Category/Tag: Machine Learning

Psycopg Tutorial: Using pgvector to do Retrieval Augmented Generation

Psycopg Tutorial: Using pgvector to do Retrieval Augmented Generation

Continuing with our tutorials on how to get started with Machine Learning, our in-house expert on AI and ML, Bruce Nielson, shares how you can use pgvector and Psycopg to do RAG.


Installing Haystack for pgvector in Preparation for Retrieval Augmented Generation

Installing Haystack for pgvector in Preparation for Retrieval Augmented Generation

Continuing with our series of tutorials on getting ready for Retrieval Augmented Generation, Bruce Nielson shares how you can get Haystack installed and working with your PostgreSQL database.


A Short Explanation of Hierarchal Navigable Small Worlds (HNSW) Index for pgvector

A Short Explanation of Hierarchal Navigable Small Worlds (HNSW) Index for pgvector

In our last two posts, we first installed PostgreSQL and then installed the pgvector extension to add functionality to PostgreSQL to allow us to use PostgreSQL as our document store for use with RAG. Today, we will briefly explain how pgvector handles similarity comparisons, and how it differs from our simple cosine similarity method.


Installing pgvector in Preparation for Retrieval Augmented Generation

Installing pgvector in Preparation for Retrieval Augmented Generation

Continuing from our previous tutorial on setting up a database in preparation for Machine Learning with RAG (Retrieval Augmented Generation), Bruce Nielson discusses how to install the pgvector extension for PostgreSQL.


Installing PostgreSQL in Preparation for Retrieval Augmented Generation

Installing PostgreSQL in Preparation for Retrieval Augmented Generation

One big problem with a Cosine Similarity search is how computationally intensive it is, and there aren't many options to make it much better. Therefore, you need a proper database to work with, and in this tutorial, we will discuss setting up PostgreSQL in preparation for working with RAG/ML.


Haystack, Google, and Gemma: A Tutorial

Haystack, Google, and Gemma: A Tutorial

The Haystack Library is a great way to easily take advantage of and integrate semantic-search-like functionality into your AI. Currently, however, it can be quite difficult to find a functional tutorial on how to get Haystack working with free LLMs, and so Bruce Nielson, Mindfire's own expert on AI and ML, decided to put together a tutorial of his own on how to get it working using Google Gemma.


LM Studio - The Easiest Way to get Started with Hugging Face LLMs

LM Studio - The Easiest Way to get Started with Hugging Face LLMs

In this short blog, Bruce Nielson shares one of his favorite tools for getting started with Hugging Face LLMs, LM Studio. This tool allows easy access and use of Hugging Face LLMs, even for those with little technical knowledge. It can be a great way to get started, or to just learn more about Large Language Models.


Wikipedia and Google Gemini

Wikipedia and Google Gemini

Ever envied the characters on Star Trek who could simply ask the computer a question or to perform a task? Well, in this article by Bruce Nielson, we learn some interesting ways to integrate Google Gemini with Wikipedia to do just that.


Getting Started with the Google Gemini API

Getting Started with the Google Gemini API

Interested in learning how to use the Google Gemini API? Or just want to learn more about it? Well, you're in luck, as Bruce Nielson, a Mindfire specialist in AI and ML, just wrote a tutorial on how to get started


An Introduction to Hugging Face and Their Pipelines

An Introduction to Hugging Face and Their Pipelines

A proper introduction into the Hugging Face ecosystem presented by Bruce Nielson.