neural network Antonyms
No Synonyms and anytonyms found
Meaning of neural network
neural network (n)
computer architecture in which processors are connected in a manner suggestive of connections between neurons; can learn by trial and error
any network of neurons or nuclei that function together to perform some function in the body
neural network Sentence Examples
- The neural network analyzed the medical data, identifying patterns that would have been impossible to detect manually.
- The self-driving car relied on a complex neural network to process sensory input and make decisions in real-time.
- Researchers trained the neural network on millions of images, enabling it to recognize and classify objects with astonishing accuracy.
- The neural network's ability to learn and improve made it an ideal solution for the challenging task of natural language processing.
- The financial institution used a neural network to analyze market trends, reducing risk and maximizing profits.
- The neural network's hierarchical structure allowed it to extract complex features from the input data.
- The hardware accelerated the neural network's processing speed, enabling it to handle vast volumes of data in real-time.
- The neural network's weights and biases were carefully optimized to minimize error and improve performance.
- The neural network's activation functions introduced non-linearity, allowing it to model complex relationships in the data.
- The neural network's predictions became more accurate over time, as it continuously learned and refined its understanding of the world.
FAQs About the word neural network
computer architecture in which processors are connected in a manner suggestive of connections between neurons; can learn by trial and error, any network of neur
No synonyms found.
No antonyms found.
The neural network analyzed the medical data, identifying patterns that would have been impossible to detect manually.
The self-driving car relied on a complex neural network to process sensory input and make decisions in real-time.
Researchers trained the neural network on millions of images, enabling it to recognize and classify objects with astonishing accuracy.
The neural network's ability to learn and improve made it an ideal solution for the challenging task of natural language processing.
