Deep Learning

Relationships. We all have experiences with that word, especially in a romantic sense. They are delicate and complex, requiring careful nurturing to thrive. External factors come into play, and as an upcoming programmer, I have discovered parallels between the impact of friends on relationships and the world of programming. In…

How to apply the augmentation on YOLOv5 or YOLOv8 dataset using albumentations library in Python? — Data Augmentation Data augmentation is a technique in machine learning or deep learning where new data is created from the existing data by applying various transformations such as flipping, rotating, and changing the brightness/contrast. Data augmentation is commonly used in computer vision tasks but can also be used in other domains such…

Introduction Embark on a captivating journey as I delve into the transformative power of data analytics and how it reshaped my path from studying microbiology to pursuing a career in data analysis. Discover the pivotal moments and profound realizations that led me to embrace this exciting field and unlock my true…

Part 1 of 3: A Comparative analysis of real-time video data loading methods with YOLOv8 from Ultralytics — In today’s rapidly evolving world of computer vision and real-time video processing, the demand for high-performance dataloading solutions has never been greater. …

Generating images from line art, scribble, or pose key points using Stable Diffusion and ControlNet. — ControlNet is a neural network that controls a pretrained image Diffusion model (e.g. Stable Diffusion). Its function is to allow input of a conditioning image, which can then be used to manipulate the image generation. Table of Contents ├─ What Does ControlNet Do? ├─ Inner Architecture │ ├─ Feedforward │ ├─ Backpropagation ├─ Architecture with Stable Diffusion │…

Now it’s possible to have deep learning models with no limitation for the input size. — Attention Based Transformers Attention-based transformers have revolutionized the AI industry since 2017. Since then, we have seen significant progress in all aspects, including Computer vision, NLP, … Attentions are considered a more powerful and capable version of Neural Networks for generalization on big datasets and are nothing more than routing between keys (K)…

What happened this week in AI by Louie The open-source movement continues at pace this week with Falcon, a new family of state-of-the-art language models, ascending to the top of Hugging Face’s leaderboard. Falcon-40B, developed by the Technology Innovation Institute in Abu Dhabi, represents the first “truly open” model, boasting capabilities that rival many existing closed-source models. The…

Discover the world of Reinforcement Learning and its applications in this comprehensive introduction. From understanding the basics to exploring real-world examples, this article will guide you through the exciting realm of AI-driven decision-making. — Introduction to Reinforcement Learning Reinforcement Learning (RL) is a fascinating branch of Artificial Intelligence (AI) that focuses on training an agent to make intelligent decisions through trial and error. Unlike other machine learning approaches that rely on labelled datasets, RL involves learning from interactions with an environment to maximize a cumulative reward.

Graph Convolutional Networks (GCNs) are a type of neural network that operates on graphs, which are mathematical structures consisting of nodes and edges. GCNs have been successfully applied to many domains, including computer vision and social network analysis. In recent years, researchers have also explored using GCNs for natural language…