[D] Looking for good refreshers on stats / ML to go back to the ML engineer interview game after 2 years doing mostly Software.

• MLflow

  57 17,620 9.9 Python

  Open source platform for the machine learning lifecycle

  

Any CI/CD experience you had working as a conventional SDE should translate well to "MLOps". Here are some resources to help you review what kinds of considerations might be important for productionizing ML projects: https://mlflow.org/, https://docs.microsoft.com/en-us/azure/machine-learning/concept-model-management-and-deployment

• handson-ml2

  12 27,055 0.0 Jupyter Notebook

  A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.

Much of the material from that book is publicly available in this repo maintained by the author.

• Scout Monitoring

  www.scoutapm.com featured

  Free Django app performance insights with Scout Monitoring. Get Scout setup in minutes, and let us sweat the small stuff. A couple lines in settings.py is all you need to start monitoring your apps. Sign up for our free tier today.

  

• tests-as-linear

  26 477 0.0 JavaScript

  Common statistical tests are linear models (or: how to teach stats)

Don't know about any cheat sheet but perhaps you'd find this pretty stimulating to read: https://lindeloev.github.io/tests-as-linear/

Suggest a related project