/machinelearning - articles

How to install Stable Diffusion on Ubuntu and use it in CLI
What is Stable Diffusion? How to install Stable Diffusion on Ubuntu? How to use Stable Diffusion in CLI? Tuning params to get better image quality.
Published half a year ago in #machinelearning about #stable diffusion, #ubuntu and #images
Searching images based on text using CLIP model
What is CLIP and common image/text vector space? How to install and run CLIP? How to compare image and text embeddings to find corresponding images based on text query?
Published half a year ago in #machinelearning about #clip, #embeddings, #vector search and #python
What is a text embedding and how to use it for text search
What is a text embedding? How to get embeddings from a lot of text data? How to search within text data using text embeddings? What is the difference between vector-based text search and full-text search?
Published half a year ago in #machinelearning about #embeddings, #vector search, #python and #openai
Image similarity search based on embeddings and sentence_transformers
How to get image embeddings using sentence_transformers models. How to store vectors in the database. How to find similar images to the given query image.
Published half a year ago in #machinelearning about #embeddings, #sentence_transformers, #clip, #vector search, #python and #clickhouse
What is actually a neural network?
The very basic and simple explanation of what a Neural Network is and why a lot of modern articles and videos explain it wrong.
Published half a year ago in #machinelearning about #neural network
Formatting unstructured data using OpenAI API and Python
How to use OpenAI to format unstructured text data, e.g. CSV. Setting additional formatting requirements to format specific values in the resulting CSV.
Published 2 years ago in #machinelearning about #python and #openai
Quick start OpenAI API example using Python
How to start using OpenAI API with Python. A simple example of a Python script that generates data based on the OpenAI language model.
Published 2 years ago in #machinelearning about #python and #openai
What is a function derivative and how to optimize functions
The article explains what a function derivative is on a very basic level. Starting from the concept of the function, we move along function changes and finally, look at a Python example of optimizing a function based on its derivative.
Published 2 years ago in #machinelearning about #math, #derivative and #python
Matrices and vectors math for AI with Python examples
Article provides an introduction to vectors and matrices, two fundamental concepts in linear algebra, which are widely used in artificial intelligence. It explains what vectors and matrices are and how they are defined in math. Basic operations with vectors and matrices using Python, including adding, multiplying, and transposing matrices.
Published 2 years ago in #machinelearning about #math, #matrix and #vector
Creating a bigram language model for text generation with Python
Understanding bigram language models, which are statistical models that predict the likelihood of a word given its preceding word. Includes an example of a simple bigram language model in Python.
Published 2 years ago in #machinelearning about #nlp, #language-models and #python
What is a language model and how it works
Basics about language models, which are algorithms that enable computers to analyze and understand human language. The article explains how language models work and how they are trained, using a simple example of a program that can understand and respond to simple questions.
Published 2 years ago in #machinelearning about #nlp and #language-models
What is Machine Learning and how it works
Machine Learning basics, the math behind machine learning, predictions, prediction errors, training dataset, validation dataset.
Published 2 years ago in #machinelearning