IntroductionThresholding is a simple and efficient technique to perform basic segmentation in an image, and to binarize it (turn it into a binary image)...

IntroductionThresholding is a simple and efficient technique to perform basic segmentation in an image, and to binarize it (turn it into a binary image)...

The learning rate is an important hyperparameter in deep learning networks - and it directly dictates the degree to which updates to weights are...

IntroductionBy setting the focus on an element, we gently guide a user to the next expected input field, giving them a better browsing experience...

IntroductionWhen developing web applications - we routinelly access resources hosted on a server. Asking for, sending, or performing other operations on resources is accomplished...

IntroductionImproving the performance of a training loop can save hours of computing time when training machine learning models. One of the ways of improving...

Data augmentation has, for a long while, been serving as a means of replacing a "static" dataset with transformed variants, bolstering the invariance of...

IntroductionA dictionary in Python is a collection of items that stores data as key-value pairs. In Python 3.7 and later versions, dictionaries are sorted...

IntroductionTo work with stored data, file handling becomes the core knowledge of every professional Python programmer. Right from its earliest release, both reading and...

IntroductionPython programmers intensively use arrays, lists, and dictionaries as serialized data structures. Storing these data structures persistently requires either a file or a database...

IntroductionSometimes confused with linear regression by novices - due to sharing the term regression - logistic regression is far different from linear regression. While...

IntroductionObject detection is a large field in computer vision, and one of the more important applications of computer vision "in the wild". Object detection isn't...