Use the vitals package with ellmer to evaluate and compare the accuracy of LLMs, including writing evals to test local models.
Dot Physics on MSN
Python tutorial: Predicting maximum projectile distance when air resistance matters
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 ...
Dot Physics on MSN
Learn how to model a mass and spring using Python
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, ...
Corey Schafer’s YouTube channel is a go-to for clear, in-depth video tutorials covering a wide range of Python topics. The ...
February 2026 TIOBE Index shows Python still far ahead, C strengthening in second, C# rising, and R holding the top 10 as rankings compress.
After building an AI prototype in six hours, John Winsor turned it into a full platform in two weeks—showing how AI is ...
In Pyper, the task decorator is used to transform functions into composable pipelines. Let's simulate a pipeline that performs a series of transformations on some data.
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 ...
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