Engineering

Read about the technology powering our platform. From the development of powerful ML models to Search Engine, and Kubernetes deployment. Great reading for the geeks during long winter nights. Read more in Developers.

Deployment of machine learning and ai models

The Best Tools for Machine Learning Model Serving

An overview and analysis of serving systems and deployment methods for Machine Learning and AI models.

How to Build a Good Visual Search Engine?

Let's take a closer look at the technology behind visual search and the key components of visual search engines.

How to Convert a Video Into a Streaming Format?

A comprehensive tutorial for converting a .mp4 .mkv or .mov videos to the streaming formats (HLS or DASH) with Python and FFmpeg.

Explainable AI: What is My Image Recognition Model Looking At?

With the AI Explainability in Ximilar App, you can see which parts of your images are the most important to your image recognition models.

How to deploy object detection on Nvidia Jetson Nano

We developed a computer vision system for object detection, counting, and tracking on Nvidia Jetson Nano.

Flows – The Game Changer for Next-generation AI Systems

Flows is a service for combining machine learning models for image recognition, object detection and other AI services into API.

Image Similarity as a Service For Your Web

A step-by-step guide for using image similarity as a service. Find similar items with accurate & fast API for Image Search.

How to Build Your Own Image Recognition API?

Tips and tricks for developing and improving your custom image recognition models and deploying them as API with the Ximilar platform.

OpenVINO: Start Optimizing Your TensorFlow 2 Models for Intel CPUs with Docker

Tutorial for optimizing your image recognition models with OpenVINO technology. Making your system faster with Intel CPUs.