Tag Archives: machine learning
General

Training YOLO to Detect License Plates

By on Friday, January 3, 2025

The nice thing about ChatGPT and similar systems is that the complexity of AI/ML functionality is hidden behind a friendly natural language interface. This makes it easily reachable to the masses. But behind this easy to use facade is a lot of advanced functionality that involve a sequence of data processing steps called a pipeline. An AI-powered business card reader, for example, would first detect text and then recognize the individual letters within the context of the words they belong to. A license plate reader would be similar. Detection is an important process that you often need in your AI/ML projects. And that’s why we will be looking at YOLO.

Read More
0
General

Running Your Own LLM With Ollama

By on Friday, December 27, 2024

Leveraging the capabilities of Large Language Models (LLM) using APIs such as the OpenAI APIs is an easy way to add intelligence and advanced functionality to your applications. However, token costs add up and they can get quite expensive. Then there’s the nagging question of privacy and security. Finally, you’re limited in your ability to experiment and customize. But if you have a powerful machine with a GPU or two sitting around, wouldn’t it be great to utilize it for running one of those open source LLMs? Here’s how you can do it.

Read More
0
General

Renting GPUs With Vast.ai

By on Saturday, December 21, 2024

Artificial Intelligence (AI) and Machine Learning (ML) require a lot of computing power. Specifically, you would want to have GPUs which have become the standard tool for computing-intensive applications because of their parallel processing capabilities, high throughput, and efficiency in handling the kinds of large-scale computations required for AI and ML.

Read More
0
General

Preprocessing Images For Recognition

By on Friday, November 15, 2024

We have previously through the process of recognizing numbers utilizing our artificial neural network (ANN). If you haven’t gone through that post on, you can do so now. However, we ran the recognition task on images from the MNIST dataset. Even though we used the test data, it’s still cannot be considered real-world. It’s clean, well-labeled, and structured, with a lot of the noise and ambiguity removed.

Read More
0