Machine Learning
Showing 85–96 of 116 results
Machine Learning: Clustering with K-Means
Level up your machine learning skills by using unsupervised learning to find patterns hidden in data.
Machine Learning: Introduction with Regression
Get started with machine learning and learn how to build, implement, and evaluate linear regression models.
Machine Learning: K-Nearest Neighbors
Sharpen your machine learning skills by learning how to prepare, implement, and assess the K-Nearest Neighbors algorithm.
Machine Learning: Logistic Regression
Predict the probability that a datapoint belongs to a given class with Logistic Regression.
Machine Learning: Perceptrons
Level up your machine learning skills by learning how to build perceptrons: the foundations of neural networks.
Machine Learning: Random Forests & Decision Trees
Learn how to build decision trees and then build those trees into random forests.
Machine Learning/AI Engineer
Machine Learning/AI Engineers build end-to-end ML applications and power many of the apps we use every day. They work in Python, Git, & ML.
Market Basket Analysis in Python
Explore association rules in market basket analysis with Python by bookstore data and creating movie recommendations.
MLOps Concepts
Discover how MLOps can take machine learning models from local notebooks to functioning models in production that generate real business value.
MLOps Deployment and Life Cycling
In this course, you’ll explore the modern MLOps framework, exploring the lifecycle and deployment of machine learning models.
MLOps for Business
Learn about MLOps, including the tools and practices needed for automating and scaling machine learning applications.
Model Validation in Python
Learn the basics of model validation, validation techniques, and begin creating validated and high performing models.