ML

lists / reviews

https://towardsdatascience.com/acing-machine-learning-interviews-aa73d6d7b07b

https://neptune.ai/blog/machine-learning-engineer-interview

( w/ answers )

https://www.simplilearn.com/tutorials/machine-learning-tutorial/machine-learning-interview-questions

https://github.com/andrewekhalel/MLQuestions

specific Qs / topic

• https://medium.com/coinmonks/what-is-entropy-and-why-information-gain-is-matter-4e85d46d2f01
• review of unsup. learning algo.
  • https://teetracker.medium.com/unsupervised-machine-learning-review-404167f8ced3
  • https://towardsdatascience.com/tsne-vs-umap-global-structure-4d8045acba17

metrics

• classification

  • https://neptune.ai/blog/f1-score-accuracy-roc-auc-pr-auc
  • https://machinelearningmastery.com/tour-of-evaluation-metrics-for-imbalanced-classification/

• regression / prediction

  • https://mlpills.dev/time-series/error-metrics-for-time-series-forecasting/

• probabilistic forecast

  • https://medium.com/trusted-data-science-haleon/metrics-for-distributional-forecasts-60e156c60177

few important Algorithms

EM

sorting-algorithms

exercises

https://www.hackerrank.com/

https://education.launchcode.org/data-analysis/index.html
https://education.launchcode.org/data-analysis/chapters/errors-and-debugging/exercises.html