Training Data for Machine Learning Algorithms Done Right!

There are lots of differences between traditional statistical modeling and machine learning. Machine learning depends on computer algorithms, few estimates, and small to large datasets to produce predictions of high accuracy. Statistical modeling, on the other hand, depends on human talents, mathematical equations, and many assumptions to predict the "best estimate." The amount of training data needed to build a comprehensive machine learning model is highly debated. The type of data determines the number of features.