In today’s data-focused landscape, Generative AI is often viewed as a magic solution for every analytical need, from generating tailored insights to creating automated reports. On tech forums and user groups, queries like, “Is there an AI tool for [specific… Continue Reading →
Data analysis is a dynamic field with endless opportunities, but for many newcomers, the transition from theory to real-world practice can be daunting. While formal education and technical training lay a strong foundation, practical experience is the key to becoming a proficient data analyst.
In this article, we’ll explore how to bridge the gap between theoretical knowledge and hands-on expertise based on lessons learned in depth within our latest guide on the topic, Solve Any Data Analysis Problem, by David Asboth.
From High-Performance Python for Data Analytics by Tiago Rodrigues Antao
In this article we will start to explore Python’s framework for concurrency – the first step in developing parallel applications.
From Exploring Data with R by Richard Iannone
From Modern Fortran by Milan Curcic
From Modern Fortran by Milan Curcic
Stock price analysis and prediction has been an increasingly popular topic since the early days of high-level programming, and Fortran has been used in the bowels of many financial trading and banking systems, mainly thanks to its robustness, reliability, and efficiency. In this article, we’ll work with a dataset that is freely available, small enough to be easily downloaded, and yet large enough to demonstrate the power of Fortran arrays.