How does deep learning work?

Deep learning is a subset of machine learning based on artificial neural networks that imitate the human brain's behavior and learning patterns. It consists of multiple layers of interconnected nodes, or artificial neurons, which process and communicate information to make predictions or decisions. Deep learning algorithms learn by continuously adjusting the weights and biases of these connections through a process called backpropagation. This allows the network to iteratively improve its performance, extracting high-level features from raw data in an automated manner. By leveraging large amounts of labeled training data, deep learning models can discern complex patterns, recognize objects, understand speech, and even generate creative content. The ability of deep learning to autonomously learn and adapt to data makes it a powerful tool across various domains, revolutionizing fields like computer vision, natural language processing, and robotics.
This mind map was published on 20 August 2023 and has been viewed 86 times.

You May Also Like

What are the main series in the Ben 10 franchise?

What is Article 16 of the Indian Constitution?

What types of services can be monitored?

What is the scientific approach to studying handwritten digit recognition?

What are the key factors influencing handwritten digit recognition?

What are the effective strategies for improving handwritten digit recognition?

How does the human brain recognize handwritten digits?

What are the limitations of current scientific studies on handwritten digit recognition?

What are the advantages and limitations of graph neural networks?

How do graph neural networks represent graph structures?

What are some popular applications of graph neural networks?