Salesforce Marketing Cloud uses AI to segment
Posted: Tue Feb 18, 2025 8:38 am
Applying AI helps businesses optimize processes, improve customer experience, and create competitive advantages. What is Machine Learning? Machine Learning is a subset of Artificial Intelligence (AI) that uses computer algorithms to analyze data and make intelligent decisions based on what it has learned.
Instead of following fixed rule-based algorithms, Machine Learning builds models to classify and make predictions from data. For example: To determine whether a heart is failing or not, we can use Machine Learning to analyze data sets such as heart beats per minute, body mass index, age, gender, and the outcome of whether greece whatsapp number data the heart is failing or not.
Machine Learning will learn and create a model that can predict the outcome based on the input data. The Difference Between Machine Learning and Traditional Algorithms Traditional Algorithm: Uses data and rules to develop an algorithm that gives an answer.
This algorithm does not change. Machine Learning: Machine Learning models will automatically determine rules and conditional statements when receiving input data. This model can be continuously trained and used to predict future values.
Instead of following fixed rule-based algorithms, Machine Learning builds models to classify and make predictions from data. For example: To determine whether a heart is failing or not, we can use Machine Learning to analyze data sets such as heart beats per minute, body mass index, age, gender, and the outcome of whether greece whatsapp number data the heart is failing or not.
Machine Learning will learn and create a model that can predict the outcome based on the input data. The Difference Between Machine Learning and Traditional Algorithms Traditional Algorithm: Uses data and rules to develop an algorithm that gives an answer.
This algorithm does not change. Machine Learning: Machine Learning models will automatically determine rules and conditional statements when receiving input data. This model can be continuously trained and used to predict future values.