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cpge-itc · Nov 18, 2023 · 9e9481f · 9e9481f
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diff --git a/_sources/dl/algo/prog_dyn/cours/prog_dyn.ipynb b/_sources/dl/algo/prog_dyn/cours/prog_dyn.ipynb
@@ -6,6 +6,7 @@
    "source": [
     "# Programmation dynamique\n",
     "\n",
+    "<iframe src=https://mozilla.github.io/pdf.js/web/viewer.html?file=https://raw.githubusercontent.com/fortierq/cours/main/algo/prog_dyn/cours/prog_dyn.pdf#zoom=page-fit&pagemode=none height=500 width=100% allowfullscreen></iframe>\n",
     "<iframe src=https://mozilla.github.io/pdf.js/web/viewer.html?file=https://raw.githubusercontent.com/fortierq/cours/main/algo/prog_dyn/cours/prog_dyn.pdf#zoom=page-fit&pagemode=none height=500 width=100% allowfullscreen></iframe><iframe src=https://mozilla.github.io/pdf.js/web/viewer.html?file=https://raw.githubusercontent.com/fortierq/cours/main/algo/prog_dyn/cours/prog_dyn.pdf#zoom=page-fit&pagemode=none height=500 width=100% allowfullscreen></iframe>"
    ]
   },

diff --git a/_sources/dl/apprentissage/cours/knn/knn.ipynb b/_sources/dl/apprentissage/cours/knn/knn.ipynb
@@ -7,6 +7,7 @@
    "source": [
     "# Cours : Algorithme des k plus proches voisins\n",
     "\n",
+    "<iframe src=https://mozilla.github.io/pdf.js/web/viewer.html?file=https://raw.githubusercontent.com/fortierq/cours/main/apprentissage/cours/knn/knn.pdf#zoom=page-fit&pagemode=none height=500 width=100% allowfullscreen></iframe>\n",
     "<iframe src=https://mozilla.github.io/pdf.js/web/viewer.html?file=https://raw.githubusercontent.com/fortierq/cours/main/apprentissage/cours/knn/knn.pdf#zoom=page-fit&pagemode=none height=500 width=100% allowfullscreen></iframe><iframe src=https://mozilla.github.io/pdf.js/web/viewer.html?file=https://raw.githubusercontent.com/fortierq/cours/main/apprentissage/cours/knn/knn.pdf#zoom=page-fit&pagemode=none height=500 width=100% allowfullscreen></iframe>"
    ]
   },

diff --git a/dl/algo/prog_dyn/cours/prog_dyn.html b/dl/algo/prog_dyn/cours/prog_dyn.html
@@ -633,6 +633,7 @@ <h2> Contents </h2>
 
   <section class="tex2jax_ignore mathjax_ignore" id="programmation-dynamique">
 <h1>Programmation dynamique<a class="headerlink" href="#programmation-dynamique" title="Permalink to this headline">#</a></h1>
+<iframe src=https://mozilla.github.io/pdf.js/web/viewer.html?file=https://raw.githubusercontent.com/fortierq/cours/main/algo/prog_dyn/cours/prog_dyn.pdf#zoom=page-fit&pagemode=none height=500 width=100% allowfullscreen></iframe>
 <iframe src=https://mozilla.github.io/pdf.js/web/viewer.html?file=https://raw.githubusercontent.com/fortierq/cours/main/algo/prog_dyn/cours/prog_dyn.pdf#zoom=page-fit&pagemode=none height=500 width=100% allowfullscreen></iframe><iframe src=https://mozilla.github.io/pdf.js/web/viewer.html?file=https://raw.githubusercontent.com/fortierq/cours/main/algo/prog_dyn/cours/prog_dyn.pdf#zoom=page-fit&pagemode=none height=500 width=100% allowfullscreen></iframe><div class="cell docutils container">
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 <div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="k">def</span> <span class="nf">knapsack</span><span class="p">(</span><span class="n">c</span><span class="p">,</span> <span class="n">w</span><span class="p">,</span> <span class="n">v</span><span class="p">):</span>

diff --git a/dl/apprentissage/cours/knn/knn.html b/dl/apprentissage/cours/knn/knn.html
@@ -627,6 +627,7 @@ <h2> Contents </h2>
 
   <section class="tex2jax_ignore mathjax_ignore" id="cours-algorithme-des-k-plus-proches-voisins">
 <h1>Cours : Algorithme des k plus proches voisins<a class="headerlink" href="#cours-algorithme-des-k-plus-proches-voisins" title="Permalink to this headline">#</a></h1>
+<iframe src=https://mozilla.github.io/pdf.js/web/viewer.html?file=https://raw.githubusercontent.com/fortierq/cours/main/apprentissage/cours/knn/knn.pdf#zoom=page-fit&pagemode=none height=500 width=100% allowfullscreen></iframe>
 <iframe src=https://mozilla.github.io/pdf.js/web/viewer.html?file=https://raw.githubusercontent.com/fortierq/cours/main/apprentissage/cours/knn/knn.pdf#zoom=page-fit&pagemode=none height=500 width=100% allowfullscreen></iframe><iframe src=https://mozilla.github.io/pdf.js/web/viewer.html?file=https://raw.githubusercontent.com/fortierq/cours/main/apprentissage/cours/knn/knn.pdf#zoom=page-fit&pagemode=none height=500 width=100% allowfullscreen></iframe><p>Nous allons classifier deux ensembles de points (rouge et bleu) issus de deux distributions gaussiennes (de paramètres différents), avec la méthode des <span class="math notranslate nohighlight">\(k\)</span> plus proches voisins :</p>
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