Tag: LLMs

Master debugging techniques for AI models and data pipelines, covering data quality, model performance, prompt engineering, and …

Learn how to fine-tune Large Language Models for specific tasks using efficient techniques like PEFT and the Hugging Face library.

Learn how to interact with Large Language Models using AI APIs in Python, setting the foundation for building intelligent applications.

Learn how to implement a Retrieval-Augmented Generation (RAG) system to enhance LLMs with external knowledge.

Learn to build and understand AI agents that perceive, reason, and act autonomously using Python and LLMs.

A comprehensive guide to mastering Applied and Agentic AI, from foundational programming to building intelligent systems.

Explains the core concepts of prompts, completions, and parameters in Large Language Models.

Explains the philosophy, syntax, and core structures of TOON, a token-efficient data format for AI.

Learn how to use JSON Schema for data validation and consistency in AI applications.

Learn advanced features and best practices for optimizing TOON in AI workflows.

Explore the performance comparison and optimization strategies between JSON and TOON in the context of Large Language Models.

Learn how to build a structured data extraction agent using AI and JSON Schema.