AI
Machine Learning
Machine learning (ML) is a branch of artificial intelligence (AI) that focuses on creating algorithms and models capable of automatically learning from data. Unlike systems based on explicit rules, ML methods recognize patterns and relationships within data sets and use that information to make predictions.
Unsupervised learning
Unsupervised learning is one of the main methodologies that powers artificial intelligence.
Strong AI and Weak AI
Weak AI, often also called Narrow AI, represents systems designed to carry out specific tasks without any claim to general understanding. Strong AI, by contrast, refers to systems endowed with a level of intelligence comparable to that of humans.
Feature Engineering
Feature engineering consists in transforming raw data—SQL tables, CSV files, sensor logs, text, audio—into numerical or categorical variables that maximise a model’s ability to generalise.
Supervised learning
Supervised learning is one of the fundamental techniques of machine learning.
How AI works
When we hear about AI we think of machines capable of “reasoning”: here we explain how models, data and computation combine to produce intelligent results.
When AI was born
Artificial intelligence has its roots in 1956, when J. McCarthy organised the Dartmouth workshop that coined the term “Artificial Intelligence”.
Software List
Text creation Data analysis Video Creation Video Transcription Video Optimization Product Optimization Advertising Sales ProductivityCategories
Author
Nicolò Caiti
I have made MarTech my profession. I work with artificial intelligence applied to digital marketing. In this blog, I examine how AI is transforming the sector—improving web performance, optimising digital strategies, and speeding up everyone’s work. With years of experience in marketing automation and advanced customer-journey management, I share practical insights, case studies, and best practices to help people harness AI’s full potential in their own roles.
I hope you find the answers you’re looking for!