In this project, we will be using scikit-learn pipelines to train our random forest algorithm and build a drug classifier. After training, we will automate the evaluation process using CML. Finally, ...

For a supervised machine learning project, you will need to label the data in a meaningful way for the outcome you are seeking. In Table 1, note that each row of the house record includes a label ...

This article looks at 13 open source projects that are remaking the world of AI and machine learning. Some are elaborate software packages that support new algorithms. Others are more subtly ...

In this paper, we present an overview of a project-based course on MLOps by showcasing a couple of sample projects developed by our students. Additionally, we s. Training Future Machine Learning ...

Data cleaning and Exploratory Data Analysis (EDA) might not seem glamorous, but the process is vital for guiding your real-world data projects. The chances are that you have heard of linear regression ...

Examine how to build explainability in a machine learning project; Find out more. Customised solutions. ... Related training. AI integration into operational risk management. Date. November 4–6, 2025 ...

Humanity’s latest, greatest invention is stalling right out of the gate. Machine learning projects have the potential to help us navigate our most significant risks — including wildfires ...