In our previous article Implementing PCA in Python with Scikit-Learn, we studied how we can reduce dimensionality of the feature set using PCA. In this article we will study another very important dimensionality reduction technique: linear discriminant analysis (or LDA). But first let's briefly discuss how PCA and LDA differ
With the availability of high performance CPUs and GPUs, it is pretty much possible to solve every regression, classification, clustering and other related problems using machine learning and deep learning models. However, there are still various factors that cause performance bottlenecks while developing such models. Large number of features in
State management is a term that will always come to mind whenever dealing with an application data structure.
The biggest problem in the development and maintenance of large-scale software systems is complexity - large systems are hard to understand.
Reactive programming is when we react to data being streamed