Use the vitals package with ellmer to evaluate and compare the accuracy of LLMs, including writing evals to test local models.

Learn how to predict the maximum distance of a projectile in Python while accounting for air resistance! 🐍⚡ This step-by-step tutorial teaches you how to model real-world projectile motion using ...

Learn how to model a mass-spring system using Python in this step-by-step tutorial! 🐍📊 Explore how to simulate oscillations, visualize motion, and analyze energy in a spring-mass system with code ...

Many of these courses focus on fast-growing, high-demand fields like data science, AI, robotics, biotechnology, and programming. This makes world-class IIT education accessible to a broader audience, ...

Abstract: With the rising popularity of Object-Oriented Programming (OOP) in both research and industry, it is important that computer science students be educated in the fundamentals of OOP and what ...

Corey Schafer’s YouTube channel is a go-to for clear, in-depth video tutorials covering a wide range of Python topics. The ...

I like Anime, Chess, Deep Learning, Mathematics and Programming. NumPy is a Python library that is mainly used to work with arrays. An array is a collection of items that are stored next to each other ...

After building an AI prototype in six hours, John Winsor turned it into a full platform in two weeks—showing how AI is collapsing the gap between vision and execution.

Machine learning is an essential component of artificial intelligence. Whether it’s powering recommendation engines, fraud detection systems, self-driving cars, generative AI, or any of the countless ...

The world’s most popular programming language is losing market share to more specialized languages such as R and Perl, Tiobe ...

The following codes are for educational purpose only and not intended to be used / submitted as your own solutions. Cheating violates the Academic Honesty of the course, not to mention it's totally ...

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