Neurons and neural networks are the basic building blocks of deep learning models. Neurons are inspired by the biological neurons in the human brain, while neural networks are interconnected networks of neurons. …

Deep learning is a type of machine learning that uses artificial neural networks to learn from data. Neural networks are inspired by the structure and function of the human brain, and they are able to learn complex patterns from large amounts of data. Deep learning has been used to achieve…

No , it is not a gen-z slang . YOLO (You Only Look Once) is a popular object detection algorithm that has revolutionized the field of computer vision. It is fast and efficient, making it an excellent choice for real-time object detection tasks. WHAT IS YOLO (you look only once) ? YOLO (You Only Look Once) is a…

WHAT IS IMAGE CLASSIFICATION ? — Image classification is the task of assigning a label or category to an entire image. It is a fundamental task in computer vision, with applications in a variety of fields, including: Image search: Image classification can be used to organize and categorize photo galleries, making it easier for users to…

WHAT IS CONVULATIONAL PADDING? — Convolutional padding is the process of adding extra pixels to the edges of an input image before performing the convolution operation. This can be done to preserve the spatial dimensions of the output image, or to control the receptive field of the convolutional layer. The most common type of padding…

WHAT IS COMPUTER VISION? — Computer vision is a field of artificial intelligence (AI) that enables computers and systems to derive meaningful information from digital images, videos and other visual inputs — and take actions or make recommendations based on that information. …

Convolutional Neural Networks (CNNs) are a type of artificial neural network (ANN) that are particularly well-suited for image recognition and processing tasks. CNNs are inspired by the structure of the human visual cortex, which is the part of the brain that is responsible for processing visual information. CNNs are made…

What is imbalanced data ? — Imbalanced data in deep learning is a common problem where the target class has an uneven distribution of observations, i.e. one class label has a very high number of observations and the other has a very low number of observations. For example, in a fraud detection dataset, the majority class…

Dropout regularization is a technique used to prevent overfitting in deep learning models. Overfitting occurs when a model learns the training data too well and is unable to generalize to new data. …