Introduction: Kotlin, the versatile and powerful programming language, has taken the development world by storm. Its concise syntax, seamless interoperability with Java, and robust features have made it a favorite among developers. In this article, we will delve into the top 10 Kotlin best practices that will not only elevate your coding skills but also boost your app’s performance and...
Introduction: When Computers Were Human by NASA’s Marshall Space Flight Center is licensed under CC-BY-NC 2.0 In the fast-paced world of technology, staying ahead of the curve is crucial for aspiring programmers. As the demand for software developers continues to surge, knowing which programming languages are most sought-after can give you a competitive edge in the job market. In this...
When working on machine learning problems, sometimes you want to construct your own custom loss function(s). This article will introduce abstract Keras backend for that purpose. Keras loss functions From Keras loss documentation, there are several built-in loss functions, e.g. mean_absolute_percentage_error, cosine_proximity, kullback_leibler_divergence etc. When compiling a Keras model, we often...
Topic modelling is a type of statistical modelling for discovering the abstract “topics” that occur in a collection of documents. Latent Dirichlet Allocation (LDA) is an example of a topic model and is used to classify text in a document to a particular topic. It builds a topic per document model and words per topic model, modelled as Dirichlet distributions. Here, we are...
These are completely different methods in machine learning. The fact that they both have the letter K in their name is a coincidence. K-means is a clustering algorithm that tries to partition a set of points into K sets (clusters) such that the points in each cluster tend to be near each other. It is unsupervised because the points have no external classification. The typical k-means...