Breaking Linear Regression

What happens if we break the assumptions of linear regression for machine learning? RESOURCES [1] What do linear regression parameters mean: https://datascience.stackexchange.com/questions/12274/what-does-linear-in-parameters-mean [2] This has some good intuition that distinguishes applications of linear regression: https://stats.stackexchange.com/questions/486672/why-dont-linear-regression-assumptions-matter-in-machine-learning [3] Why should residuals be normally distributed? https://qr.ae/pvl91W [4] Penn State's notes on the assumptions of linear regression: https://online.stat.psu.edu/stat501/lesson/4/4.1 [5]What do normal residuals tell you about your data: https://stats.stackexchange.com/questions/54533/what-do-normal-residuals-mean-and-what-does-this-tell-me-about-my-data [6] Wikipedia on linear regression (it's actually pretty good): https://en.wikipedia.org/wiki/Linear_regression#Assumptions [7] Better understanding of "Linear in parameters": https://datascience.stackexchange.com/questions/12274/what-does-linear-in-parameters-mean MATH COURSES (7 day free trial) 📕 Mathematics for Machine Learning: https://imp.i384100.net/MathML 📕 Calculus: https://imp.i384100.net/Calculus 📕 Statistics for Data Science: https://imp.i384100.net/AdvancedStatistics 📕 Bayesian Statistics: https://imp.i384100.net/BayesianStatistics 📕 Linear Algebra: https://imp.i384100.net/LinearAlgebra 📕 Probability: https://imp.i384100.net/Probability OTHER RELATED COURSES (7 day free trial) 📕 ⭐ Deep Learning Specialization: https://imp.i384100.net/Deep-Learning 📕 Python for Everybody: https://imp.i384100.net/python 📕 MLOps Course: https://imp.i384100.net/MLOps 📕 Natural Language Processing (NLP): https://imp.i384100.net/NLP 📕 Machine Learning in Production: https://imp.i384100.net/MLProduction 📕 Data Science Specialization: https://imp.i384100.net/DataScience 📕 Tensorflow: https://imp.i384100.net/Tensorflow