Logistic regression is an approach to supervised machine learning that models selected values to predict possible outcomes. In this course, Notre Dame professor Frederick Nwanganga provides you with a ...

Python has a plethora of machine learning libraries, but the top 5 libraries are TensorFlow, Keras, PyTorch, Scikit-learn, and Pandas. These libraries offer a wide range of tools for various ...

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

The time-tested technique for predicting numbers, and the role of domain knowledge in machine learning.

Scikit-learn - It is a machine learning library that enables tools for used for many other machine learning algorithms such as classification, prediction, etc. Pickle- The pickle module is used for ...

Dr. James McCaffrey presents a complete end-to-end demonstration of linear regression using JavaScript. Linear regression is ...

Machine learning uses algorithms to turn a data set into a model that can identify patterns or make predictions from new data. Which algorithm works best depends on the problem.

Unlike most other machine learning regression systems, when using LightGBM, numeric predictor and target variables can be used as-is. You can normalize numeric predictors using min-max, z-score, or ...