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neuralnetflix

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9d040cb5102e9efcce847913f10e10f9661c318e

Updates readme with link to video

nnikhilaravi committed 8 years ago
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e8068a45b4d1fe866102a20cf7f59b80e35d506a

Add files via upload

kkimiamavon committed 8 years ago
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2a2cac07a7d7014dc9d0b63037500c69ad1b4c15

[Milestone 4] - updates answer to last question in the report

nnikhilaravi committed 8 years ago
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d2abd090d6eb1c57248a000efc7a8f48f6592dd9

[Milestone 4] - adds final code

nnikhilaravi committed 8 years ago
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12bad5a28cba74f6bfb13e2e539475db88f51e3a

[Milestone 4] - updates accuracy comparison table

nnikhilaravi committed 8 years ago
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fcff127208d6337bdc5357eaecc1ab70b7929c38

[Milestone 4]- updates report

nnikhilaravi committed 8 years ago

README

The README file for this repository.

Neural Netflix

Deep learning for movie posters

By Leonard Loo, Nikhila Ravi, Kimia Mavon and Yihang Yan

Watch the video to learn about our project!

Alt text

Running the code

Please don't shift around the directories. You can run the code in the various .ipynb as they are and they will read from the data folder.

Milestone1: No data needed. Pulled directly from TMDB. Milestone2: No data needed. Pulled directly from TMDB and IMDB. Milestone3: Used train_data_with_sampling.csv, test_data.csv and keywords.csv. Milestone4: No data needed. Pulled posters directly from our Github repo. Note: The data augmentation code's data is not included, because there are too many posters generated.

This project was created for the AC209b class at Harvard Spring 2017