There are additional components of the workshop which explore building machine learning pipelines and unsupervised learning. We'll demonstrate how to perform these tasks using scikit-learn, the main ...

Learn about some of the best Python libraries for programming Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL).

This is a beginner-friendly program, with a recommended background of at least high school mathematics. We also recommend a basic familiarity with Python, as labs use Python to demonstrate learning ...

I use Python 3 and Jupyter Notebooks to generate plots and equations with linear regression on Kaggle data. I checked the correlations and built a basic machine learning model with this dataset.

The key to a successful kernel ridge regression model is understanding kernel functions. The demo program uses the radial basis function (RBF) kernel with a gamma value of 1.0. Basic linear regression ...

The Data Science Lab. Regression Using a scikit MLPRegressor Neural Network. Dr. James McCaffrey of Microsoft Research uses a full-code, step-by-step demo to show how to predict the annual income of a ...

We went through a hands-on Python implementation on solving a linear regression problem that has normally distributed data. Users can do more practice by solving their machine learning problems with ...