Learn what AI agents are, what small language models (SLMs) are, why running them locally matters, and how to build a working AI agent on your own machine using Ollama, Hugging Face Transformers, and LangChain/LangGraph step by step, with real Python code.

Machine Learning Mastery offers developers resources and tutorials on machine learning algorithms, techniques, and applications. Developers can learn about supervised and unsupervised learning methods, deep learning frameworks, and practical machine learning projects. Additionally, the blog covers topics such as data preprocessing, model evaluation, and hyperparameter tuning, providing  insights for both beginners and experienced practitioners in the field of machine learning.

Machine Learning Mastery

A step-by-step guide to building a fully functional AI agent that runs locally on your own machine using small language models (SLMs), with no internet connection or API costs. Covers what AI agents and SLMs are, how to install and configure Ollama with Phi-3 or Llama 3.2, and how to build a working agent using LangChain/LangGraph with a calculator tool and conversation memory. Also discusses trade-offs of local SLMs versus cloud models, including accuracy, speed, and context length limitations.

Building AI Agents with Local Small Language Models