Introduction Self-supervised machine learning is a subfield of artificial intelligence that focuses on training models without the need for explicit human-labeled data. Instead, it leverages the vast amounts of unlabeled data available to learn useful… Read More »Self-Supervised Machine Learning
Machine Learning Operations (MLOps): Introduction Machine Learning Operations (MLOps) is a set of practices and techniques that aim to streamline and automate the deployment, management, and monitoring of machine learning models in production environments. It… Read More »Machine Learning Operations (MLOps)
Introduction Local explainability refers to the ability to understand and interpret the decisions made by a machine learning model at an individual instance level. It aims to provide insights into why a particular prediction or… Read More »Local Explainability
Introduction An operating point, also known as a bias point or quiescent point, refers to the steady-state condition of an electronic circuit or system. It represents the specific values of voltage, current, and other relevant… Read More »Operating Point
Introduction A Generative Adversarial Network (GAN) is a type of machine learning model that consists of two neural networks: a generator and a discriminator. The generator network is responsible for creating new data samples, such… Read More »Generative Adversarial Network (GAN)
Introduction General explainability refers to the ability of a system or model to provide understandable and interpretable explanations for its decisions or actions. It is an important aspect of artificial intelligence and machine learning, as… Read More »General Explainability
Introduction Multimodal Artificial Intelligence (AI) refers to the integration of multiple modes of communication and perception, such as speech, text, images, and gestures, into AI systems. By combining these different modalities, multimodal AI aims to… Read More »Multimodal Artificial Intelligence
Introduction The Foundation Model (FM) is a state-of-the-art language model developed by OpenAI. It is designed to generate human-like text and has been trained on a vast amount of internet text data. The FM is… Read More »Foundation Model (FM)
Introduction Training data is a crucial component in the development of artificial intelligence systems. It refers to the information or examples that are used to train an AI model or algorithm. This data is carefully… Read More »Training Data
Introduction Introduction: In the context of binary classification, a true negative refers to a situation where a model correctly predicts the absence of a particular condition or event when it is indeed absent. It is… Read More »True Negative