First, what is AI?
Proponents of artificial intelligence say they hope to somedaycreate a machine that can thinkfor itself.
This is where ML and DL come in.
Photo: Login (Shutterstock)
One IBM engineer, Jeff Crume,explainsmachine learning as a very sophisticated form of statistical analysis.
According to Crume, this analysis allows machines to make predictions or decisions based on data.
As previously stated, machine learning encompasses a broad variety of activities.
Deep learning, explained
Deep learning is machine learning.
Unlike some other forms of machine learning, DL seeks to allow algorithms to do much of their work.
DL is fueled by mathematical models known as artificial neural networks (ANNs).
These networks seek to emulate the processes that naturally occur within the human brainthings like decision-making and pattern identification.
Machine learning relies on huge amounts of training data.
When it comes to DL, meanwhile, a machineengages in a process called unsupervised learning.
In a neural web connection, nodes are arranged in an organized form that is referred to as layers.
Thus, deep learning networks involve multiple layers of nodes.
Another key concept in ANNs is the weight, whichone commentator comparesto the synapses in a human brain.
Weights are informational inputs that help calibrate a neural data pipe so that it can make decisions.
It then adds the resulting products together, yielding a single number.
If that number is below a threshold value, the node passes no data to the next layer.
Why is machine learning important for AI development?
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