Convolutional neural network
Convolutional neural networks (CNNs) are a type of artificial neural network (ANN) that are particularly well-suited for analyzing grid-like data, such as images, videos, and … Read more
Convolutional neural networks (CNNs) are a type of artificial neural network (ANN) that are particularly well-suited for analyzing grid-like data, such as images, videos, and … Read more
Long short-term memory (LSTM) networks are a type of recurrent neural network (RNN) architecture used in the fields of deep learning and machine learning. Unlike … Read more
Support vector machines (SVMs) are a supervised machine learning algorithm used for classification and regression tasks. They are known for their effectiveness in high-dimensional spaces … Read more
Definition Recurrent neural networks (RNNs) are a type of artificial neural network (ANN) that is well-suited for sequential data, such as natural language, speech, and … Read more
Definition: Neural networks, also known as artificial neural networks (ANNs) or simply networks, are a type of machine learning algorithm inspired by the structure and … Read more
Definition: Unsupervised machine learning is a type of machine learning that deals with unlabeled data. Unlike supervised learning, where the data is labeled with the … Read more
Machine learning models are mathematical frameworks that can be used to make predictions or decisions based on data. They are a powerful tool that can … Read more
In machine learning, normalizing data, also sometimes called data scaling, is a critical pre-processing step that involves transforming your data into a common range. This … Read more
Data augmentation is a technique used to artificially increase the size of a training dataset by applying transformations to existing data. This can be useful … Read more
In terms of design and implementation, a reinforcement learning (RL) framework is an organized approach that can be used to create RL algorithms. It is … Read more