Links I find helpful:

Binning Continuous Variables

What is the benefit of breaking up a continuous predictor variable?

Justification for low/high or tertiary splits in ANOVA

Class Imbalance

Are unbalanced datasets problematic, and (how) does oversampling (purport to) help?

Profusion of threads on imbalanced data - can we merge/deem canonical any?

Why does data science see class imbalance as a problem for supervised learning when statistics does not?

Classification Metrics (Related to Class Imbalance)

Why is accuracy not the best measure for assessing classification models?

Academic reference on the drawbacks of accuracy, F1 score, sensitivity and/or specificity

Central Limit Theorem

Debunking wrong CLT statement

Chunk Tests

What are chunk tests?

Deep Learning

Convolution operator in CNN and how it differs from feed forward NN operation?

Difference between loss and cost function in the specific context of MAE in multiple-regression?

Hypothesis Testing

Is normality testing 'essentially useless'?

Significance test for large sample sizes

Machine Learning

How to know that your machine learning problem is hopeless?

Imbalanced data to match reality with Random Forest?

Model Evaluation

Is my model any good, based on the diagnostic metric ($R^2$/AUC/ accuracy/RMSE etc.) value?

$R^2$

Interpreting nonlinear regression $R^2$

How arbitrary is adjusted r-squared as a measure of fit?

How to motivate the definition of $R^2$ in sklearn.metrics.r2_score?

Predicted R squared