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

• MLflow

  55 17,234 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 26,896 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.

• InfluxDB

  www.influxdata.com sponsored

  Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.

  

• tests-as-linear

  26 472 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