LabModelacion MAT-282

Repository created with the purpose of build recommender systems and as a "Laboratorio de modelación"(subject of college) Project. Partial structure of README was obtained from the next link:

https://www.kaggle.com/WinningModelDocumentationGuidelines

Content Table

• ARCHIVE CONTENTS.
• HARDWARE.
• SOFTWARE.
• COMMENTS 6/11/2019 UPDATE.

ARCHIVE CONTENTS

.ipynb_checkpoints :carpet with some checkpoints(User-User.ipynb)

User-User.ipynb : Jupyter notebook file with all the code (Kernel=Python 3)

BX-Users.csv : Generic dataset with information associated to Users

BX-Books-Rating.csv : Generic with information associated to the "Rating"-interaction

BX-Books.csv : Generic dataset with information associated to Items

Soon...

train_code : code to rebuild models from scratch

predict_code : code to generate predictions from model binaries

HARDWARE (The following specs were used to create the original solution)

Windows 10 Home 64 bits 10.0,compilation:18362 (512Gb boot disk)

Intel(R) Core(TM) i5-8250U CPU @ 1.60Ghz (8CPUs) , ~1.8GHz

8192MB RAM

SOFTWARE (python packages are detailed separately in requirements.txt)

Python 3.7.3

nvidia drivers v.384

Python library used:

Pandas Ver. 0.25.1

Numpy Ver. 1.17.1

scikit-surprise 1.1.0

Comments about 6/11/2019 update

Sparse Matrix size: ~100k users X 100k items