Udemy MLOps Real World Machine Learning Projects for Professi
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| Torrent Hash : | 6072421399D4E8DAB286626C63C8099E57B86D03 |
| Torrent Added : | at May 1, 2025, 8:22 a.m. in Other |
| Torrent Size : | 2.6 GB |
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Udemy MLOps Real World Machine Learning Projects for Professi
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Udemy MLOps Real World Machine Learning Projects for Professi
Get Bonus Downloads Here.url -
1 -Project Planning & Introduction.mp4 -
1 -Data Collection.mp4 -
2 -1_Preprocessing_&_EDA.ipynb -
2 -Data Preprocessing & EDA.mp4 -
1 -Setup MLFlow Server on AWS.mp4 -
LICENSE -
README.md -
argv_exp.py -
example.py -
gitignore -
requirements.txt -
1 -2_experiment_1_baseline_model.ipynb -
1 -Building Baseline Model.mp4 -
2 -3_experiment_2_bow_tfidf.ipynb -
2 -Improving Baseline Model - BOW, TFIDF.mp4 -
3 -4_experiment_3_tfidf_(1,3)_max_features.ipynb -
3 -Improving Baseline Model - Max features.mp4 -
4 -5_experiment_4_handling_imbalanced_data.ipynb -
4 -Improving Baseline Model - Handling Imbalanced data.mp4 -
5 -6_experiment_5_xgboost_with_hpt.ipynb -
5 -7_experiment_6_lightgbm_detailed_hpt.ipynb -
5 -Improving Baseline Model - Hyperparameter tuning with Multiple Model.mp4 -
6 -8_stacking.ipynb -
6 -Improving Baseline Model - Stacking Models.mp4 -
1 -Building ML Pipeline using DVC.mp4 -
2 -Data Ingestion Component.mp4 -
3 -Data Preprocessing Component.mp4 -
4 -Model Building Component.mp4 -
5 -Model Evaluation Component with MLFlow.mp4 -
6 -Model Register Component with MLFlow.mp4 -
Dockerfile -
LICENSE -
README.md -
app.py -
confusion_matrix_Test Data.png -
test_processed.csv -
train_processed.csv -
test.csv -
train.csv -
dvc.lock -
dvc.yaml -
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config -
gitignore -
btime -
lock -
rwlock -
rwlock.lock -
dvcignore -
errors.log -
experiment_info.json -
app.py -
COMMIT_EDITMSG -
FETCH_HEAD -
HEAD -
ORIG_HEAD -
config -
description -
applypatch-msg.sample -
commit-msg.sample -
fsmonitor-watchman.sample -
post-update.sample -
pre-applypatch.sample -
pre-commit.sample -
pre-merge-commit.sample -
pre-push.sample -
pre-rebase.sample -
pre-receive.sample -
prepare-commit-msg.sample -
push-to-checkout.sample -
sendemail-validate.sample -
update.sample -
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packed-refs -
main -
HEAD -
main -
cicd.yaml -
gitignore -
lgbm_model.pkl -
model_building_errors.log -
model_evaluation_errors.log -
model_registration_errors.log -
1_Preprocessing_&_EDA.ipynb -
2_experiment_1_baseline_model.ipynb -
3_experiment_2_bow_tfidf.ipynb -
4_experiment_3_tfidf_(1,3)_max_features.ipynb -
5_experiment_4_handling_imbalanced_data.ipynb -
6_experiment_5_xgboost_with_hpt.ipynb -
7_experiment_6_lightgbm_detailed_hpt.ipynb -
8_stacking.ipynb -
reddit_preprocessing.csv -
params.yaml -
preprocessing_errors.log -
requirements.txt -
setup.py -
__init__.py -
data_ingestion.py -
data_preprocessing.py -
model_building.py -
model_evaluation.py -
register_model.py -
tfidf_vectorizer.pkl -
PKG-INFO -
SOURCES.txt -
dependency_links.txt -
top_level.txt -
manifest.json -
popup.html -
popup.js -
1 -Flask API Implementation.mp4 -
2 -Implementation of Chrome Plugin.mp4 -
1 -Adding Docker.mp4 -
2 -Deployment on AWS.mp4 -
Dockerfile -
LICENSE -
README.md -
app.py -
confusion_matrix_Test Data.png -
test_processed.csv -
train_processed.csv -
test.csv -
train.csv -
dvc.lock -
dvc.yaml -
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config -
gitignore -
btime -
lock -
rwlock -
rwlock.lock -
dvcignore -
errors.log -
experiment_info.json -
app.py -
COMMIT_EDITMSG -
FETCH_HEAD -
HEAD -
ORIG_HEAD -
config -
description -
applypatch-msg.sample -
commit-msg.sample -
fsmonitor-watchman.sample -
post-update.sample -
pre-applypatch.sample -
pre-commit.sample -
pre-merge-commit.sample -
pre-push.sample -
pre-rebase.sample -
pre-receive.sample -
prepare-commit-msg.sample -
push-to-checkout.sample -
sendemail-validate.sample -
update.sample -
index -
exclude -
HEAD -
main -
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main -
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packed-refs -
main -
HEAD -
main -
cicd.yaml -
gitignore -
lgbm_model.pkl -
model_building_errors.log -
model_evaluation_errors.log -
model_registration_errors.log -
1_Preprocessing_&_EDA.ipynb -
2_experiment_1_baseline_model.ipynb -
3_experiment_2_bow_tfidf.ipynb -
4_experiment_3_tfidf_(1,3)_max_features.ipynb -
5_experiment_4_handling_imbalanced_data.ipynb -
6_experiment_5_xgboost_with_hpt.ipynb -
7_experiment_6_lightgbm_detailed_hpt.ipynb -
8_stacking.ipynb -
reddit_preprocessing.csv -
params.yaml -
preprocessing_errors.log -
requirements.txt -
setup.py -
__init__.py -
data_ingestion.py -
data_preprocessing.py -
model_building.py -
model_evaluation.py -
register_model.py -
tfidf_vectorizer.pkl -
PKG-INFO -
SOURCES.txt -
dependency_links.txt -
top_level.txt -
manifest.json -
popup.html -
popup.js -
Bonus Resources.txt -
Please login or create a FREE account to post comments
Get Bonus Downloads Here.url -
183 bytes
1 -Project Planning & Introduction.mp4 -
350.9 MB
1 -Data Collection.mp4 -
29.5 MB
2 -1_Preprocessing_&_EDA.ipynb -
2.4 MB
2 -Data Preprocessing & EDA.mp4 -
363.1 MB
1 -Setup MLFlow Server on AWS.mp4 -
281.0 MB
LICENSE -
1.0 KB
README.md -
1.3 KB
argv_exp.py -
152 bytes
example.py -
3.4 KB
gitignore -
3.0 KB
requirements.txt -
19 bytes
1 -2_experiment_1_baseline_model.ipynb -
111.4 KB
1 -Building Baseline Model.mp4 -
169.8 MB
2 -3_experiment_2_bow_tfidf.ipynb -
30.5 KB
2 -Improving Baseline Model - BOW, TFIDF.mp4 -
151.4 MB
3 -4_experiment_3_tfidf_(1,3)_max_features.ipynb -
33.0 KB
3 -Improving Baseline Model - Max features.mp4 -
104.7 MB
4 -5_experiment_4_handling_imbalanced_data.ipynb -
36.1 KB
4 -Improving Baseline Model - Handling Imbalanced data.mp4 -
101.7 MB
5 -6_experiment_5_xgboost_with_hpt.ipynb -
48.4 KB
5 -7_experiment_6_lightgbm_detailed_hpt.ipynb -
9.7 MB
5 -Improving Baseline Model - Hyperparameter tuning with Multiple Model.mp4 -
92.4 MB
6 -8_stacking.ipynb -
91.4 KB
6 -Improving Baseline Model - Stacking Models.mp4 -
35.5 MB
1 -Building ML Pipeline using DVC.mp4 -
23.0 MB
2 -Data Ingestion Component.mp4 -
69.5 MB
3 -Data Preprocessing Component.mp4 -
28.1 MB
4 -Model Building Component.mp4 -
54.4 MB
5 -Model Evaluation Component with MLFlow.mp4 -
89.2 MB
6 -Model Register Component with MLFlow.mp4 -
29.3 MB
Dockerfile -
127 bytes
LICENSE -
1.1 KB
README.md -
1.9 KB
app.py -
11.3 KB
confusion_matrix_Test Data.png -
21.1 KB
test_processed.csv -
977.1 KB
train_processed.csv -
3.9 MB
test.csv -
1.3 MB
train.csv -
5.3 MB
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