatio, ratioW = 0.8; if ((winW*ratioW)/picW > (winH*ratioH)/picH) { me.style("height", winH*ratioH + "px"); me.style("width", "auto"); @@ -90,7 +90,7 @@ } }; d3.selectAll(".scalepic").each(scalePicture); - d3.selectAll(".scalepic-half").each(function(d, i) { scalePicture(d, i, this, 0.45); }); + d3.selectAll(".scalepic-half").each(function(d, i) { scalePicture(d, i, this, 0.5); }); }; window.addEventListener("resize", sizeSlides); @@ -180,7 +180,7 @@ <div class="innerStep center"> <h3>Neuronales Netz – künstliches neuronales Netz</h3> <img class="scalepic-half" src="img/neuronales-netz.jpg" alt="Foto Neuron" /> - <img class="scalepic-half" src="img/kuenstliches_neuronales_netz.png" alt="Mehrschichtiges Perzeptron" /> + <img class="scalepic-half" src="img/kuenstliches_neuronales_netz.svg" alt="Mehrschichtiges Perzeptron" /> </div> </div> @@ -289,7 +289,7 @@ <div id="boston-bias" class="step slide" data-x="3000" data-y="3000" data-z="0"> <h3>(Eine geht noch.)</h3> <p style="text-align: center; font-size: 140%;"> - Berechneter MEDV-Wert: <span class="calculated">lade…</span> - Erwarteter MEDV-Wert: <span class="expected">lade…</span> + Berechneter MEDV-Wert: <span class="calculated">lade…</span> - Erwarteter MEDV-Wert: <span class="expected">lade…</span> <button class="mdl-button mdl-js-button btn-calc"><i class="material-icons">redo</i></button> </p> <div class="visContainer"></div> @@ -435,7 +435,38 @@ </div> <div id="sources" class="step slide" data-x="7000" data-y="0" data-z="1000"> - <h3>Quellen, Lizenzen & mehr</h3> + <h3 class="emoji">Quellen und Lizenzen :bookmark_tabs:</h3> + <div class="sources-list"> + <p>Quellen</p> + <ul> + <li>Roman V. Belavkin – Lecture 11: Feed-Forward Neural Networks</li> + <li>Carlos Gershenson – Artificial Neural Networks for beginners</li> + <li>Carsten Könneker und Uwe Reichert – Lexikon der Biologie: Effektorzellen, Rezeptorzellen, Neuron</li> + </ul> + <p>Daten</p> + <ul> + <li>Harrison, D. and Rubinfeld, D.L. – Housing Data Set (gemeinfrei)</li> + <li>Timo H. – Gewichte des neuronalen Netzes zur Lösung des Problems der Boston-Datenreihe (CC-0)</li> + </ul> + <p>Grafiken</p> + <ul> + <li>MethoxyRoxy – Pyramidal hippocampal neuron (CC-BY-SA 2.5)</li> + <li>SEER, US National Cancer Institute, Dhp1080, Unbekannt – Neuron, sprachneutral (CC BY-SA 3.0)</li> + <li>Chrislb – Schema eines künstlichen Neurons (CC-BY-SA 3.0)</li> + <li>Sky99 – Struktur eines klassischen Multi-Layer-Perzeptrons (CC-BY-SA 3.0)</li> + <li>EmojiOne – EmojiOne (CC-BY 4.0)</li> + <li>Google – Material Design Icons (CC-BY 4.0)</li> + <li>Timo H. – Diagramme und Präsentationslayout (CC-BY-SA 4.0)</li> + </ul> + <p>Bibliotheken</p> + <ul> + <li>Bartek Szopka und Mitwirkende – impress.js (MIT)</li> + <li>Google – Material Design Lite (Apache 2)</li> + <li>Michael Bostock – D3.js (New BSD)</li> + <li>MathJax-Vereinigung – MathJax (Apache 2)</li> + <li>Timo H. – Programmcode der Präsentation (GPL 3)</li> + </ul> + </div> </div> <div id="thanx" class="step slide" data-x="7000" data-y="1000" data-z="1000"> |
