An AI startup with limited computational resources is building an image classifier. They don't have the capability to train a deep neural network from scratch. What approach can they use to leverage the capabilities of deep learning without the extensive training time?
- Transfer learning
- Reinforcement learning
- Genetic algorithms
- Random forest classifier
Transfer learning allows the startup to use pre-trained deep neural networks (e.g., a pre-trained CNN) as a starting point. This approach significantly reduces training time and computational resources, while still benefiting from the capabilities of deep learning.
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