Dive into Faraday’s Law of Electromagnetic Induction with a practical Python implementation in this first part of our Electrodynamics series. Learn how to simulate and visualize changing magnetic ...

A marriage of formal methods and LLMs seeks to harness the strengths of both.

Abstract: Q-learning and double Q-learning are well-known sample-based, off-policy reinforcement learning algorithms. However, Q-learning suffers from overestimation bias, while double Q-learning ...

In this tutorial, we explore how exploration strategies shape intelligent decision-making through agent-based problem solving. We build and train three agents, Q-Learning with epsilon-greedy ...

The same is true for Q# callables defined in Jupyter notebook using the %%qsharp cell magic: These callables can then be invoked as normal Python functions, which will run them in the Q# simulator ...

If you’re learning machine learning with Python, chances are you’ll come across Scikit-learn. Often described as “Machine Learning in Python,” Scikit-learn is one of the most widely used open-source ...

Learning Python often begins with a simple yet powerful exercise: printing “Hello, World!” to the screen. This one-liner doesn’t just display text—it’s your first step toward mastering Python ...

Google Colab is a really handy tool for anyone working with machine learning and data stuff. It’s free, it runs in the cloud, and it lets you use Python without a lot of fuss. Whether you’re just ...

Abstract: Self-regulated learning refers to the process in which learners are responsible for their own learning, from passive acquisition of knowledge to learning self-active control and restraint.