Part of the series: From Scripts to Software: Practical Python for Reproducible Research Having learned how to write sustainable, object-oriented code and how to scale it across multiple processors, we will now explore how to dramatically accelerate your computations using Graphics Processing Units (GPUs). Modern GPUs are massively parallel processors that can perform millions of...
Python is a general-purpose programming language that is easy to learn and widely used. It is one of the primary programming languages for data science, and when combined with its modules such as NumPy, SciPy, Matplotlib, and Pandas, it can be a very powerful tool for numerical computing. The first part of this hands-on series...
The second part of this hands-on series will introduce you to a few libraries that enable Python to function as a powerful numerical programming language, including NumPy, SciPy, and Pandas. We will focus on a few illustrative problems, such as exploratory statistical analysis and visualization, curve fitting, finding solutions to a set of linear equations,...
Neural networks are the "beating heart" of modern LLM-based AI systems, driving everything from image recognition to natural language processing. In this 2-hour lecture, we'll explore the foundational concepts of neural networks and their pivotal role in deep learning projects. This session is designed to be accessible to all, with a focus on intuitive explanations...