API integration is a feature that allows different software systems, platforms, or applications to seamlessly communicate with each other. It enables the exchange of data, functionality, a...read more
Neural network architecture refers to the structure and design of artificial neural networks, which are computer systems inspired by the human brain. At its core, a neural network consists...read more
Pattern recognition in neural networks involves teaching the network to identify and categorize patterns in data. This process begins by feeding the network a large set of examples, called...read more
Data visualization in neural networks involves using graphical techniques to represent data and model performance. It helps users understand how the network operates and makes decisions by...read more
Model deployment is the process of taking a trained AI model and making it available for use in real-world applications. Once the model has learned to create content—like text, images, or ...read more
Parameter tuning in neural networks refers to the process of improving the model’s performance by adjusting its internal settings, specifically the weights, to minimize prediction errors. ...read more
Data handling refers to the processes involved in preparing and managing the data used for training, validating, and testing the model. Data handling includes several steps: first, data co...read more
Debugging tools help developers identify and fix issues in their models during the training and testing phases. When a neural network doesn’t perform as expected, debugging tools provide i...read more
Transfer learning is a powerful technique in artificial neural networks that allows a model to leverage knowledge gained from one task and apply it to another related task. Instead of trai...read more
