Challenge Overview
Cloud Hub is looking to create a proof of concept project that leverages machine learning to classify data. We are looking to leverage bayes classifier (or something better) to help map data to a list of approved vendors we have in our database. The incoming data will have different spellings, spacing and will need to be cleansed and then analzyed. For example Chef (DevOps software) bills clients as "OPSCODE, INC". We want to train our system to know this relationship, and know that the next time Opscode or something similar appears that it refers to Chef.
Requirements
1. Build NodeJS API with Express to demonstrate service.
2. Build endpoint or script to train the model.
3. Write endpoint to add additional training data, one classification at a time.
4. Build endpoint to anaylize the test samples, one at a time is acceptable.
5. Include postman file for testing and verification.
2. The bulk of your documentation should be in the Readme.md and you should assume that this will be open source so make sure you cover all the steps to set up, If you have specific information that should not be included in a public readme (like links to your video) put them in a file called submission.txt and they will be omitted from the project if it is open sourced.
3. Provide a quick video of your solution in action (feel free to annotate your video if you are not comfortable with spoken English or don’t like the sound of your own voice). Video may be private on youtube or added to the submission files. Your video can skip the setup of your environment, linting and tests. We are interested to see the new functionality of the app in the video.
Requirements
1. Build NodeJS API with Express to demonstrate service.
2. Build endpoint or script to train the model.
3. Write endpoint to add additional training data, one classification at a time.
4. Build endpoint to anaylize the test samples, one at a time is acceptable.
5. Include postman file for testing and verification.
Final Submission Guidelines
1. Provide your code and documentation in a single zip file.2. The bulk of your documentation should be in the Readme.md and you should assume that this will be open source so make sure you cover all the steps to set up, If you have specific information that should not be included in a public readme (like links to your video) put them in a file called submission.txt and they will be omitted from the project if it is open sourced.
3. Provide a quick video of your solution in action (feel free to annotate your video if you are not comfortable with spoken English or don’t like the sound of your own voice). Video may be private on youtube or added to the submission files. Your video can skip the setup of your environment, linting and tests. We are interested to see the new functionality of the app in the video.