The steps to follow to use machine learning models are: In “fit” and “predict” steps, you can use several models, and evaluate them, to keep the most performing one. Python libraries: Here, we train a model to guess a comfortable boot size for a dog, based on the size of the harness that fits them:…
Feature scaling is considered a part of the data processing cycle that cannot be skipped, so that we can achieve stable and fast training of our ML algorithm. eature Scaling is a technique to standardize the independent features present in the data in a fixed range. It is performed during the data pre-processing to handle…
A model is overfit if it works better on training data than it does on other data. verfitting can be avoided in several ways. The simplest way is to have a dataset that’s a better representation of what is seen in the real world. A complimentary way we can avoid overfitting is to stop training…
