Deep learning is a subset of machine learning that structures algorithms in layers to create an "artificial neural network" that can learn and make intelligent decisions on its own.
Key Concepts
- Neural Networks: Deep learning uses neural networks, which are inspired by the human brain's structure and function.
- Layers: Neural networks consist of layers, including input, hidden, and output layers.
- Activation Functions: These functions help determine whether a neuron should be activated or not.
- Backpropagation: This is the process of adjusting the weights of the neurons to improve the accuracy of the model.
Applications
- Image Recognition: Deep learning models can recognize objects in images, such as identifying a cat in a photo.
- Speech Recognition: These models can convert spoken words into written text.
- Natural Language Processing: Deep learning is used to understand and generate human language.
Resources
For more in-depth tutorials and resources, check out our Deep Learning Tutorials.
Image
Here's an example of a deep learning model in action:
Neural Network
If you're interested in learning more about neural networks, you might want to explore Neural Network Architecture.