Dr. James McCaffrey of Microsoft Research provides a full-code, step-by-step machine learning tutorial on how to use the LightGBM system to perform multi-class classification using Python and the ...

Discover how to build an automated intent classification model by leveraging pre-training data using a BERT encoder, BigQuery, and Google Data Studio.

Xilinx introduced a medical X-ray classification deep-learning model and a reference design kit, in association with Spline.AI on AWS.

Arguably the most powerful multi-class classification technique is a neural network model. There are several tools and code libraries that you can use to create a neural network classifier.

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.