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The Adapter Design Pattern is a popular Structural Design Pattern used in software engineering. This guide looks at how we can implement the Adapter Design Pattern in Python. Design Patterns are template-like solutions - practically recipes for solving recurring, common problems in software development. The Adapter Pattern is based upon...
Guest Contributor
Counting the number of word occurrences in a string is a fairly easy task, but has several approaches to doing so. You have to account for the efficiency of the method as well, since you'll typically want to employ automated tools when you don't want to perform manual labor -...
David Landup
Thresholding is a simple and efficient technique to perform basic segmentation in an image, and to binarize it (turn it into a binary image) where pixels are either 0 or 1 (or 255 if you're using integers to represent them). Typically, you can use thresholding to perform simple background-foreground segmentation...
The learning rate is an important hyperparameter in deep learning networks - and it directly dictates the degree to which updates to weights are performed, which are estimated to minimize some given loss function. In SGD: $$ weight_{t+1} = weight_t - lr * \frac{derror}{dweight_t} $$ With a learning...
By setting the focus on an element, we gently guide a user to the next expected input field, giving them a better browsing experience with less guesswork. In this article, we will learn how to set focus on an element after rendering our React application or a React component. In...
Joel Olawanle
When developing web applications - we routinely access resources hosted on a server. Asking for, sending, or performing other operations on resources is accomplished through HTTP requests. These requests are sent from the client to a host on a server. When making HTTP request, the client employs a URL (Uniform...
Improving the performance of a training loop can save hours of computing time when training machine learning models. One of the ways of improving the performance of TensorFlow code is using the tf.function() decorator - a simple, one-line change that can make your functions run significantly faster. In this...
Felipe Antunes
Data augmentation has, for a long while, been serving as a means of replacing a "static" dataset with transformed variants, bolstering the invariance of Convolutional Neural Networks (CNNs), and usually leading to robustness to input. Note: Invariance boils down to making models blind to certain perturbations, when making...
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