Key Points
- Neural networks are a type of machine learning model that is inspired by the structure and function of the human brain.
- Neural networks are made up of interconnected nodes called neurons that work together to process and analyze complex data.
- Neural networks can be used for a wide variety of tasks, such as image recognition, speech recognition, natural language processing, and predictive modeling, and have become increasingly popular due to their ability to achieve state-of-the-art performance on a wide range of problems.
One minute overview
A neural network is a type of machine learning model that is inspired by the structure and function of the human brain. It is a computational system that is made up of interconnected nodes, called neurons, that work together to process and analyze complex data.
In a neural network, data is fed into the input layer, which is then processed by one or more hidden layers of neurons, and finally produces an output. Each neuron in the network is connected to other neurons through weighted connections, which determine the strength of the signal passed between them. The weights are adjusted during training to optimize the performance of the network.
Learning
You can learn how easy it is to build a nueral network from scratch using this 30 minute tutorial. The tools used are free and all you need is a web browser.
