The Essential Guide to Large Language Models Structured Output, and Function Calling
Deep hands-on dive into LLMs structured output and function calling without any frameworks. It goes from theory all the way down to the implementation of two features using these capabilities in Python with practical tips from production systems. The first part of the article is suited for the broader audience, while the second part dives into the code. By the end of the article, the reader will have a solid foundation of structured output and function calling, and experience applying them to real-world use cases.
The Essential Guide to Large Language Models Structured Output, and Function CallingBuild Your Own Linear Regression: Implementations, Hyperparameters and their Optimizations
Implement linear regression from scratch using two different algorithms. Compare implementation results to what sklearn library provides on a real-world dataset. Tune them to reach balance between accuracy and performance via hyperparameters.
Applied Algorithms: Image Sort
Implement fast image sorting algorithm from scratch. Hands-on article covers basic of image processing and implements $O(n)$ sorting algorithm while discussing a bit of theory behind images on computers and applied algorithms with step-by-step reasoning.
Applied Algorithms: Image Sort