Predictive Maintenance: Predicting Machine Failure using Sensor Data with XGBoost and Python
Predictive maintenance is a game-changer for the modern industry. Still, it is based on a simple idea: By using machine … Read more
Classification (multi-class)
Here you’ll find all articles that address multi-class classification problems.
Multi-class classification is a machine learning task in which the goal is to classify data into more than two classes or categories. There are many algorithms and approaches that can solve this type of classification problem. Examples include predicting the type of animal in an image or classifying text documents into different categories. Training a multiclass machine learning model is basically the same as in binary classification. However, usually, there is more data required, and preparing the data can grow more complex. This is because the training data needs to include a sufficient number of cases in each class.
How to Measure the Performance of a Machine Learning Classifier with Python and Scikit-Learn?
Have you ever received a spam email and wondered how your email provider was able to identify it as spam? … Read more
Predictive Policing: Preventing Crime in San Francisco using XGBoost and Python
In this tutorial, we’ll be using machine learning to predict and map out crime in San Francisco. We’ll be working … Read more
Training a Sentiment Classifier with Naive Bayes and Logistic Regression in Python
Are you ready to learn about the exciting world of social media sentiment analysis using Python? In this article, we’ll … Read more