diff --git a/ch08/Topic_Modeling_Clustering.ipynb b/ch08/Topic_Modeling_Clustering.ipynb
index 0e8ef87..4aabd78 100644
--- a/ch08/Topic_Modeling_Clustering.ipynb
+++ b/ch08/Topic_Modeling_Clustering.ipynb
@@ -162,8 +162,7 @@
      "height": 527
     },
     "id": "FdsLNCg0ddwW",
-    "outputId": "c28d0aed-a2d9-418b-a4f1-74b5fada5042",
-    "scrolled": false
+    "outputId": "c28d0aed-a2d9-418b-a4f1-74b5fada5042"
    },
    "outputs": [],
    "source": [
@@ -304,8 +303,7 @@
      "base_uri": "https://localhost:8080/"
     },
     "id": "5aC7LQMHddwZ",
-    "outputId": "5981f3f3-d0f7-4458-b0c7-4eda85804eee",
-    "scrolled": false
+    "outputId": "5981f3f3-d0f7-4458-b0c7-4eda85804eee"
    },
    "outputs": [],
    "source": [
@@ -463,7 +461,7 @@
    "outputs": [],
    "source": [
     "from sklearn.decomposition import LatentDirichletAllocation\n",
-    "\n",
+    "# task runs for a while... (15min on my machine)\n",
     "lda_para_model = LatentDirichletAllocation(n_components = 10, random_state=42)\n",
     "W_lda_para_matrix = lda_para_model.fit_transform(count_para_vectors)\n",
     "H_lda_para_matrix = lda_para_model.components_"
@@ -499,9 +497,9 @@
    },
    "outputs": [],
    "source": [
-    "import pyLDAvis.sklearn\n",
+    "import pyLDAvis.lda_model\n",
     "\n",
-    "lda_display = pyLDAvis.sklearn.prepare(lda_para_model, count_para_vectors, count_para_vectorizer, sort_topics=False)\n",
+    "lda_display = pyLDAvis.lda_model.prepare(lda_para_model, count_para_vectors, count_para_vectorizer, sort_topics=False)\n",
     "pyLDAvis.display(lda_display)"
    ]
   },
@@ -513,28 +511,10 @@
    },
    "outputs": [],
    "source": [
-    "lda_tsne_display = pyLDAvis.sklearn.prepare(lda_para_model, count_para_vectors, count_para_vectorizer, sort_topics=False, mds='tsne')\n",
+    "lda_tsne_display = pyLDAvis.lda_model.prepare(lda_para_model, count_para_vectors, count_para_vectorizer, sort_topics=False, mds='tsne')\n",
     "pyLDAvis.display(lda_tsne_display)"
    ]
   },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "id": "IYHW0BxPddwd"
-   },
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "id": "naHnuA-Mddw8"
-   },
-   "outputs": [],
-   "source": []
-  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -817,6 +797,7 @@
    },
    "outputs": [],
    "source": [
+    "from numpy import triu\n",
     "from gensim.corpora import Dictionary\n",
     "\n",
     "dict_gensim_para = Dictionary(gensim_paragraphs) "
@@ -1081,8 +1062,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "id": "Zvr8KcafddxL",
-    "scrolled": false
+    "id": "Zvr8KcafddxL"
    },
    "outputs": [],
    "source": [
@@ -1115,8 +1095,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "id": "aXzMrPQTddxM",
-    "scrolled": false
+    "id": "aXzMrPQTddxM"
    },
    "outputs": [],
    "source": [
@@ -1209,8 +1188,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "id": "GB23o18CddxT",
-    "scrolled": false
+    "id": "GB23o18CddxT"
    },
    "outputs": [],
    "source": [
@@ -1292,8 +1270,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "id": "WYcY-h91ddxU",
-    "scrolled": false
+    "id": "WYcY-h91ddxU"
    },
    "outputs": [],
    "source": [
@@ -1315,7 +1292,7 @@
    "provenance": []
   },
   "kernelspec": {
-   "display_name": "Python 3 (ipykernel)",
+   "display_name": "blueprints",
    "language": "python",
    "name": "python3"
   },
@@ -1329,7 +1306,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.8.10"
+   "version": "3.12.8"
   },
   "toc": {
    "base_numbering": 1,
diff --git a/ch08/requirements.txt b/ch08/requirements.txt
index 429151f..52f8e02 100644
--- a/ch08/requirements.txt
+++ b/ch08/requirements.txt
@@ -1,2 +1,3 @@
 gensim>3.7
 pyLDAvis
+scipy<1.13
\ No newline at end of file