Artificial Neural Networks (ANNs)
Learn about the basics of ANNs, how they work, and how you can use them in your own projects
Artificial Neural Networks (ANNs) are a type of machine learning algorithm that are modeled after the structure and function of the human brain. ANNs are used to solve a wide variety of problems, from image recognition and natural language processing to stock market prediction and autonomous driving. They are designed to automatically learn from data, making them a powerful tool for data analysis and modeling.
Let’s look at the basics of ANNs and how they work.
What are ANNs?
At a high level, an ANN is composed of a series of interconnected nodes, or “neurons,” that process and transmit information. Each neuron receives inputs from other neurons and produces an output that is passed along to other neurons in the network.
Each neuron in an ANN has a set of weights that determine the strength of its connection to other neurons. During the training process, the weights are adjusted to minimize the error between the network’s predicted output and the actual target values.
This process of adjusting the weights is known as backpropagation, and it’s how the network “learns” from the data. The network…
