The pros and cons of various data splitting techniques in Python — In Machine Learning, the first step towards a better-performing model is clean, relevant data. As the saying goes, “garbage in, garbage out.” If your model is trained on “bad data,” (noisy, redundant, irrelevant, or dirty data) it will learn the patterns of this messy data and will not perform as…