1. Introduction 1.1 Motivation Have you ever found yourself tirelessly scouring the internet for that one image that perfectly conveys your creative vision, only to come up short? Perhaps you’re a content creator on the quest for visuals that align seamlessly with your ideas. But hours of web surfing yield little more than frustration. Imagine … Continued

Introduction Diffusion models have earned a special place in the AI visual Content Generation landscape, dethroning GANs and positioning themselves as the go-to approach when creating realistic content. As technologies like LoRAs and Latent Consistency Models arrived, these models started to be less restrictive in terms of time and computing resources, and new possibilities and … Continued

Machine learning and data projects, in contrast with traditional software engineering projects, are governed by a resource characterized by unpredictable patterns, distributions, and biases – namely, the data itself. For a successful implementation of projects that give value through inference over datasets, we often consider: Does the collaboration between Agile methodologies and Machine Learning projects … Continued

Imagine you have to develop a computer vision application that must run in an industrial or agricultural environment with limited connectivity. Think, for example, of an application that detects plagues using a camera mounted on agricultural machinery.  Now imagine an application that monitors some machine in an industrial plant and needs to raise a real-time … Continued

Going on with our blog series on Large Language Models (LLMs) today we will talk about a successful finetuning case. While a well-crafted prompt can get the job done in many scenarios, there are times where it might not be enough. Finetuning steps in when we need results of higher quality compared to using prompts … Continued

In this follow-up to our initial exploration of NeRF (Neural Radiance Fields), we’ll dive deeper into the essential aspects of data preparation and management for utilizing this innovative technology. Additionally, we’ll highlight a selection of practical tools that can aid you in your NeRF journey, enabling you to better understand and apply its capabilities. Recap … Continued

Where are we? 🗺️ If you are a data scientist, machine learning engineer, or otherwise involved in a data-driven project, it is highly likely that you have used pandas to clean, sanitize, filter, and prepare the data to be used as input for your chosen methods, models, or algorithms. In this early step, which usually … Continued