├── LICENSE
├── README.md
├── fm_amazon_recommender.html
└── fm_amazon_recommender.ipynb


/LICENSE:
--------------------------------------------------------------------------------
 1 | MIT License
 2 | 
 3 | Copyright (c) 2019 Nick Walsh
 4 | 
 5 | Permission is hereby granted, free of charge, to any person obtaining a copy
 6 | of this software and associated documentation files (the "Software"), to deal
 7 | in the Software without restriction, including without limitation the rights
 8 | to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
 9 | copies of the Software, and to permit persons to whom the Software is
10 | furnished to do so, subject to the following conditions:
11 | 
12 | The above copyright notice and this permission notice shall be included in all
13 | copies or substantial portions of the Software.
14 | 
15 | THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
16 | IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
17 | FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
18 | AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
19 | LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
20 | OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
21 | SOFTWARE.
22 | 


--------------------------------------------------------------------------------
/README.md:
--------------------------------------------------------------------------------
 1 | # sagemaker-rec-demo
 2 | 
 3 | **Building a Recommender System with Amazon SageMaker Factorization Machines and BlazingText**
 4 | 
 5 | 
 6 | ## Contents
 7 | 
 8 | Notebook: `fm_amazon_recommender.ipynb`
 9 | 
10 | ### Main Workshop:
11 | - Background (Factorization Machines)
12 | - Setup
13 | 	- Spin up SageMaker hosted notebook instance in console
14 | 	- Add SageMaker IAM policy to this SageMaker notebook to allow S3 read/write access
15 | 	- Create new S3 bucket (first cell)
16 | 	- Import necessary libraries (second cell)
17 | - Dataset
18 | 	- Overview
19 | 	- Source: [Amazon Reviews Public Dataset](https://s3.amazonaws.com/amazon-reviews-pds/readme.html)
20 | 	- Features
21 | - Data preprocessing
22 | - Training
23 | 	- Create SageMaker estimator
24 | 	- Launch training job
25 | - Host
26 | 	- Deploy endpoint to perform inference
27 | 
28 | 
29 | ### Extra Credit: 
30 | - Background (New challenges, word2vec, BlazingText)
31 | - Data Augmentation
32 | - Dimensionality reduction with t-SNE
33 | - Train
34 | - Host


--------------------------------------------------------------------------------