Introduction Descriptive analytics is a branch of data analytics that focuses on understanding and summarizing historical data to gain insights and patterns. It involves analyzing and interpreting data to describe… Descriptive Analytics
Introduction Introduction: A false negative refers to a situation where a test or diagnostic result incorrectly indicates the absence of a condition or attribute when it is actually present. In… False Negative
Introduction A false positive refers to a situation where a test or diagnostic result incorrectly indicates the presence of a condition or attribute when it is actually not present. This… False Positive
Introduction Feature engineering is a crucial step in the process of building machine learning models. It involves transforming raw data into a format that is suitable for analysis and modeling.… Feature Engineering
Introduction Federated Learning is a decentralized machine learning approach that allows multiple devices or edge devices to collaboratively train a shared model without sharing their raw data. Instead, the model… Federated Learning
Introduction Overfitting is a common problem in machine learning and statistical modeling. It occurs when a model is trained too well on a specific dataset, to the point that it… Overfitting
Introduction Prescriptive analytics is a branch of advanced analytics that utilizes various techniques, such as mathematical modeling, optimization algorithms, and machine learning, to provide organizations with actionable insights and recommendations.… Prescriptive Analytics
Introduction A Recurrent Neural Network (RNN) is a type of artificial neural network that is designed to process sequential data. Unlike traditional feedforward neural networks, RNNs have connections between nodes… Recurrent Neural Network (RNN)
