Keras Functional API is a way to build more complex models in Keras that go beyond the simple sequential model structure. It allows creating models with multiple inputs and outputs, shared layers, and more flexible architectures. Instead of the linea...
Transfer learning is a machine learning technique where knowledge gained from one task is applied to another related task. It involves using a pretrained model, trained on a large dataset, as a starting point for a new task. The pretrained model's le...
In simple words, a CNN (Convolutional Neural Network) "sees" or interprets visual information by analyzing patterns and features at different levels of abstraction. At the initial layers, the CNN captures low-level features like edges and textures. A...
Pretrained models are used because they offer a shortcut to building accurate models. They are already trained on massive datasets, learning rich patterns and representations. By using pretrained models, we can save time and effort required for train...
Data augmentation is a technique used to expand and diversify a training dataset by applying various modifications to existing data. These modifications can include flipping, rotation, cropping, scaling, adding noise, or adjusting brightness and cont...
Backpropagation in CNN (Convolutional Neural Networks) is an algorithm used to train the network by adjusting the weights and biases based on the error calculated during the forward pass. It involves two main steps: forward pass and backward pass. Du...
