Machine learning is a method of data analysis that automates analytical model building. It is a branch of artificial intelligence based on the idea that systems can learn from data, identify patterns and make decisions with minimal human intervention.
Why is Machine Learning important?
The iterative aspect of Machine Learning is important because as models are exposed to new data, they are able to independently adapt. They learn from previous computations to produce reliable, repeatable decisions and results.
What’s required to create good machine learning systems?
-Data preparation capabilities.
-Algorithms-basic and advanced.
-Automation and iterative processes.
-Scalability.
-Ensemble modelling.
What is a machine learning model?
A Machine Learning Model can be a mathematical representation of a real-world process. The learning algorithm finds patterns in the training data such that the input parameters correspond to the target. The output of the training process is a machine learning model which you can then use to make predictions.
What is a machine learning algorithm?
Machine learning algorithms build a mathematical model based on sample data, known as “training data”, in order to make predictions or decisions without being explicitly programmed to perform the task.
Top comments (0)