Presenters
- Dr. Vijay Agneeswaran [ LinkedIn : http://bit.ly/vijaysa Twitter : @a_vijaysrinivas ]
- Abhishek Kumar [ LinkedIn : http://bit.ly/kumarabhishek Twitter : @meabhishekkumar ]
- Slides [ PDF : https://github.com/meabhishekkumar/strata-conference-ca-2018/blob/master/deep_learning_based_search_and_recommender_system.pdf ]
- Notebooks
- Data Preparation : Download required data to your local machine [https://github.com/meabhishekkumar/strata-conference-ca-2018/blob/master/01_data_preperation.ipynb ]
- Short Introduction to Embeddings in Tensorflow
- Image Search using Tensorflow
- Explicit Feedback Based Recommendation System using Tesnorflow
- Implicit Feedback Based Recommendation System
You can easily setup the enviornment with all required components ( data and notebooks ) with the help of Docker.
Here are the steps.
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Install Docker on your local machine. You will required documentation on Docker website [ https://docs.docker.com/install/ ]
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Make sure Docker is working fine. If you are not getting any error and able to see the docker
$ docker --version- Download the docker image and create container for the tutorial
$ docker run -it --rm -p 8888:8888 -p 0.0.0.0:6006:6006 meabhishekkumar/strata-ca-2018- Restricted Boltzmann Machines for Collaborative Filtering by Ruslan Salakhutdinov. Source: http://www.machinelearning.org/proceedings/icml2007/papers/407.pdf
- Wide & Deep Learning for Recommender Systems by Heng-Tze Cheng. Source: https://arxiv.org/abs/1606.07792
- A Survey and Critique of Deep Learning on Recommender Systems by Lei Zheng. Source: http://bdsc.lab.uic.edu/docs/survey-critique-deep.pdf
- DeepFM: A Factorization-Machine based Neural Network for CTR Prediction. IJCAI2017 Source: https://arxiv.org/abs/1703.04247
- Deep Neural Networks for YouTube Recommendations by Paul Covington. Source: https://static.googleusercontent.com/media/research.google.com/en//pubs/archive/45530.pdf
Credits :
- Recommendation system notebooks are inspired by Olivier Grisel work using Keras