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				| @ -188,24 +188,24 @@ Week 1: Intro | ||||
| - Read [SQuAD: 100,000+ Questions for Machine Comprehension of Text](https://arxiv.org/abs/1606.05250) | ||||
| - Read [Know What You Don't Know: Unanswerable Questions for SQuAD](https://arxiv.org/abs/1806.03822) | ||||
| 
 | ||||
| Week 2 and 3: Web Application | ||||
| Output: | ||||
| 
 | ||||
| - Analyze sql schema of Prodigy annotations  | ||||
| - Find out who annotated what. | ||||
| - Make a web application that displays results. | ||||
| - Extend the application to analyze more Prodigy instances (for both question and answer annotations) | ||||
| - Improve the process of annotation. | ||||
| - Short report | ||||
| 
 | ||||
| Output: Web application (in Node.js or Python) and Dockerfile | ||||
| 
 | ||||
| Week 4-7 The model | ||||
| Week 2-4 The System | ||||
| 
 | ||||
| Select and train a working question answering system | ||||
| 
 | ||||
| Output: | ||||
| 
 | ||||
| - a deployment script with comments for a selected question answering system  | ||||
| - a working training recipe (can use English data), a script with comments or Jupyter Notebook | ||||
| 
 | ||||
| Week 5-7 The Model | ||||
| 
 | ||||
| Take a working training recipe (can use English data), a script with comments or Jupyter Notebook | ||||
| 
 | ||||
| Output: | ||||
| 
 | ||||
| - a trained model | ||||
| - evaluation of the model (if possible) | ||||
| 
 | ||||
|  | ||||
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