In this tutorial, we implement a reinforcement learning agent using RLax, a research-oriented library developed by Google DeepMind for building reinforcement learning algorithms with JAX. We combine ...

Abstract: In this paper, Q-learning and Double Q-learning reinforcement learning algorithms were used to fine-tune sliding mode controller parameters to balance the Ball-and-Beam system. Each ...

Abstract: Bayesian inference provides a methodology for parameter estimation and uncertainty quantification in machine learning and deep learning methods. Variational inference and Markov Chain ...

With countless applications and a combination of approachability and power, Python is one of the most popular programming languages for beginners and experts alike. We’ve compiled a list of 10 online ...

This beginner-friendly tutorial shows how to create clear, interactive graphs in GlowScript VPython. You’ll learn the basics of setting up plots, graphing data in real time, and customizing axes and ...

In some ways, Java was the key language for machine learning and AI before Python stole its crown. Important pieces of the data science ecosystem, like Apache Spark, started out in the Java universe.

In today’s data-rich environment, business are always looking for a way to capitalize on available data for new insights and increased efficiencies. Given the escalating volumes of data and the ...

Ritwik is a passionate gamer who has a soft spot for JRPGs. He's been writing about all things gaming for six years and counting. No matter how great a title's gameplay may be, there's always the ...

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 ...