Upload 6 files
Browse files- .gitattributes +3 -0
- TMDB.csv +3 -0
- feature_array.npz +3 -0
- meow.ipynb +102 -0
- movie.ipynb +1674 -0
- movies_df.csv +3 -0
- my_index.ann +3 -0
.gitattributes
CHANGED
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@@ -33,3 +33,6 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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movies_df.csv filter=lfs diff=lfs merge=lfs -text
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my_index.ann filter=lfs diff=lfs merge=lfs -text
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TMDB.csv filter=lfs diff=lfs merge=lfs -text
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TMDB.csv
ADDED
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@@ -0,0 +1,3 @@
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version https://git-lfs.github.com/spec/v1
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oid sha256:cbb74d9630803fa76200511ee5fed3f23193b9ffdcb5999578f735962bcbcb57
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size 570252856
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feature_array.npz
ADDED
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@@ -0,0 +1,3 @@
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version https://git-lfs.github.com/spec/v1
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oid sha256:4211dd1420c9a800b52de53d7e82417c2fe223def70ef57b1624a024f7f9fe21
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+
size 88777756
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meow.ipynb
ADDED
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@@ -0,0 +1,102 @@
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{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 2,
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"id": "3afa097a",
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Time and Space\n",
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"A Monster From Space\n",
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"Budhayaan\n",
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"Manhunt in Space\n",
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"Journey to Space\n"
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]
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}
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],
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"source": [
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"from annoy import AnnoyIndex\n",
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"import numpy as np\n",
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"import pandas as pd\n",
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"\n",
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"# Load your movie data and feature shape\n",
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"new_movies = pd.read_csv('movies_df.csv')\n",
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"feature_array = np.load('feature_array.npz')['arr_0']\n",
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"f = feature_array.shape[1] # Feature dimension\n",
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"\n",
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"# Create Annoy index and load from file\n",
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"annoy_index = AnnoyIndex(f, 'angular')\n",
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"annoy_index.load('my_index.ann')\n",
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"\n",
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"def get_movie_title(movie_id):\n",
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" return new_movies.iloc[movie_id]['title']\n",
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"\n",
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"def recommend_fast(movie_id, top_k=5):\n",
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" idxs = annoy_index.get_nns_by_item(movie_id, top_k+1)[1:] # skip itself\n",
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" return idxs\n",
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"\n",
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"# Example: Get recommendations for any movie\n",
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"recommended_movies = recommend_fast(1)\n",
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"for mv in recommended_movies:\n",
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" print(get_movie_title(mv))\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"id": "39068f98",
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Time and Space\n",
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"A Monster From Space\n",
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"Budhayaan\n",
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"Manhunt in Space\n",
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"Journey to Space\n"
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]
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}
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],
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"source": [
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"recommended_movies = recommend_fast(1)\n",
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"for mv in recommended_movies:\n",
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" print(get_movie_title(mv))\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "f22a4417",
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"metadata": {},
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"outputs": [],
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"source": []
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.13.9"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 5
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}
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movie.ipynb
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|
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|
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|
| 217 |
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|
| 218 |
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|
| 219 |
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|
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|
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|
| 226 |
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|
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|
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|
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|
| 230 |
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|
| 231 |
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|
| 232 |
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|
| 233 |
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|
| 234 |
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|
| 235 |
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|
| 236 |
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|
| 237 |
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|
| 238 |
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|
| 239 |
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|
| 240 |
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|
| 241 |
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|
| 242 |
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| 243 |
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| 244 |
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|
| 245 |
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|
| 246 |
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|
| 247 |
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|
| 248 |
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" </tr>\n",
|
| 249 |
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" <tr>\n",
|
| 250 |
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" <th>4</th>\n",
|
| 251 |
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" <td>24428</td>\n",
|
| 252 |
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|
| 253 |
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|
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|
| 255 |
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|
| 256 |
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|
| 257 |
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|
| 258 |
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|
| 259 |
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|
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|
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|
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|
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|
| 273 |
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|
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|
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|
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|
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|
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|
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|
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|
| 286 |
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|
| 287 |
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|
| 288 |
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|
| 289 |
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|
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|
| 291 |
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|
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| 293 |
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|
| 298 |
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|
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|
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|
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|
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|
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|
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|
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|
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" id title \\\n",
|
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"0 27205 Inception \n",
|
| 334 |
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|
| 335 |
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|
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|
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|
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|
| 341 |
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|
| 342 |
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|
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|
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|
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|
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|
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| 352 |
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|
| 355 |
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|
| 356 |
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"\n",
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"1 Mankind was born on Earth. It was never meant ... \n",
|
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"... ... \n",
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|
| 382 |
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"\n",
|
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" genres \\\n",
|
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|
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|
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|
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"source": [
|
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"movies = movies[[\"id\",\"title\",\"overview\",\"poster_path\",\"backdrop_path\",\"tagline\",\"genres\",\"keywords\"]]\n",
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| 420 |
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|
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|
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|
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| 577 |
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| 587 |
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| 588 |
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|
| 589 |
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|
| 590 |
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|
| 591 |
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| 592 |
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|
| 594 |
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|
| 595 |
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|
| 596 |
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| 597 |
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|
| 598 |
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| 599 |
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|
| 600 |
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| 601 |
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| 602 |
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| 604 |
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| 605 |
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|
| 607 |
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| 608 |
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| 624 |
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"0 27205 Inception \n",
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| 871 |
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" <td>Enter the world of Pandora.</td>\n",
|
| 872 |
+
" <td>Action, Adventure, Fantasy, Science Fiction</td>\n",
|
| 873 |
+
" <td>future, society, culture clash, space travel, ...</td>\n",
|
| 874 |
+
" </tr>\n",
|
| 875 |
+
" <tr>\n",
|
| 876 |
+
" <th>4</th>\n",
|
| 877 |
+
" <td>24428</td>\n",
|
| 878 |
+
" <td>The Avengers</td>\n",
|
| 879 |
+
" <td>When,an,unexpected,enemy,emerges,and,threatens...</td>\n",
|
| 880 |
+
" <td>/RYMX2wcKCBAr24UyPD7xwmjaTn.jpg</td>\n",
|
| 881 |
+
" <td>Some assembly required.</td>\n",
|
| 882 |
+
" <td>Science Fiction, Action, Adventure</td>\n",
|
| 883 |
+
" <td>new york city, superhero, shield, based on com...</td>\n",
|
| 884 |
+
" </tr>\n",
|
| 885 |
+
" <tr>\n",
|
| 886 |
+
" <th>...</th>\n",
|
| 887 |
+
" <td>...</td>\n",
|
| 888 |
+
" <td>...</td>\n",
|
| 889 |
+
" <td>...</td>\n",
|
| 890 |
+
" <td>...</td>\n",
|
| 891 |
+
" <td>...</td>\n",
|
| 892 |
+
" <td>...</td>\n",
|
| 893 |
+
" <td>...</td>\n",
|
| 894 |
+
" </tr>\n",
|
| 895 |
+
" <tr>\n",
|
| 896 |
+
" <th>1266856</th>\n",
|
| 897 |
+
" <td>796650</td>\n",
|
| 898 |
+
" <td>Survival of a Dragon</td>\n",
|
| 899 |
+
" <td>A,warrior,is,transported,1000,years,into,the,p...</td>\n",
|
| 900 |
+
" <td>/qX69cmtnyc9EfE3WN2UF3UI5Ta8.jpg</td>\n",
|
| 901 |
+
" <td></td>\n",
|
| 902 |
+
" <td>Adventure, Action, Fantasy</td>\n",
|
| 903 |
+
" <td>time travel</td>\n",
|
| 904 |
+
" </tr>\n",
|
| 905 |
+
" <tr>\n",
|
| 906 |
+
" <th>1266857</th>\n",
|
| 907 |
+
" <td>796651</td>\n",
|
| 908 |
+
" <td>A Model for the Motion of a Spring</td>\n",
|
| 909 |
+
" <td>The,utilization,of,numerical,oscillation,model...</td>\n",
|
| 910 |
+
" <td>/3s2vSewmxpdnzrWwPamkBbAM7mo.jpg</td>\n",
|
| 911 |
+
" <td></td>\n",
|
| 912 |
+
" <td>Fantasy</td>\n",
|
| 913 |
+
" <td></td>\n",
|
| 914 |
+
" </tr>\n",
|
| 915 |
+
" <tr>\n",
|
| 916 |
+
" <th>1266862</th>\n",
|
| 917 |
+
" <td>796657</td>\n",
|
| 918 |
+
" <td>Car Crash: Who's Lying?</td>\n",
|
| 919 |
+
" <td>Documentary,exploring,the,aftermath,of,a,car,c...</td>\n",
|
| 920 |
+
" <td>/yatOGyk6OZKtfZQlRIBnHYwfSHD.jpg</td>\n",
|
| 921 |
+
" <td></td>\n",
|
| 922 |
+
" <td>Documentary</td>\n",
|
| 923 |
+
" <td></td>\n",
|
| 924 |
+
" </tr>\n",
|
| 925 |
+
" <tr>\n",
|
| 926 |
+
" <th>1266863</th>\n",
|
| 927 |
+
" <td>796658</td>\n",
|
| 928 |
+
" <td>Cowboy</td>\n",
|
| 929 |
+
" <td>Having,grown,up,in,a,home,with,an,abusive,fath...</td>\n",
|
| 930 |
+
" <td>/fhPUn11H9wU0cGWLpo6WMcMXb9a.jpg</td>\n",
|
| 931 |
+
" <td></td>\n",
|
| 932 |
+
" <td>Documentary, Animation</td>\n",
|
| 933 |
+
" <td></td>\n",
|
| 934 |
+
" </tr>\n",
|
| 935 |
+
" <tr>\n",
|
| 936 |
+
" <th>1266864</th>\n",
|
| 937 |
+
" <td>1525030</td>\n",
|
| 938 |
+
" <td>Detective Kibbles: Part 2 | Remastered</td>\n",
|
| 939 |
+
" <td>After,a,brutal,attack,in,his,own,home,Detectiv...</td>\n",
|
| 940 |
+
" <td>/74SKZslJiJrO1nK4LnFa7ztesxZ.jpg</td>\n",
|
| 941 |
+
" <td>Every hero must have an end.</td>\n",
|
| 942 |
+
" <td>Crime, Comedy, Drama</td>\n",
|
| 943 |
+
" <td>police, detective, drama, kibbles</td>\n",
|
| 944 |
+
" </tr>\n",
|
| 945 |
+
" </tbody>\n",
|
| 946 |
+
"</table>\n",
|
| 947 |
+
"<p>991491 rows × 7 columns</p>\n",
|
| 948 |
+
"</div>"
|
| 949 |
+
],
|
| 950 |
+
"text/plain": [
|
| 951 |
+
" id title \\\n",
|
| 952 |
+
"0 27205 Inception \n",
|
| 953 |
+
"1 157336 Interstellar \n",
|
| 954 |
+
"2 155 The Dark Knight \n",
|
| 955 |
+
"3 19995 Avatar \n",
|
| 956 |
+
"4 24428 The Avengers \n",
|
| 957 |
+
"... ... ... \n",
|
| 958 |
+
"1266856 796650 Survival of a Dragon \n",
|
| 959 |
+
"1266857 796651 A Model for the Motion of a Spring \n",
|
| 960 |
+
"1266862 796657 Car Crash: Who's Lying? \n",
|
| 961 |
+
"1266863 796658 Cowboy \n",
|
| 962 |
+
"1266864 1525030 Detective Kibbles: Part 2 | Remastered \n",
|
| 963 |
+
"\n",
|
| 964 |
+
" overview \\\n",
|
| 965 |
+
"0 Cobb,a,skilled,thief,who,commits,corporate,esp... \n",
|
| 966 |
+
"1 The,adventures,of,a,group,of,explorers,who,mak... \n",
|
| 967 |
+
"2 Batman,raises,the,stakes,in,his,war,on,crime,W... \n",
|
| 968 |
+
"3 In,the,22nd,century,a,paraplegic,Marine,is,dis... \n",
|
| 969 |
+
"4 When,an,unexpected,enemy,emerges,and,threatens... \n",
|
| 970 |
+
"... ... \n",
|
| 971 |
+
"1266856 A,warrior,is,transported,1000,years,into,the,p... \n",
|
| 972 |
+
"1266857 The,utilization,of,numerical,oscillation,model... \n",
|
| 973 |
+
"1266862 Documentary,exploring,the,aftermath,of,a,car,c... \n",
|
| 974 |
+
"1266863 Having,grown,up,in,a,home,with,an,abusive,fath... \n",
|
| 975 |
+
"1266864 After,a,brutal,attack,in,his,own,home,Detectiv... \n",
|
| 976 |
+
"\n",
|
| 977 |
+
" poster_path \\\n",
|
| 978 |
+
"0 /oYuLEt3zVCKq57qu2F8dT7NIa6f.jpg \n",
|
| 979 |
+
"1 /gEU2QniE6E77NI6lCU6MxlNBvIx.jpg \n",
|
| 980 |
+
"2 /qJ2tW6WMUDux911r6m7haRef0WH.jpg \n",
|
| 981 |
+
"3 /kyeqWdyUXW608qlYkRqosgbbJyK.jpg \n",
|
| 982 |
+
"4 /RYMX2wcKCBAr24UyPD7xwmjaTn.jpg \n",
|
| 983 |
+
"... ... \n",
|
| 984 |
+
"1266856 /qX69cmtnyc9EfE3WN2UF3UI5Ta8.jpg \n",
|
| 985 |
+
"1266857 /3s2vSewmxpdnzrWwPamkBbAM7mo.jpg \n",
|
| 986 |
+
"1266862 /yatOGyk6OZKtfZQlRIBnHYwfSHD.jpg \n",
|
| 987 |
+
"1266863 /fhPUn11H9wU0cGWLpo6WMcMXb9a.jpg \n",
|
| 988 |
+
"1266864 /74SKZslJiJrO1nK4LnFa7ztesxZ.jpg \n",
|
| 989 |
+
"\n",
|
| 990 |
+
" tagline \\\n",
|
| 991 |
+
"0 Your mind is the scene of the crime. \n",
|
| 992 |
+
"1 Mankind was born on Earth. It was never meant ... \n",
|
| 993 |
+
"2 Welcome to a world without rules. \n",
|
| 994 |
+
"3 Enter the world of Pandora. \n",
|
| 995 |
+
"4 Some assembly required. \n",
|
| 996 |
+
"... ... \n",
|
| 997 |
+
"1266856 \n",
|
| 998 |
+
"1266857 \n",
|
| 999 |
+
"1266862 \n",
|
| 1000 |
+
"1266863 \n",
|
| 1001 |
+
"1266864 Every hero must have an end. \n",
|
| 1002 |
+
"\n",
|
| 1003 |
+
" genres \\\n",
|
| 1004 |
+
"0 Action, Science Fiction, Adventure \n",
|
| 1005 |
+
"1 Adventure, Drama, Science Fiction \n",
|
| 1006 |
+
"2 Drama, Action, Crime, Thriller \n",
|
| 1007 |
+
"3 Action, Adventure, Fantasy, Science Fiction \n",
|
| 1008 |
+
"4 Science Fiction, Action, Adventure \n",
|
| 1009 |
+
"... ... \n",
|
| 1010 |
+
"1266856 Adventure, Action, Fantasy \n",
|
| 1011 |
+
"1266857 Fantasy \n",
|
| 1012 |
+
"1266862 Documentary \n",
|
| 1013 |
+
"1266863 Documentary, Animation \n",
|
| 1014 |
+
"1266864 Crime, Comedy, Drama \n",
|
| 1015 |
+
"\n",
|
| 1016 |
+
" keywords \n",
|
| 1017 |
+
"0 rescue, mission, dream, airplane, paris, franc... \n",
|
| 1018 |
+
"1 rescue, future, spacecraft, race against time,... \n",
|
| 1019 |
+
"2 joker, sadism, chaos, secret identity, crime f... \n",
|
| 1020 |
+
"3 future, society, culture clash, space travel, ... \n",
|
| 1021 |
+
"4 new york city, superhero, shield, based on com... \n",
|
| 1022 |
+
"... ... \n",
|
| 1023 |
+
"1266856 time travel \n",
|
| 1024 |
+
"1266857 \n",
|
| 1025 |
+
"1266862 \n",
|
| 1026 |
+
"1266863 \n",
|
| 1027 |
+
"1266864 police, detective, drama, kibbles \n",
|
| 1028 |
+
"\n",
|
| 1029 |
+
"[991491 rows x 7 columns]"
|
| 1030 |
+
]
|
| 1031 |
+
},
|
| 1032 |
+
"execution_count": 12,
|
| 1033 |
+
"metadata": {},
|
| 1034 |
+
"output_type": "execute_result"
|
| 1035 |
+
}
|
| 1036 |
+
],
|
| 1037 |
+
"source": [
|
| 1038 |
+
"movies"
|
| 1039 |
+
]
|
| 1040 |
+
},
|
| 1041 |
+
{
|
| 1042 |
+
"cell_type": "code",
|
| 1043 |
+
"execution_count": 13,
|
| 1044 |
+
"id": "d68c1ec7",
|
| 1045 |
+
"metadata": {},
|
| 1046 |
+
"outputs": [
|
| 1047 |
+
{
|
| 1048 |
+
"name": "stderr",
|
| 1049 |
+
"output_type": "stream",
|
| 1050 |
+
"text": [
|
| 1051 |
+
"C:\\Users\\unkno\\AppData\\Local\\Temp\\ipykernel_5356\\3940781081.py:1: SettingWithCopyWarning: \n",
|
| 1052 |
+
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
|
| 1053 |
+
"Try using .loc[row_indexer,col_indexer] = value instead\n",
|
| 1054 |
+
"\n",
|
| 1055 |
+
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
|
| 1056 |
+
" movies['encode_list'] = (\n"
|
| 1057 |
+
]
|
| 1058 |
+
}
|
| 1059 |
+
],
|
| 1060 |
+
"source": [
|
| 1061 |
+
"movies['encode_list'] = (\n",
|
| 1062 |
+
" movies['overview'].fillna('') + \" \" +\n",
|
| 1063 |
+
" movies['genres'].fillna('') + \" \" +\n",
|
| 1064 |
+
" movies['keywords'].fillna('')\n",
|
| 1065 |
+
")\n"
|
| 1066 |
+
]
|
| 1067 |
+
},
|
| 1068 |
+
{
|
| 1069 |
+
"cell_type": "code",
|
| 1070 |
+
"execution_count": 14,
|
| 1071 |
+
"id": "fa8d3290",
|
| 1072 |
+
"metadata": {},
|
| 1073 |
+
"outputs": [
|
| 1074 |
+
{
|
| 1075 |
+
"data": {
|
| 1076 |
+
"text/plain": [
|
| 1077 |
+
"0 Cobb,a,skilled,thief,who,commits,corporate,esp...\n",
|
| 1078 |
+
"1 The,adventures,of,a,group,of,explorers,who,mak...\n",
|
| 1079 |
+
"2 Batman,raises,the,stakes,in,his,war,on,crime,W...\n",
|
| 1080 |
+
"3 In,the,22nd,century,a,paraplegic,Marine,is,dis...\n",
|
| 1081 |
+
"4 When,an,unexpected,enemy,emerges,and,threatens...\n",
|
| 1082 |
+
" ... \n",
|
| 1083 |
+
"1266856 A,warrior,is,transported,1000,years,into,the,p...\n",
|
| 1084 |
+
"1266857 The,utilization,of,numerical,oscillation,model...\n",
|
| 1085 |
+
"1266862 Documentary,exploring,the,aftermath,of,a,car,c...\n",
|
| 1086 |
+
"1266863 Having,grown,up,in,a,home,with,an,abusive,fath...\n",
|
| 1087 |
+
"1266864 After,a,brutal,attack,in,his,own,home,Detectiv...\n",
|
| 1088 |
+
"Name: encode_list, Length: 991491, dtype: object"
|
| 1089 |
+
]
|
| 1090 |
+
},
|
| 1091 |
+
"execution_count": 14,
|
| 1092 |
+
"metadata": {},
|
| 1093 |
+
"output_type": "execute_result"
|
| 1094 |
+
}
|
| 1095 |
+
],
|
| 1096 |
+
"source": [
|
| 1097 |
+
"movies['encode_list']"
|
| 1098 |
+
]
|
| 1099 |
+
},
|
| 1100 |
+
{
|
| 1101 |
+
"cell_type": "code",
|
| 1102 |
+
"execution_count": 15,
|
| 1103 |
+
"id": "3c2cc44f",
|
| 1104 |
+
"metadata": {},
|
| 1105 |
+
"outputs": [
|
| 1106 |
+
{
|
| 1107 |
+
"data": {
|
| 1108 |
+
"text/plain": [
|
| 1109 |
+
"0 Cobb,a,skilled,thief,who,commits,corporate,esp...\n",
|
| 1110 |
+
"Name: encode_list, dtype: object"
|
| 1111 |
+
]
|
| 1112 |
+
},
|
| 1113 |
+
"execution_count": 15,
|
| 1114 |
+
"metadata": {},
|
| 1115 |
+
"output_type": "execute_result"
|
| 1116 |
+
}
|
| 1117 |
+
],
|
| 1118 |
+
"source": [
|
| 1119 |
+
"movies['encode_list'].head(1)"
|
| 1120 |
+
]
|
| 1121 |
+
},
|
| 1122 |
+
{
|
| 1123 |
+
"cell_type": "code",
|
| 1124 |
+
"execution_count": 16,
|
| 1125 |
+
"id": "5685e307",
|
| 1126 |
+
"metadata": {},
|
| 1127 |
+
"outputs": [
|
| 1128 |
+
{
|
| 1129 |
+
"name": "stdout",
|
| 1130 |
+
"output_type": "stream",
|
| 1131 |
+
"text": [
|
| 1132 |
+
"Defaulting to user installation because normal site-packages is not writeable\n",
|
| 1133 |
+
"Requirement already satisfied: nltk in c:\\users\\unkno\\appdata\\local\\packages\\pythonsoftwarefoundation.python.3.13_qbz5n2kfra8p0\\localcache\\local-packages\\python313\\site-packages (3.9.1)\n",
|
| 1134 |
+
"Requirement already satisfied: click in c:\\users\\unkno\\appdata\\local\\packages\\pythonsoftwarefoundation.python.3.13_qbz5n2kfra8p0\\localcache\\local-packages\\python313\\site-packages (from nltk) (8.3.0)\n",
|
| 1135 |
+
"Requirement already satisfied: joblib in c:\\users\\unkno\\appdata\\local\\packages\\pythonsoftwarefoundation.python.3.13_qbz5n2kfra8p0\\localcache\\local-packages\\python313\\site-packages (from nltk) (1.5.2)\n",
|
| 1136 |
+
"Requirement already satisfied: regex>=2021.8.3 in c:\\users\\unkno\\appdata\\local\\packages\\pythonsoftwarefoundation.python.3.13_qbz5n2kfra8p0\\localcache\\local-packages\\python313\\site-packages (from nltk) (2024.11.6)\n",
|
| 1137 |
+
"Requirement already satisfied: tqdm in c:\\users\\unkno\\appdata\\local\\packages\\pythonsoftwarefoundation.python.3.13_qbz5n2kfra8p0\\localcache\\local-packages\\python313\\site-packages (from nltk) (4.67.1)\n",
|
| 1138 |
+
"Requirement already satisfied: colorama in c:\\users\\unkno\\appdata\\local\\packages\\pythonsoftwarefoundation.python.3.13_qbz5n2kfra8p0\\localcache\\local-packages\\python313\\site-packages (from click->nltk) (0.4.6)\n"
|
| 1139 |
+
]
|
| 1140 |
+
},
|
| 1141 |
+
{
|
| 1142 |
+
"name": "stderr",
|
| 1143 |
+
"output_type": "stream",
|
| 1144 |
+
"text": [
|
| 1145 |
+
"\n",
|
| 1146 |
+
"[notice] A new release of pip is available: 25.0.1 -> 25.2\n",
|
| 1147 |
+
"[notice] To update, run: C:\\Users\\unkno\\AppData\\Local\\Microsoft\\WindowsApps\\PythonSoftwareFoundation.Python.3.13_qbz5n2kfra8p0\\python.exe -m pip install --upgrade pip\n"
|
| 1148 |
+
]
|
| 1149 |
+
}
|
| 1150 |
+
],
|
| 1151 |
+
"source": [
|
| 1152 |
+
"!pip install nltk"
|
| 1153 |
+
]
|
| 1154 |
+
},
|
| 1155 |
+
{
|
| 1156 |
+
"cell_type": "code",
|
| 1157 |
+
"execution_count": 17,
|
| 1158 |
+
"id": "e7182aa4",
|
| 1159 |
+
"metadata": {},
|
| 1160 |
+
"outputs": [
|
| 1161 |
+
{
|
| 1162 |
+
"name": "stderr",
|
| 1163 |
+
"output_type": "stream",
|
| 1164 |
+
"text": [
|
| 1165 |
+
"C:\\Users\\unkno\\AppData\\Local\\Temp\\ipykernel_5356\\3196361095.py:9: SettingWithCopyWarning: \n",
|
| 1166 |
+
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
|
| 1167 |
+
"Try using .loc[row_indexer,col_indexer] = value instead\n",
|
| 1168 |
+
"\n",
|
| 1169 |
+
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
|
| 1170 |
+
" movies['encode_list'] = movies['encode_list'].map(stem)\n"
|
| 1171 |
+
]
|
| 1172 |
+
}
|
| 1173 |
+
],
|
| 1174 |
+
"source": [
|
| 1175 |
+
"from nltk.stem.porter import PorterStemmer\n",
|
| 1176 |
+
"\n",
|
| 1177 |
+
"ps = PorterStemmer()\n",
|
| 1178 |
+
"\n",
|
| 1179 |
+
"def stem(text):\n",
|
| 1180 |
+
" return \" \".join(ps.stem(word) for word in text.split(\",\"))\n",
|
| 1181 |
+
" \n",
|
| 1182 |
+
"# Use 'map' instead of 'apply' for faster operation\n",
|
| 1183 |
+
"movies['encode_list'] = movies['encode_list'].map(stem)"
|
| 1184 |
+
]
|
| 1185 |
+
},
|
| 1186 |
+
{
|
| 1187 |
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"cell_type": "code",
|
| 1188 |
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"execution_count": 18,
|
| 1189 |
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"id": "eeca71ce",
|
| 1190 |
+
"metadata": {},
|
| 1191 |
+
"outputs": [],
|
| 1192 |
+
"source": [
|
| 1193 |
+
"new_movies = movies[['id', 'title', 'poster_path', 'encode_list']]"
|
| 1194 |
+
]
|
| 1195 |
+
},
|
| 1196 |
+
{
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| 1197 |
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"cell_type": "code",
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| 1198 |
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"execution_count": 19,
|
| 1199 |
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"id": "82157fde",
|
| 1200 |
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"metadata": {},
|
| 1201 |
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|
| 1202 |
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{
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| 1203 |
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"data": {
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"text/html": [
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|
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" <tr style=\"text-align: right;\">\n",
|
| 1222 |
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" <th></th>\n",
|
| 1223 |
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" <th>id</th>\n",
|
| 1224 |
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" <th>title</th>\n",
|
| 1225 |
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" <th>poster_path</th>\n",
|
| 1226 |
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" <th>encode_list</th>\n",
|
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" </tr>\n",
|
| 1228 |
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" </thead>\n",
|
| 1229 |
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|
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" <tr>\n",
|
| 1231 |
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" <th>0</th>\n",
|
| 1232 |
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" <td>27205</td>\n",
|
| 1233 |
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" <td>Inception</td>\n",
|
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" <td>/oYuLEt3zVCKq57qu2F8dT7NIa6f.jpg</td>\n",
|
| 1235 |
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" <td>cobb a skill thief who commit corpor espionag ...</td>\n",
|
| 1236 |
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" </tr>\n",
|
| 1237 |
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" <tr>\n",
|
| 1238 |
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" <th>1</th>\n",
|
| 1239 |
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|
| 1240 |
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" <td>Interstellar</td>\n",
|
| 1241 |
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" <td>/gEU2QniE6E77NI6lCU6MxlNBvIx.jpg</td>\n",
|
| 1242 |
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" <td>the adventur of a group of explor who make use...</td>\n",
|
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" </tr>\n",
|
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" <tr>\n",
|
| 1245 |
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|
| 1246 |
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|
| 1247 |
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" <td>The Dark Knight</td>\n",
|
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" <td>/qJ2tW6WMUDux911r6m7haRef0WH.jpg</td>\n",
|
| 1249 |
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" <td>batman rais the stake in hi war on crime with ...</td>\n",
|
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|
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|
| 1252 |
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|
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|
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|
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|
| 1256 |
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" <td>in the 22nd centuri a parapleg marin is dispat...</td>\n",
|
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|
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|
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|
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" <td>The Avengers</td>\n",
|
| 1262 |
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" <td>/RYMX2wcKCBAr24UyPD7xwmjaTn.jpg</td>\n",
|
| 1263 |
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" <td>when an unexpect enemi emerg and threaten glob...</td>\n",
|
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" </tr>\n",
|
| 1265 |
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" </tbody>\n",
|
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|
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|
| 1268 |
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|
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|
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|
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|
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|
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|
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|
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"\n",
|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
| 1288 |
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}
|
| 1289 |
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],
|
| 1290 |
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|
| 1291 |
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|
| 1292 |
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]
|
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},
|
| 1294 |
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{
|
| 1295 |
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|
| 1297 |
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"id": "e15ed18b",
|
| 1298 |
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|
| 1299 |
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"outputs": [
|
| 1300 |
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{
|
| 1301 |
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"name": "stdout",
|
| 1302 |
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"output_type": "stream",
|
| 1303 |
+
"text": [
|
| 1304 |
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"Defaulting to user installation because normal site-packages is not writeable\n",
|
| 1305 |
+
"Requirement already satisfied: scikit-learn in c:\\users\\unkno\\appdata\\local\\packages\\pythonsoftwarefoundation.python.3.13_qbz5n2kfra8p0\\localcache\\local-packages\\python313\\site-packages (1.7.2)\n",
|
| 1306 |
+
"Requirement already satisfied: numpy>=1.22.0 in c:\\users\\unkno\\appdata\\local\\packages\\pythonsoftwarefoundation.python.3.13_qbz5n2kfra8p0\\localcache\\local-packages\\python313\\site-packages (from scikit-learn) (2.2.4)\n",
|
| 1307 |
+
"Requirement already satisfied: scipy>=1.8.0 in c:\\users\\unkno\\appdata\\local\\packages\\pythonsoftwarefoundation.python.3.13_qbz5n2kfra8p0\\localcache\\local-packages\\python313\\site-packages (from scikit-learn) (1.16.2)\n",
|
| 1308 |
+
"Requirement already satisfied: joblib>=1.2.0 in c:\\users\\unkno\\appdata\\local\\packages\\pythonsoftwarefoundation.python.3.13_qbz5n2kfra8p0\\localcache\\local-packages\\python313\\site-packages (from scikit-learn) (1.5.2)\n",
|
| 1309 |
+
"Requirement already satisfied: threadpoolctl>=3.1.0 in c:\\users\\unkno\\appdata\\local\\packages\\pythonsoftwarefoundation.python.3.13_qbz5n2kfra8p0\\localcache\\local-packages\\python313\\site-packages (from scikit-learn) (3.6.0)\n"
|
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|
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{
|
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| 1314 |
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"output_type": "stream",
|
| 1315 |
+
"text": [
|
| 1316 |
+
"\n",
|
| 1317 |
+
"[notice] A new release of pip is available: 25.0.1 -> 25.2\n",
|
| 1318 |
+
"[notice] To update, run: C:\\Users\\unkno\\AppData\\Local\\Microsoft\\WindowsApps\\PythonSoftwareFoundation.Python.3.13_qbz5n2kfra8p0\\python.exe -m pip install --upgrade pip\n"
|
| 1319 |
+
]
|
| 1320 |
+
}
|
| 1321 |
+
],
|
| 1322 |
+
"source": [
|
| 1323 |
+
"!pip install scikit-learn\n",
|
| 1324 |
+
"from sklearn.feature_extraction.text import TfidfVectorizer\n",
|
| 1325 |
+
"vectorizer = TfidfVectorizer(max_features=1000, stop_words='english')\n"
|
| 1326 |
+
]
|
| 1327 |
+
},
|
| 1328 |
+
{
|
| 1329 |
+
"cell_type": "code",
|
| 1330 |
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"execution_count": 21,
|
| 1331 |
+
"id": "634f446d",
|
| 1332 |
+
"metadata": {},
|
| 1333 |
+
"outputs": [],
|
| 1334 |
+
"source": [
|
| 1335 |
+
"features = vectorizer.fit_transform(new_movies['encode_list']).toarray()"
|
| 1336 |
+
]
|
| 1337 |
+
},
|
| 1338 |
+
{
|
| 1339 |
+
"cell_type": "code",
|
| 1340 |
+
"execution_count": 22,
|
| 1341 |
+
"id": "d1f0fdac",
|
| 1342 |
+
"metadata": {},
|
| 1343 |
+
"outputs": [
|
| 1344 |
+
{
|
| 1345 |
+
"data": {
|
| 1346 |
+
"text/plain": [
|
| 1347 |
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"array([[0., 0., 0., ..., 0., 0., 0.],\n",
|
| 1348 |
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" [0., 0., 0., ..., 0., 0., 0.],\n",
|
| 1349 |
+
" [0., 0., 0., ..., 0., 0., 0.],\n",
|
| 1350 |
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" ...,\n",
|
| 1351 |
+
" [0., 0., 0., ..., 0., 0., 0.],\n",
|
| 1352 |
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" [0., 0., 0., ..., 0., 0., 0.],\n",
|
| 1353 |
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" [0., 0., 0., ..., 0., 0., 0.]], shape=(991491, 1000))"
|
| 1354 |
+
]
|
| 1355 |
+
},
|
| 1356 |
+
"execution_count": 22,
|
| 1357 |
+
"metadata": {},
|
| 1358 |
+
"output_type": "execute_result"
|
| 1359 |
+
}
|
| 1360 |
+
],
|
| 1361 |
+
"source": [
|
| 1362 |
+
"features"
|
| 1363 |
+
]
|
| 1364 |
+
},
|
| 1365 |
+
{
|
| 1366 |
+
"cell_type": "code",
|
| 1367 |
+
"execution_count": 23,
|
| 1368 |
+
"id": "1ca6a500",
|
| 1369 |
+
"metadata": {},
|
| 1370 |
+
"outputs": [],
|
| 1371 |
+
"source": [
|
| 1372 |
+
"# Skip FAISS - use sklearn only with limited data\n",
|
| 1373 |
+
"from sklearn.metrics.pairwise import cosine_similarity\n",
|
| 1374 |
+
"\n",
|
| 1375 |
+
"# Your features is already a numpy array - use it directly\n",
|
| 1376 |
+
"feature_array = features.astype('float32')\n",
|
| 1377 |
+
"\n",
|
| 1378 |
+
"def get_movie_title(movie_id):\n",
|
| 1379 |
+
" return new_movies.iloc[movie_id]['title']\n",
|
| 1380 |
+
"\n",
|
| 1381 |
+
"def recommend(movie_id, top_k=5):\n",
|
| 1382 |
+
" # Get the feature vector for the input movie\n",
|
| 1383 |
+
" movie_vector = feature_array[movie_id].reshape(1, -1)\n",
|
| 1384 |
+
" \n",
|
| 1385 |
+
" # Calculate similarity only for this movie vs all others\n",
|
| 1386 |
+
" similarity_scores = cosine_similarity(movie_vector, feature_array).flatten()\n",
|
| 1387 |
+
" \n",
|
| 1388 |
+
" # Get top similar movies (exclude the movie itself)\n",
|
| 1389 |
+
" similar_indices = similarity_scores.argsort()[-top_k-1:-1][::-1]\n",
|
| 1390 |
+
" \n",
|
| 1391 |
+
" return similar_indices\n"
|
| 1392 |
+
]
|
| 1393 |
+
},
|
| 1394 |
+
{
|
| 1395 |
+
"cell_type": "code",
|
| 1396 |
+
"execution_count": 31,
|
| 1397 |
+
"id": "c425f84f",
|
| 1398 |
+
"metadata": {},
|
| 1399 |
+
"outputs": [
|
| 1400 |
+
{
|
| 1401 |
+
"name": "stdout",
|
| 1402 |
+
"output_type": "stream",
|
| 1403 |
+
"text": [
|
| 1404 |
+
"Interstellar\n",
|
| 1405 |
+
"Time and Space\n",
|
| 1406 |
+
"A Monster From Space\n",
|
| 1407 |
+
"Budhayaan\n",
|
| 1408 |
+
"Manhunt in Space\n",
|
| 1409 |
+
"Journey to Space\n"
|
| 1410 |
+
]
|
| 1411 |
+
}
|
| 1412 |
+
],
|
| 1413 |
+
"source": [
|
| 1414 |
+
"print(get_movie_title(1))\n",
|
| 1415 |
+
"\n",
|
| 1416 |
+
"recommended_movies = recommend(1) # Get recommendations for movie at index 0\n",
|
| 1417 |
+
"for mv in recommended_movies:\n",
|
| 1418 |
+
" print(get_movie_title(mv))"
|
| 1419 |
+
]
|
| 1420 |
+
},
|
| 1421 |
+
{
|
| 1422 |
+
"cell_type": "code",
|
| 1423 |
+
"execution_count": 26,
|
| 1424 |
+
"id": "65432cd8",
|
| 1425 |
+
"metadata": {},
|
| 1426 |
+
"outputs": [],
|
| 1427 |
+
"source": [
|
| 1428 |
+
"import numpy as np\n",
|
| 1429 |
+
"import pandas as pd\n",
|
| 1430 |
+
"\n",
|
| 1431 |
+
"# Save compressed numpy array\n",
|
| 1432 |
+
"np.savez_compressed('feature_array.npz', feature_array)\n",
|
| 1433 |
+
"\n"
|
| 1434 |
+
]
|
| 1435 |
+
},
|
| 1436 |
+
{
|
| 1437 |
+
"cell_type": "code",
|
| 1438 |
+
"execution_count": 28,
|
| 1439 |
+
"id": "2139293d",
|
| 1440 |
+
"metadata": {},
|
| 1441 |
+
"outputs": [],
|
| 1442 |
+
"source": [
|
| 1443 |
+
"import pandas as pd\n",
|
| 1444 |
+
"\n",
|
| 1445 |
+
"# Remove any extension type columns\n",
|
| 1446 |
+
"safe_new_movies = new_movies.select_dtypes(include=['int64', 'float64', 'object']).copy()\n",
|
| 1447 |
+
"\n",
|
| 1448 |
+
"# Convert all columns to string as a fallback if extension issues persist\n",
|
| 1449 |
+
"for col in safe_new_movies.columns:\n",
|
| 1450 |
+
" safe_new_movies[col] = safe_new_movies[col].astype(str)\n",
|
| 1451 |
+
"\n",
|
| 1452 |
+
"safe_new_movies.reset_index(drop=True, inplace=True)\n",
|
| 1453 |
+
"\n",
|
| 1454 |
+
"# Now save as parquet\n",
|
| 1455 |
+
"safe_new_movies.to_csv('movies_df.csv', index=False)\n"
|
| 1456 |
+
]
|
| 1457 |
+
},
|
| 1458 |
+
{
|
| 1459 |
+
"cell_type": "code",
|
| 1460 |
+
"execution_count": 33,
|
| 1461 |
+
"id": "d0eb30ec",
|
| 1462 |
+
"metadata": {},
|
| 1463 |
+
"outputs": [],
|
| 1464 |
+
"source": [
|
| 1465 |
+
"import numpy as np\n",
|
| 1466 |
+
"import pandas as pd\n",
|
| 1467 |
+
"from sklearn.metrics.pairwise import cosine_similarity\n",
|
| 1468 |
+
"\n",
|
| 1469 |
+
"# Load compressed numpy feature array and movie data\n",
|
| 1470 |
+
"feature_array = np.load('feature_array.npz')['arr_0']\n",
|
| 1471 |
+
"new_movies = pd.read_csv('movies_df.csv')\n",
|
| 1472 |
+
"\n",
|
| 1473 |
+
"def get_movie_title(movie_id):\n",
|
| 1474 |
+
" return new_movies.iloc[movie_id]['title']\n",
|
| 1475 |
+
"\n",
|
| 1476 |
+
"def recommend(movie_id, top_k=5):\n",
|
| 1477 |
+
" movie_vector = feature_array[movie_id].reshape(1, -1)\n",
|
| 1478 |
+
" similarity_scores = cosine_similarity(movie_vector, feature_array).flatten()\n",
|
| 1479 |
+
" similar_indices = similarity_scores.argsort()[-top_k-1:-1][::-1] # Exclude itself\n",
|
| 1480 |
+
" return similar_indices\n"
|
| 1481 |
+
]
|
| 1482 |
+
},
|
| 1483 |
+
{
|
| 1484 |
+
"cell_type": "code",
|
| 1485 |
+
"execution_count": 34,
|
| 1486 |
+
"id": "c6e82e65",
|
| 1487 |
+
"metadata": {},
|
| 1488 |
+
"outputs": [
|
| 1489 |
+
{
|
| 1490 |
+
"name": "stdout",
|
| 1491 |
+
"output_type": "stream",
|
| 1492 |
+
"text": [
|
| 1493 |
+
"Time and Space\n",
|
| 1494 |
+
"A Monster From Space\n",
|
| 1495 |
+
"Budhayaan\n",
|
| 1496 |
+
"Manhunt in Space\n",
|
| 1497 |
+
"Journey to Space\n"
|
| 1498 |
+
]
|
| 1499 |
+
}
|
| 1500 |
+
],
|
| 1501 |
+
"source": [
|
| 1502 |
+
"recommended_movies = recommend(1)\n",
|
| 1503 |
+
"for mv in recommended_movies:\n",
|
| 1504 |
+
" print(get_movie_title(mv))"
|
| 1505 |
+
]
|
| 1506 |
+
},
|
| 1507 |
+
{
|
| 1508 |
+
"cell_type": "code",
|
| 1509 |
+
"execution_count": 1,
|
| 1510 |
+
"id": "a1aa9f21",
|
| 1511 |
+
"metadata": {},
|
| 1512 |
+
"outputs": [
|
| 1513 |
+
{
|
| 1514 |
+
"name": "stdout",
|
| 1515 |
+
"output_type": "stream",
|
| 1516 |
+
"text": [
|
| 1517 |
+
"Defaulting to user installation because normal site-packages is not writeable\n",
|
| 1518 |
+
"Requirement already satisfied: annoy in c:\\users\\unkno\\appdata\\local\\packages\\pythonsoftwarefoundation.python.3.13_qbz5n2kfra8p0\\localcache\\local-packages\\python313\\site-packages (1.17.3)\n"
|
| 1519 |
+
]
|
| 1520 |
+
},
|
| 1521 |
+
{
|
| 1522 |
+
"name": "stderr",
|
| 1523 |
+
"output_type": "stream",
|
| 1524 |
+
"text": [
|
| 1525 |
+
"\n",
|
| 1526 |
+
"[notice] A new release of pip is available: 25.0.1 -> 25.2\n",
|
| 1527 |
+
"[notice] To update, run: C:\\Users\\unkno\\AppData\\Local\\Microsoft\\WindowsApps\\PythonSoftwareFoundation.Python.3.13_qbz5n2kfra8p0\\python.exe -m pip install --upgrade pip\n"
|
| 1528 |
+
]
|
| 1529 |
+
},
|
| 1530 |
+
{
|
| 1531 |
+
"name": "stdout",
|
| 1532 |
+
"output_type": "stream",
|
| 1533 |
+
"text": [
|
| 1534 |
+
"Time and Space\n",
|
| 1535 |
+
"A Monster From Space\n",
|
| 1536 |
+
"Budhayaan\n",
|
| 1537 |
+
"Manhunt in Space\n",
|
| 1538 |
+
"Journey to Space\n"
|
| 1539 |
+
]
|
| 1540 |
+
}
|
| 1541 |
+
],
|
| 1542 |
+
"source": [
|
| 1543 |
+
"!pip install annoy\n",
|
| 1544 |
+
"\n",
|
| 1545 |
+
"from annoy import AnnoyIndex\n",
|
| 1546 |
+
"import numpy as np\n",
|
| 1547 |
+
"import pandas as pd\n",
|
| 1548 |
+
"\n",
|
| 1549 |
+
"# Load data\n",
|
| 1550 |
+
"feature_array = np.load('feature_array.npz')['arr_0']\n",
|
| 1551 |
+
"new_movies = pd.read_csv('movies_df.csv')\n",
|
| 1552 |
+
"f = feature_array.shape[1]\n",
|
| 1553 |
+
"annoy_index = AnnoyIndex(f, 'angular')\n",
|
| 1554 |
+
"\n",
|
| 1555 |
+
"# Build Annoy index (run this only once, it takes some time—then it's super fast)\n",
|
| 1556 |
+
"for i in range(feature_array.shape[0]):\n",
|
| 1557 |
+
" annoy_index.add_item(i, feature_array[i])\n",
|
| 1558 |
+
"annoy_index.build(10)\n",
|
| 1559 |
+
"\n",
|
| 1560 |
+
"def get_movie_title(movie_id):\n",
|
| 1561 |
+
" return new_movies.iloc[movie_id]['title']\n",
|
| 1562 |
+
"\n",
|
| 1563 |
+
"def recommend_fast(movie_id, top_k=5):\n",
|
| 1564 |
+
" idxs = annoy_index.get_nns_by_item(movie_id, top_k+1)[1:] # skip itself\n",
|
| 1565 |
+
" return idxs\n",
|
| 1566 |
+
"\n",
|
| 1567 |
+
"# Example usage\n",
|
| 1568 |
+
"recommended_movies = recommend_fast(1)\n",
|
| 1569 |
+
"for mv in recommended_movies:\n",
|
| 1570 |
+
" print(get_movie_title(mv))\n"
|
| 1571 |
+
]
|
| 1572 |
+
},
|
| 1573 |
+
{
|
| 1574 |
+
"cell_type": "code",
|
| 1575 |
+
"execution_count": 2,
|
| 1576 |
+
"id": "26664759",
|
| 1577 |
+
"metadata": {},
|
| 1578 |
+
"outputs": [
|
| 1579 |
+
{
|
| 1580 |
+
"name": "stdout",
|
| 1581 |
+
"output_type": "stream",
|
| 1582 |
+
"text": [
|
| 1583 |
+
"Time and Space\n",
|
| 1584 |
+
"A Monster From Space\n",
|
| 1585 |
+
"Budhayaan\n",
|
| 1586 |
+
"Manhunt in Space\n",
|
| 1587 |
+
"Journey to Space\n"
|
| 1588 |
+
]
|
| 1589 |
+
}
|
| 1590 |
+
],
|
| 1591 |
+
"source": [
|
| 1592 |
+
"recommended_movies = recommend_fast(1)\n",
|
| 1593 |
+
"for mv in recommended_movies:\n",
|
| 1594 |
+
" print(get_movie_title(mv))"
|
| 1595 |
+
]
|
| 1596 |
+
},
|
| 1597 |
+
{
|
| 1598 |
+
"cell_type": "code",
|
| 1599 |
+
"execution_count": 3,
|
| 1600 |
+
"id": "f7be3f08",
|
| 1601 |
+
"metadata": {},
|
| 1602 |
+
"outputs": [
|
| 1603 |
+
{
|
| 1604 |
+
"name": "stdout",
|
| 1605 |
+
"output_type": "stream",
|
| 1606 |
+
"text": [
|
| 1607 |
+
"Hunger Games: Katniss & Rue\n",
|
| 1608 |
+
"Offside - an Unequal Game\n",
|
| 1609 |
+
"bottomofthe9th\n",
|
| 1610 |
+
"Ádám Wilds - The Movie\n",
|
| 1611 |
+
"Pi Pong\n"
|
| 1612 |
+
]
|
| 1613 |
+
}
|
| 1614 |
+
],
|
| 1615 |
+
"source": [
|
| 1616 |
+
"recommended_movies = recommend_fast(200)\n",
|
| 1617 |
+
"for mv in recommended_movies:\n",
|
| 1618 |
+
" print(get_movie_title(mv))"
|
| 1619 |
+
]
|
| 1620 |
+
},
|
| 1621 |
+
{
|
| 1622 |
+
"cell_type": "code",
|
| 1623 |
+
"execution_count": 4,
|
| 1624 |
+
"id": "adda9d00",
|
| 1625 |
+
"metadata": {},
|
| 1626 |
+
"outputs": [
|
| 1627 |
+
{
|
| 1628 |
+
"name": "stdout",
|
| 1629 |
+
"output_type": "stream",
|
| 1630 |
+
"text": [
|
| 1631 |
+
"3.851896818727255 GB\n"
|
| 1632 |
+
]
|
| 1633 |
+
}
|
| 1634 |
+
],
|
| 1635 |
+
"source": [
|
| 1636 |
+
"annoy_index.save('my_index.ann')\n",
|
| 1637 |
+
"\n",
|
| 1638 |
+
"import os\n",
|
| 1639 |
+
"print(os.path.getsize('my_index.ann') / (1024**3), \"GB\")\n"
|
| 1640 |
+
]
|
| 1641 |
+
},
|
| 1642 |
+
{
|
| 1643 |
+
"cell_type": "code",
|
| 1644 |
+
"execution_count": null,
|
| 1645 |
+
"id": "1f34ea24",
|
| 1646 |
+
"metadata": {},
|
| 1647 |
+
"outputs": [],
|
| 1648 |
+
"source": [
|
| 1649 |
+
"\n"
|
| 1650 |
+
]
|
| 1651 |
+
}
|
| 1652 |
+
],
|
| 1653 |
+
"metadata": {
|
| 1654 |
+
"kernelspec": {
|
| 1655 |
+
"display_name": "Python 3",
|
| 1656 |
+
"language": "python",
|
| 1657 |
+
"name": "python3"
|
| 1658 |
+
},
|
| 1659 |
+
"language_info": {
|
| 1660 |
+
"codemirror_mode": {
|
| 1661 |
+
"name": "ipython",
|
| 1662 |
+
"version": 3
|
| 1663 |
+
},
|
| 1664 |
+
"file_extension": ".py",
|
| 1665 |
+
"mimetype": "text/x-python",
|
| 1666 |
+
"name": "python",
|
| 1667 |
+
"nbconvert_exporter": "python",
|
| 1668 |
+
"pygments_lexer": "ipython3",
|
| 1669 |
+
"version": "3.13.9"
|
| 1670 |
+
}
|
| 1671 |
+
},
|
| 1672 |
+
"nbformat": 4,
|
| 1673 |
+
"nbformat_minor": 5
|
| 1674 |
+
}
|
movies_df.csv
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:18ed8378723b509ba7c779ce6c495a32a3d6605a12d51fb9a1821c55aea2a808
|
| 3 |
+
size 309075548
|
my_index.ann
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:51716a2ec84add79327be429a40daed697255f555ec3e1b1193c959dfbdf214f
|
| 3 |
+
size 4135942716
|