jonathanMindee / solution-engineer-ds

Repository from Github https://github.comjonathanMindee/solution-engineer-dsRepository from Github https://github.comjonathanMindee/solution-engineer-ds

Solution Engineer (data science) Case Study for Mindee

This case is about testing candidates applying for a Solution Engineer position (data science track) at Mindee. The goal is to deliver high performances text recognition models trained using our open-source OCR library docTR.

Step 1: Understand the case

Read this article to understand the use case.

Step 2: Reproduce the text recognition training experiment

Ask the hiring manager to give you the training data. If you don't have enough computation capability, try to train on a smaller subsample of data.

Step 3: Demo

Show us how your model is performing during a live demo.

Step 4: Ideas of optimization

What would you change / add in your training process to optimize the results?

Preparing your interview

During your presentation, we will:

  • review your code quality using your training and inference scripts
  • check your ability to deliver a end-to-end demo
  • ask you questions about the models and how to optimize it

Good luck!

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