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  1. Best_model.joblib +3 -0
  2. app.py +101 -0
  3. preprocessor.joblib +3 -0
  4. requirements.txt +543 -0
Best_model.joblib ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
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+ oid sha256:92a3b494dd92658f40578f5821389ecdfb4c0b5f328fce099cb758def229e85b
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+ size 168519129
app.py ADDED
@@ -0,0 +1,101 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ import gradio as gr
2
+ import pandas as pd
3
+ import joblib
4
+ import os
5
+
6
+ # Load the models
7
+ preprocessor_path = os.path.join('.', 'preprocessor.joblib')
8
+ model_path = os.path.join('.', 'Best_model.joblib')
9
+
10
+ preprocessor = joblib.load('C:\Users\USER\Documents\DS\TMP\preprocessor.joblib')
11
+ best_model = joblib.load('C:\Users\USER\Documents\DS\TMP\Best_model.joblib')
12
+
13
+ # Define prediction function
14
+ def predict(age, job, marital, education, default, housing, loan, contact, month, day_of_week, duration, campaign, pdays, previous, poutcome, emp_var_rate, cons_price_idx, cons_conf_idx, euribor3m, nr_employed):
15
+ # Create a DataFrame for the input data
16
+ data = pd.DataFrame({
17
+ 'age': [age],
18
+ 'job': [job],
19
+ 'marital': [marital],
20
+ 'education': [education],
21
+ 'default': [default],
22
+ 'housing': [housing],
23
+ 'loan': [loan],
24
+ 'contact': [contact],
25
+ 'month': [month],
26
+ 'day_of_week': [day_of_week],
27
+ 'duration': [duration],
28
+ 'campaign': [campaign],
29
+ 'pdays': [pdays],
30
+ 'previous': [previous],
31
+ 'poutcome': [poutcome],
32
+ 'emp.var.rate': [emp_var_rate],
33
+ 'cons.price.idx': [cons_price_idx],
34
+ 'cons.conf.idx': [cons_conf_idx],
35
+ 'euribor3m': [euribor3m],
36
+ 'nr.employed': [nr_employed]
37
+ })
38
+
39
+ # Preprocess the data
40
+ preprocessed_data = preprocessor.transform(data)
41
+
42
+ # Make predictions
43
+ prediction = best_model.predict(preprocessed_data)
44
+ probability = best_model.predict_proba(preprocessed_data)
45
+
46
+ return {
47
+ "Prediction": prediction[0],
48
+ "Probability (Yes)": probability[0][1],
49
+ "Probability (No)": probability[0][0]
50
+ }
51
+
52
+ # Define the interface
53
+ def gradio_interface():
54
+ with gr.Blocks() as app:
55
+ gr.Markdown("# Bank Marketing Campaign Prediction")
56
+
57
+ with gr.Row():
58
+ age = gr.Number(label="Age", value=30)
59
+ job = gr.Dropdown(["housemaid", "services", "admin.", "blue-collar", "technician", "retired", "management", "unemployed", "self-employed", "unknown", "entrepreneur", "student"], label="Job")
60
+ marital = gr.Dropdown(["married", "single", "divorced", "unknown"], label="Marital Status")
61
+ education = gr.Dropdown(["basic.4y", "high.school", "basic.6y", "basic.9y", "professional.course", "unknown", "university.degree", "illiterate", "tertiary", "secondary", "primary"], label="Education")
62
+
63
+ with gr.Row():
64
+ default = gr.Dropdown(["no", "unknown", "yes"], label="Default")
65
+ housing = gr.Dropdown(["no", "yes", "unknown"], label="Housing Loan")
66
+ loan = gr.Dropdown(["no", "yes", "unknown"], label="Personal Loan")
67
+ contact = gr.Dropdown(["telephone", "cellular", "unknown"], label="Contact Type")
68
+
69
+ with gr.Row():
70
+ month = gr.Dropdown(["may", "jun", "jul", "aug", "oct", "nov", "dec", "mar", "apr", "sep", "jan", "feb"], label="Month")
71
+ day_of_week = gr.Dropdown(["mon", "tue", "wed", "thu", "fri"], label="Day of Week")
72
+
73
+ with gr.Row():
74
+ duration = gr.Number(label="Call Duration (seconds)", value=100)
75
+ campaign = gr.Number(label="Number of Contacts during Campaign", value=1)
76
+ pdays = gr.Number(label="Days since Last Contact", value=999)
77
+ previous = gr.Number(label="Number of Contacts before Campaign", value=0)
78
+ poutcome = gr.Dropdown(["nonexistent", "failure", "success", "unknown", "other"], label="Previous Outcome")
79
+
80
+ with gr.Row():
81
+ emp_var_rate = gr.Number(label="Employment Variation Rate", value=1.1)
82
+ cons_price_idx = gr.Number(label="Consumer Price Index", value=93.994)
83
+ cons_conf_idx = gr.Number(label="Consumer Confidence Index", value=-36.4)
84
+ euribor3m = gr.Number(label="Euribor 3-Month Rate", value=4.857)
85
+ nr_employed = gr.Number(label="Number of Employees", value=5191.0)
86
+
87
+ predict_btn = gr.Button("Predict")
88
+ output = gr.JSON()
89
+
90
+ predict_btn.click(
91
+ predict,
92
+ inputs=[age, job, marital, education, default, housing, loan, contact, month, day_of_week, duration, campaign, pdays, previous, poutcome, emp_var_rate, cons_price_idx, cons_conf_idx, euribor3m, nr_employed],
93
+ outputs=output
94
+ )
95
+
96
+ return app
97
+
98
+ # Launch the app
99
+ if __name__ == "__main__":
100
+ app = gradio_interface()
101
+ app.launch()
preprocessor.joblib ADDED
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1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:34a6b9e6713e8941ac3d86acc659f146e739684e7055678601dda88e2958dacb
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+ size 6716
requirements.txt ADDED
@@ -0,0 +1,543 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ absl-py==1.4.0
2
+ accelerate==1.1.1
3
+ aiohappyeyeballs==2.4.4
4
+ aiohttp==3.11.10
5
+ aiosignal==1.3.2
6
+ alabaster==1.0.0
7
+ albucore==0.0.19
8
+ albumentations==1.4.20
9
+ altair==5.5.0
10
+ annotated-types==0.7.0
11
+ anyio==3.7.1
12
+ argon2-cffi==23.1.0
13
+ argon2-cffi-bindings==21.2.0
14
+ array_record==0.5.1
15
+ arviz==0.20.0
16
+ astropy==6.1.7
17
+ astropy-iers-data==0.2024.12.9.0.36.21
18
+ astunparse==1.6.3
19
+ async-timeout==4.0.3
20
+ atpublic==4.1.0
21
+ attrs==24.2.0
22
+ audioread==3.0.1
23
+ autograd==1.7.0
24
+ babel==2.16.0
25
+ backcall==0.2.0
26
+ beautifulsoup4==4.12.3
27
+ bigframes==1.29.0
28
+ bigquery-magics==0.4.0
29
+ bleach==6.2.0
30
+ blinker==1.9.0
31
+ blis==0.7.11
32
+ blosc2==2.7.1
33
+ bokeh==3.6.2
34
+ Bottleneck==1.4.2
35
+ bqplot==0.12.43
36
+ branca==0.8.0
37
+ CacheControl==0.14.1
38
+ cachetools==5.5.0
39
+ catalogue==2.0.10
40
+ certifi==2024.8.30
41
+ cffi==1.17.1
42
+ chardet==5.2.0
43
+ charset-normalizer==3.4.0
44
+ chex==0.1.88
45
+ clarabel==0.9.0
46
+ click==8.1.7
47
+ cloudpathlib==0.20.0
48
+ cloudpickle==3.1.0
49
+ cmake==3.30.5
50
+ cmdstanpy==1.2.5
51
+ colorcet==3.1.0
52
+ colorlover==0.3.0
53
+ colour==0.1.5
54
+ community==1.0.0b1
55
+ confection==0.1.5
56
+ cons==0.4.6
57
+ contourpy==1.3.1
58
+ cryptography==43.0.3
59
+ cuda-python==12.2.1
60
+ cudf-cu12 @ https://pypi.nvidia.com/cudf-cu12/cudf_cu12-24.10.1-cp310-cp310-manylinux_2_24_x86_64.manylinux_2_28_x86_64.whl
61
+ cufflinks==0.17.3
62
+ cupy-cuda12x==12.2.0
63
+ cvxopt==1.3.2
64
+ cvxpy==1.5.4
65
+ cycler==0.12.1
66
+ cymem==2.0.10
67
+ Cython==3.0.11
68
+ dask==2024.10.0
69
+ datascience==0.17.6
70
+ db-dtypes==1.3.1
71
+ dbus-python==1.2.18
72
+ debugpy==1.8.0
73
+ decorator==4.4.2
74
+ defusedxml==0.7.1
75
+ Deprecated==1.2.15
76
+ diffusers==0.31.0
77
+ distro==1.9.0
78
+ dlib==19.24.2
79
+ dm-tree==0.1.8
80
+ docker-pycreds==0.4.0
81
+ docstring_parser==0.16
82
+ docutils==0.21.2
83
+ dopamine_rl==4.0.9
84
+ duckdb==1.1.3
85
+ earthengine-api==1.2.0
86
+ easydict==1.13
87
+ ecos==2.0.14
88
+ editdistance==0.8.1
89
+ eerepr==0.0.4
90
+ einops==0.8.0
91
+ en-core-web-sm @ https://github.com/explosion/spacy-models/releases/download/en_core_web_sm-3.7.1/en_core_web_sm-3.7.1-py3-none-any.whl#sha256=86cc141f63942d4b2c5fcee06630fd6f904788d2f0ab005cce45aadb8fb73889
92
+ entrypoints==0.4
93
+ et_xmlfile==2.0.0
94
+ etils==1.11.0
95
+ etuples==0.3.9
96
+ eval_type_backport==0.2.0
97
+ exceptiongroup==1.2.2
98
+ fastai==2.7.18
99
+ fastcore==1.7.26
100
+ fastdownload==0.0.7
101
+ fastjsonschema==2.21.1
102
+ fastprogress==1.0.3
103
+ fastrlock==0.8.2
104
+ filelock==3.16.1
105
+ firebase-admin==6.5.0
106
+ Flask==3.0.3
107
+ flatbuffers==24.3.25
108
+ flax==0.8.5
109
+ folium==0.18.0
110
+ fonttools==4.55.3
111
+ frozendict==2.4.6
112
+ frozenlist==1.5.0
113
+ fsspec==2024.10.0
114
+ future==1.0.0
115
+ gast==0.6.0
116
+ gcsfs==2024.10.0
117
+ GDAL==3.6.4
118
+ gdown==5.2.0
119
+ geemap==0.35.1
120
+ gensim==4.3.3
121
+ geocoder==1.38.1
122
+ geographiclib==2.0
123
+ geopandas==1.0.1
124
+ geopy==2.4.1
125
+ gin-config==0.5.0
126
+ gitdb==4.0.11
127
+ GitPython==3.1.43
128
+ glob2==0.7
129
+ google==2.0.3
130
+ google-ai-generativelanguage==0.6.10
131
+ google-api-core==2.19.2
132
+ google-api-python-client==2.151.0
133
+ google-auth==2.27.0
134
+ google-auth-httplib2==0.2.0
135
+ google-auth-oauthlib==1.2.1
136
+ google-cloud-aiplatform==1.73.0
137
+ google-cloud-bigquery==3.25.0
138
+ google-cloud-bigquery-connection==1.16.1
139
+ google-cloud-bigquery-storage==2.27.0
140
+ google-cloud-bigtable==2.27.0
141
+ google-cloud-core==2.4.1
142
+ google-cloud-datastore==2.20.2
143
+ google-cloud-firestore==2.19.0
144
+ google-cloud-functions==1.18.1
145
+ google-cloud-iam==2.17.0
146
+ google-cloud-language==2.15.1
147
+ google-cloud-pubsub==2.27.1
148
+ google-cloud-resource-manager==1.14.0
149
+ google-cloud-storage==2.8.0
150
+ google-cloud-translate==3.17.0
151
+ google-colab @ file:///colabtools/dist/google_colab-1.0.0.tar.gz
152
+ google-crc32c==1.6.0
153
+ google-genai==0.2.2
154
+ google-generativeai==0.8.3
155
+ google-pasta==0.2.0
156
+ google-resumable-media==2.7.2
157
+ googleapis-common-protos==1.66.0
158
+ googledrivedownloader==0.4
159
+ graphviz==0.20.3
160
+ greenlet==3.1.1
161
+ grpc-google-iam-v1==0.13.1
162
+ grpcio==1.68.1
163
+ grpcio-status==1.62.3
164
+ gspread==6.0.2
165
+ gspread-dataframe==3.3.1
166
+ gym==0.25.2
167
+ gym-notices==0.0.8
168
+ h11==0.14.0
169
+ h5netcdf==1.4.1
170
+ h5py==3.12.1
171
+ holidays==0.62
172
+ holoviews==1.20.0
173
+ html5lib==1.1
174
+ httpcore==1.0.7
175
+ httpimport==1.4.0
176
+ httplib2==0.22.0
177
+ httpx==0.28.1
178
+ huggingface-hub==0.26.5
179
+ humanize==4.11.0
180
+ hyperopt==0.2.7
181
+ ibis-framework==9.2.0
182
+ idna==3.10
183
+ imageio==2.36.1
184
+ imageio-ffmpeg==0.5.1
185
+ imagesize==1.4.1
186
+ imbalanced-learn==0.12.4
187
+ imgaug==0.4.0
188
+ immutabledict==4.2.1
189
+ importlib_metadata==8.5.0
190
+ importlib_resources==6.4.5
191
+ imutils==0.5.4
192
+ inflect==7.4.0
193
+ iniconfig==2.0.0
194
+ intel-cmplr-lib-ur==2025.0.4
195
+ intel-openmp==2025.0.4
196
+ ipyevents==2.0.2
197
+ ipyfilechooser==0.6.0
198
+ ipykernel==5.5.6
199
+ ipyleaflet==0.19.2
200
+ ipyparallel==8.8.0
201
+ ipython==7.34.0
202
+ ipython-genutils==0.2.0
203
+ ipython-sql==0.5.0
204
+ ipytree==0.2.2
205
+ ipywidgets==7.7.1
206
+ itsdangerous==2.2.0
207
+ jax==0.4.33
208
+ jax-cuda12-pjrt==0.4.33
209
+ jax-cuda12-plugin==0.4.33
210
+ jaxlib==0.4.33
211
+ jeepney==0.7.1
212
+ jellyfish==1.1.0
213
+ jieba==0.42.1
214
+ Jinja2==3.1.4
215
+ jiter==0.8.2
216
+ joblib==1.4.2
217
+ jsonpatch==1.33
218
+ jsonpickle==4.0.0
219
+ jsonpointer==3.0.0
220
+ jsonschema==4.23.0
221
+ jsonschema-specifications==2024.10.1
222
+ jupyter-client==6.1.12
223
+ jupyter-console==6.1.0
224
+ jupyter-leaflet==0.19.2
225
+ jupyter-server==1.24.0
226
+ jupyter_core==5.7.2
227
+ jupyterlab_pygments==0.3.0
228
+ jupyterlab_widgets==3.0.13
229
+ kaggle==1.6.17
230
+ kagglehub==0.3.5
231
+ keras==3.5.0
232
+ keyring==23.5.0
233
+ kiwisolver==1.4.7
234
+ langchain==0.3.11
235
+ langchain-core==0.3.24
236
+ langchain-text-splitters==0.3.2
237
+ langcodes==3.5.0
238
+ langsmith==0.2.3
239
+ language_data==1.3.0
240
+ launchpadlib==1.10.16
241
+ lazr.restfulclient==0.14.4
242
+ lazr.uri==1.0.6
243
+ lazy_loader==0.4
244
+ libclang==18.1.1
245
+ libcudf-cu12 @ https://pypi.nvidia.com/libcudf-cu12/libcudf_cu12-24.10.1-py3-none-manylinux_2_28_x86_64.whl
246
+ librosa==0.10.2.post1
247
+ lightgbm==4.5.0
248
+ linkify-it-py==2.0.3
249
+ llvmlite==0.43.0
250
+ locket==1.0.0
251
+ logical-unification==0.4.6
252
+ lxml==5.3.0
253
+ marisa-trie==1.2.1
254
+ Markdown==3.7
255
+ markdown-it-py==3.0.0
256
+ MarkupSafe==3.0.2
257
+ matplotlib==3.8.0
258
+ matplotlib-inline==0.1.7
259
+ matplotlib-venn==1.1.1
260
+ mdit-py-plugins==0.4.2
261
+ mdurl==0.1.2
262
+ miniKanren==1.0.3
263
+ missingno==0.5.2
264
+ mistune==3.0.2
265
+ mizani==0.13.1
266
+ mkl==2025.0.1
267
+ ml-dtypes==0.4.1
268
+ mlxtend==0.23.3
269
+ more-itertools==10.5.0
270
+ moviepy==1.0.3
271
+ mpmath==1.3.0
272
+ msgpack==1.1.0
273
+ multidict==6.1.0
274
+ multipledispatch==1.0.0
275
+ multitasking==0.0.11
276
+ murmurhash==1.0.11
277
+ music21==9.3.0
278
+ namex==0.0.8
279
+ narwhals==1.18.2
280
+ natsort==8.4.0
281
+ nbclassic==1.1.0
282
+ nbclient==0.10.1
283
+ nbconvert==7.16.4
284
+ nbformat==5.10.4
285
+ ndindex==1.9.2
286
+ nest-asyncio==1.6.0
287
+ networkx==3.4.2
288
+ nibabel==5.3.2
289
+ nltk==3.9.1
290
+ notebook==6.5.5
291
+ notebook_shim==0.2.4
292
+ numba==0.60.0
293
+ numexpr==2.10.2
294
+ numpy==1.26.4
295
+ nvidia-cublas-cu12==12.6.4.1
296
+ nvidia-cuda-cupti-cu12==12.6.80
297
+ nvidia-cuda-nvcc-cu12==12.6.85
298
+ nvidia-cuda-runtime-cu12==12.6.77
299
+ nvidia-cudnn-cu12==9.6.0.74
300
+ nvidia-cufft-cu12==11.3.0.4
301
+ nvidia-curand-cu12==10.3.7.77
302
+ nvidia-cusolver-cu12==11.7.1.2
303
+ nvidia-cusparse-cu12==12.5.4.2
304
+ nvidia-nccl-cu12==2.23.4
305
+ nvidia-nvjitlink-cu12==12.6.85
306
+ nvtx==0.2.10
307
+ nx-cugraph-cu12 @ https://pypi.nvidia.com/nx-cugraph-cu12/nx_cugraph_cu12-24.10.0-py3-none-any.whl
308
+ oauth2client==4.1.3
309
+ oauthlib==3.2.2
310
+ openai==1.54.5
311
+ opencv-contrib-python==4.10.0.84
312
+ opencv-python==4.10.0.84
313
+ opencv-python-headless==4.10.0.84
314
+ openpyxl==3.1.5
315
+ opentelemetry-api==1.29.0
316
+ opentelemetry-sdk==1.29.0
317
+ opentelemetry-semantic-conventions==0.50b0
318
+ opt_einsum==3.4.0
319
+ optax==0.2.4
320
+ optree==0.13.1
321
+ orbax-checkpoint==0.6.4
322
+ orjson==3.10.12
323
+ osqp==0.6.7.post3
324
+ packaging==24.2
325
+ pandas==2.2.2
326
+ pandas-datareader==0.10.0
327
+ pandas-gbq==0.24.0
328
+ pandas-stubs==2.2.2.240909
329
+ pandocfilters==1.5.1
330
+ panel==1.5.4
331
+ param==2.1.1
332
+ parso==0.8.4
333
+ parsy==2.1
334
+ partd==1.4.2
335
+ pathlib==1.0.1
336
+ patsy==1.0.1
337
+ peewee==3.17.8
338
+ peft==0.13.2
339
+ pexpect==4.9.0
340
+ pickleshare==0.7.5
341
+ pillow==11.0.0
342
+ platformdirs==4.3.6
343
+ plotly==5.24.1
344
+ plotnine==0.14.3
345
+ pluggy==1.5.0
346
+ ply==3.11
347
+ polars==1.9.0
348
+ pooch==1.8.2
349
+ portpicker==1.5.2
350
+ preshed==3.0.9
351
+ prettytable==3.12.0
352
+ proglog==0.1.10
353
+ progressbar2==4.5.0
354
+ prometheus_client==0.21.1
355
+ promise==2.3
356
+ prompt_toolkit==3.0.48
357
+ propcache==0.2.1
358
+ prophet==1.1.6
359
+ proto-plus==1.25.0
360
+ protobuf==4.25.5
361
+ psutil==5.9.5
362
+ psycopg2==2.9.10
363
+ ptyprocess==0.7.0
364
+ py-cpuinfo==9.0.0
365
+ py4j==0.10.9.7
366
+ pyarrow==17.0.0
367
+ pyasn1==0.6.1
368
+ pyasn1_modules==0.4.1
369
+ pycocotools==2.0.8
370
+ pycparser==2.22
371
+ pydantic==2.10.3
372
+ pydantic_core==2.27.1
373
+ pydata-google-auth==1.9.0
374
+ pydot==3.0.3
375
+ pydotplus==2.0.2
376
+ PyDrive==1.3.1
377
+ PyDrive2==1.21.3
378
+ pyerfa==2.0.1.5
379
+ pygame==2.6.1
380
+ pygit2==1.16.0
381
+ Pygments==2.18.0
382
+ PyGObject==3.42.1
383
+ PyJWT==2.10.1
384
+ pylibcudf-cu12 @ https://pypi.nvidia.com/pylibcudf-cu12/pylibcudf_cu12-24.10.1-cp310-cp310-manylinux_2_24_x86_64.manylinux_2_28_x86_64.whl
385
+ pylibcugraph-cu12==24.10.0
386
+ pylibraft-cu12==24.10.0
387
+ pymc==5.18.2
388
+ pymystem3==0.2.0
389
+ pynvjitlink-cu12==0.4.0
390
+ pyogrio==0.10.0
391
+ Pyomo==6.8.2
392
+ PyOpenGL==3.1.7
393
+ pyOpenSSL==24.2.1
394
+ pyparsing==3.2.0
395
+ pyperclip==1.9.0
396
+ pyproj==3.7.0
397
+ pyshp==2.3.1
398
+ PySocks==1.7.1
399
+ pyspark==3.5.3
400
+ pytensor==2.26.4
401
+ pytest==8.3.4
402
+ python-apt==0.0.0
403
+ python-box==7.3.0
404
+ python-dateutil==2.8.2
405
+ python-louvain==0.16
406
+ python-slugify==8.0.4
407
+ python-utils==3.9.1
408
+ pytz==2024.2
409
+ pyviz_comms==3.0.3
410
+ PyYAML==6.0.2
411
+ pyzmq==24.0.1
412
+ qdldl==0.1.7.post4
413
+ ratelim==0.1.6
414
+ referencing==0.35.1
415
+ regex==2024.9.11
416
+ requests==2.32.3
417
+ requests-oauthlib==1.3.1
418
+ requests-toolbelt==1.0.0
419
+ requirements-parser==0.9.0
420
+ rich==13.9.4
421
+ rmm-cu12==24.10.0
422
+ rpds-py==0.22.3
423
+ rpy2==3.4.2
424
+ rsa==4.9
425
+ safetensors==0.4.5
426
+ scikit-image==0.24.0
427
+ scikit-learn==1.5.2
428
+ scipy==1.13.1
429
+ scooby==0.10.0
430
+ scs==3.2.7
431
+ seaborn==0.13.2
432
+ SecretStorage==3.3.1
433
+ Send2Trash==1.8.3
434
+ sentence-transformers==3.2.1
435
+ sentencepiece==0.2.0
436
+ sentry-sdk==2.19.2
437
+ setproctitle==1.3.4
438
+ shap==0.46.0
439
+ shapely==2.0.6
440
+ shellingham==1.5.4
441
+ simple-parsing==0.1.6
442
+ six==1.17.0
443
+ sklearn-pandas==2.2.0
444
+ slicer==0.0.8
445
+ smart-open==7.0.5
446
+ smmap==5.0.1
447
+ sniffio==1.3.1
448
+ snowballstemmer==2.2.0
449
+ soundfile==0.12.1
450
+ soupsieve==2.6
451
+ soxr==0.5.0.post1
452
+ spacy==3.7.5
453
+ spacy-legacy==3.0.12
454
+ spacy-loggers==1.0.5
455
+ Sphinx==8.1.3
456
+ sphinxcontrib-applehelp==2.0.0
457
+ sphinxcontrib-devhelp==2.0.0
458
+ sphinxcontrib-htmlhelp==2.1.0
459
+ sphinxcontrib-jsmath==1.0.1
460
+ sphinxcontrib-qthelp==2.0.0
461
+ sphinxcontrib-serializinghtml==2.0.0
462
+ SQLAlchemy==2.0.36
463
+ sqlglot==25.1.0
464
+ sqlparse==0.5.3
465
+ srsly==2.5.0
466
+ stanio==0.5.1
467
+ statsmodels==0.14.4
468
+ StrEnum==0.4.15
469
+ stringzilla==3.11.1
470
+ sympy==1.13.1
471
+ tables==3.10.1
472
+ tabulate==0.9.0
473
+ tbb==2022.0.0
474
+ tcmlib==1.2.0
475
+ tenacity==9.0.0
476
+ tensorboard==2.17.1
477
+ tensorboard-data-server==0.7.2
478
+ tensorflow==2.17.1
479
+ tensorflow-datasets==4.9.7
480
+ tensorflow-hub==0.16.1
481
+ tensorflow-io-gcs-filesystem==0.37.1
482
+ tensorflow-metadata==1.13.1
483
+ tensorflow-probability==0.24.0
484
+ tensorstore==0.1.71
485
+ termcolor==2.5.0
486
+ terminado==0.18.1
487
+ text-unidecode==1.3
488
+ textblob==0.17.1
489
+ tf-slim==1.1.0
490
+ tf_keras==2.17.0
491
+ thinc==8.2.5
492
+ threadpoolctl==3.5.0
493
+ tifffile==2024.12.12
494
+ timm==1.0.12
495
+ tinycss2==1.4.0
496
+ tokenizers==0.20.3
497
+ toml==0.10.2
498
+ tomli==2.2.1
499
+ toolz==0.12.1
500
+ torch @ https://download.pytorch.org/whl/cu121_full/torch-2.5.1%2Bcu121-cp310-cp310-linux_x86_64.whl
501
+ torchaudio @ https://download.pytorch.org/whl/cu121/torchaudio-2.5.1%2Bcu121-cp310-cp310-linux_x86_64.whl
502
+ torchsummary==1.5.1
503
+ torchvision @ https://download.pytorch.org/whl/cu121/torchvision-0.20.1%2Bcu121-cp310-cp310-linux_x86_64.whl
504
+ tornado==6.3.3
505
+ tqdm==4.66.6
506
+ traitlets==5.7.1
507
+ traittypes==0.2.1
508
+ transformers==4.46.3
509
+ tweepy==4.14.0
510
+ typeguard==4.4.1
511
+ typer==0.15.1
512
+ types-pytz==2024.2.0.20241003
513
+ types-setuptools==75.6.0.20241126
514
+ typing_extensions==4.12.2
515
+ tzdata==2024.2
516
+ tzlocal==5.2
517
+ uc-micro-py==1.0.3
518
+ umf==0.9.1
519
+ uritemplate==4.1.1
520
+ urllib3==2.2.3
521
+ vega-datasets==0.9.0
522
+ wadllib==1.3.6
523
+ wandb==0.18.7
524
+ wasabi==1.1.3
525
+ wcwidth==0.2.13
526
+ weasel==0.4.1
527
+ webcolors==24.11.1
528
+ webencodings==0.5.1
529
+ websocket-client==1.8.0
530
+ websockets==14.1
531
+ Werkzeug==3.1.3
532
+ widgetsnbextension==3.6.10
533
+ wordcloud==1.9.4
534
+ wrapt==1.17.0
535
+ xarray==2024.10.0
536
+ xarray-einstats==0.8.0
537
+ xgboost==2.1.3
538
+ xlrd==2.0.1
539
+ xyzservices==2024.9.0
540
+ yarl==1.18.3
541
+ yellowbrick==1.5
542
+ yfinance==0.2.50
543
+ zipp==3.21.0