Foundation CSS is an open-source and responsive front-end framework built by ZURB foundation in September 2011, that makes it easy to layout stunning responsive websites, apps, and emails that appear amazing and can be accessible to any device. It is used by many companies such as Facebook, eBay, Mozilla, Adobe, and even Disney. The framework is built on Saas-like bootstrap. It is more sophisticated, flexible, and easily customizable. It also comes with CLI, so it’s easy to use it with module bundlers. It offers the Fastclick.js tool for faster rendering on mobile devices. In this article, we will discuss the Kitchen Sink Switch in Foundation CSS....
Machine learning is a prominent technology in this modern world and as years go by it is growing immensely. There are several components involved in Machine Learning that make it evolve and solve various problems and one such crucial component that exists is the Perceptron. In this article, we will be learning about what a perceptron is, the history of perceptron, and how one can use the same with the help of the Scikit-Learn, library which is arguably one of the most popular machine learning libraries in Python....
In this article, we will learn about the Prior and Posterior Gaussian Processes for Different kernels. But first, let’s understand what is Prior and Posterior Gaussian Processes are. After that, we will use the sci-kit learn library to see the code implementation for the same in Python....
Mockito is an open-source testing framework used for unit testing of Java applications. It plays a vital role in developing testable applications. Mockito is used to mock interfaces so that a dummy functionality can be added to a mock interface that can be used in Unit Testing. Unit Testing is a type of software testing in which individual software components are tested. The primary objective of using the Mockito framework is to simplify the development of a test by mocking external dependencies and using them in the test code. And as a result, Mockito provides a simpler test code that is easier to understand, more readable, and modifiable. Mockito can also be used with other testing frameworks like JUnit and TestNG. So in this article, we will discuss the differences between @Mock and @InjectMocks which are the two most important and confusing annotations that are available in the Mockito framework....
Regression modelling plays a crucial role in predicting numerical outcomes and understanding the relationships between variables. One key aspect of building robust regression models is the careful consideration of the target variable, as its distribution and characteristics can significantly impact model performance. In this article, we will discuss the effect of transforming the targets in regression modelling and their benefits....
In machine learning, optimizers and loss functions are two components that help improve the performance of the model. A loss function measures the performance of a model by measuring the difference between the output expected from the model and the actual output obtained from the model. Mean square loss and log loss are some examples of loss functions. The optimizer helps to improve the model by adjusting its parameters so that the loss function value is minimized. SGD, ADAM, and RMSProp are some examples of optimizers. The focus of this article will be the various loss functions supported by the SGD module of Sklearn. Sklearn provides two classes of SGD: SGDClassifier for classification tasks and SGDRegressor for regression tasks....
In the modern world, machine learning and data analysis are essential for seeing patterns, connections, and structures in huge datasets. A powerful method for dimensionality reduction and grouping is spectral embedding. This extensive lesson will walk you through Spectral Embedding from its fundamentals to practical implementation, giving novices a clear grasp while making sure you have all the knowledge you require....
Machine learning is an effective tool for predicting numerical values, and regression is one of its key applications. In the arena of regression analysis, accurate estimation is crucial for measuring the overall performance of predictive models. This is where the famous machine learning library Python Scikit-Learn comes in. Scikit-Learn gives a complete set of regression metrics to evaluate the quality of regression models....
In this article, we are going to see how to convert sklearn dataset to a pandas dataframe in Python....
In this article, we shall play around with pixel intensity value using Machine Learning Algorithms. The goal is to perform a Color Quantization example using KMeans in the Scikit Learn library....
Anaconda is a powerful platform widely used in the Python community for managing packages, dependencies, and environments. One of the most popular libraries for machine learning tasks in Python is scikit-learn. However, it’s crucial to keep your libraries up to date to leverage the latest features, bug fixes, and performance improvements. In this article, we’ll explore how to upgrade the scikit-learn package within the Anaconda environment....
In this article we will implement a classification model using Scikit learn implementation for SVM model in Python. Then we will try to understand what is a kernel and how it can helps us to achieve better performance by learning non-linear boundaries in the dataset....
