Whats the Difference Between Artificial Intelligence, Machine Learning, and Deep Learning?
Artificial Intelligence (AI), Machine Learning and Deep Learning are popular terms.
But what’s in a name?
These phrases are mixed as if they were interchangeable, because they all surround several technologies that use datainterpretation to solve problems.
The key concepts behind these terms are very different. Here is a general description of these technologies.
Related course: Machine Learning Intro for Python Developers
Artificial Intelligence refers to the ability of a machine to perform complex tasks, it is a generic term. Often these are software based on algorithms that are capable of cognitive computing.
This includes robotics, the processing of natural languages, machine learning, and profound learning.
The exponential gains in computing power have led to an explosion of AI applications.
What you’d see in science fiction is now part of everyday life.
Machines can now perform complex tasks without human intervention.
The two best-known forms of this are machine learning and deep learning.
The idea of machine learning dates back to the late 1950s. It started when a computer scientist at Stanford, he thought: instead of humans teaching computers, machines could learn by themselves.
The learning process takes data, and with the large amount of data generated online, this took off.
Machine Learning consists algorithms that analyze and learn from the data.
These algorithms enable the software to make predictions and associations.
This is unlike traditional programming, where the software relied on manually coded software routines.
Real World Example:
To prevent fraud, machine learning helps identify and react to patterns, behaviors and risk trends. It uses training data to do so.
Deep learning refers to a particular class of machine learning and artificial intelligence.
Deep Learning is based on Neural Networks.
Neural networks were created in the 1950s, they are inspired by the model of the biology of the human brain.
If we said that machine learning is a branch of artificial intelligence, deep learning is a branch of machine learning.
Deep learning is a set of machine learning algorithms that use complex neural networks capable of learning from experience. These systems must be trained on the basis of existing examples.
How does it work?
In Neural Networks, Artificial Neurons are grouped into layers. The information flows unidirectionally. Each neuron in a layer communicates with the rest until the end of the network is reached. The result is the capacity for deep learning to feed a computer system using a large amount of data for complex decision making.