In supervised learning we have a set of training data as an input and a set of labels or "correct answers" for each training set as an output. Then we're training our model (machine learning algorithm ...

This Github repository contains a Jupyter Notebook that implements the basic gradient descent algorithm, a popular optimization algorithm used in machine learning for training various models, such as ...

Businesspeople need to demand more from machine learning so they can connect ... The primary goal of a linear regression training algorithm is to compute coefficients that make the difference ...

Now that you have a solid foundation in Supervised Learning, we shift our attention to uncovering the hidden structure from unlabeled data. We will start with an introduction to Unsupervised Learning.

The simplest and fastest algorithm is linear (least squares) regression, but you shouldn’t stop there, because it often gives you a mediocre result. Other common machine learning regression ...

The experiment for all the selected machine learning algorithm applied using anaconda IDE in Jupyter lab environment. As a result R-square of linear regression scores 0.95 and MLP scores 0.83 where as ...