/fizzbuzz

Primary LanguageJupyter Notebook

LEMAY.AI INTERVIEW QUESTIONS

Hello, human.

Your goal is to demonstrate your coding skills by creating a video recording of your answers to some general knowledge questions, writing an ML API demo using Docker, python3, and a bit of magic, and showing us your exploratory data analysis skills. Please spend minimal effort on graphics and UI, as this is not a test of your UI coding skills. Just don't stress on frontend stuff.

1) GENERAL KNOWLEDGE VIDEO DEMONSTRATION AND TECHNICAL WRITING SAMPLE

  • Please provide a writing sample. The sample can be from your past work (off-the-shelf), or you can create a new technical writing sample. The writing sample should be on a technical subject, written in English, and should be at least one page in length.
  • Please make a video recording of your answers to the questions in the notebook: https://github.com/lemay-ai/fizzbuzz/blob/main/Interview_Questions.ipynb
  • Please send the video file and writing sample to daniel@lemay.ai and matt@lemay.ai
  • After you submit the video, proceed to steps 2 and 3, below.

2) MODEL DEPLOYMENT DEMONSTRATION

Please fork this repo (you may opt to share a private repo with us to preserve your privacy) and then do the following:

  • Create a branch in your forked repo
  • Create a container to process inference requests from any pretrained model in the huggingface model hub: https://huggingface.co/models
  • Your solution should include server components to support multiple parallel incoming requests (e.g., NGINX/gunicorn)
  • Create a notebook to demonstrate requests that POST to the container endpoint and print out the response
  • Please explain why you have chosen this model as your demonstration

3) EXPLORATORY DATA ANALYSIS DEMONSTRATION

  • Perform exploratory data analysis on any dataset in the huggingface datasets hub: https://huggingface.co/datasets

  • Include a notebook that contains your analysis within the repository

  • Please explain why you have chosen this dataset for your demonstration of exploratory data analysis

  • Commit your code

  • Create a pull request and you can approve it yourself and merge the branch into trunk

  • Document the process for using your updated repo in README.md so that we can try out your demo ourselves

  • Share the repo with the github users dcshapiro and elmathioso