Term
Deep Learning (ˈdiːp ˈlɜːnɪŋ)
Definition
Deep Learning is a type of machine learning that uses complex, multi-layered networks called neural networks. It allows computers to learn from data in a way that mimics human learning, tackling intricate tasks like recognizing objects in pictures or understanding spoken words.
Where you’ll find it
In AI platforms, Deep Learning is typically found in the tools or libraries for building and training AI models. It may not be available in all subscription plans, and its features could vary depending on the platform’s version or the specific AI capabilities it supports.
Common use cases
- Automating tasks: Such as sorting images or converting speech to text.
- Enhancing user interactions: Through chatbots and voice-activated assistants that understand natural language.
- Improving data analysis: By identifying patterns and insights that are not easily visible to humans.
Things to watch out for
- High resource requirements: Training deep learning models usually needs significant computational power, often requiring advanced GPUs or cloud-based platforms.
- Data privacy: When using personal data, especially in tasks like facial or voice recognition, managing and protecting user data is crucial.
- Overfitting: This occurs when a model learns the detail and noise in the training data to an extent that it negatively impacts the model’s performance on new data.
Related terms
- Neural Networks
- Machine Learning
- Image Recognition
- Speech Recognition
- AI Models