Machine learning offers immense opportunities, and Introducing Machine Learning delivers practical knowledge to make the most of them. Dino and Francesco Esposito start with a quick overview of the foundations of artificial intelligence and the basic steps of any machine learning project. Next, they introduce Microsoft’s powerful ML.NET library, including capabilities for data processing, training, and evaluation. They present families of algorithms that can be trained to solve real-life problems, as well as deep learning techniques utilising neural networks. The authors conclude by introducing valuable runtime services available through the Azure cloud platform and consider the long-term business vision for machine learning.

14-time Microsoft MVP Dino Esposito and Francesco Esposito help you

Explore what’s known about how humans learn and how intelligent software is built
Discover which problems machine learning can address
Understand the machine learning pipeline: the steps leading to a deliverable model
Use AutoML to automatically select the best pipeline for any problem and dataset
Master ML.NET, implement its pipeline, and apply its tasks and algorithms
Explore the mathematical foundations of machine learning
Make predictions, improve decision-making, and apply probabilistic methods
Group data via classification and clustering
Learn the fundamentals of deep learning, including neural network design
Leverage AI cloud services to build better real-world solutions faster