Few-shot learning refers to a variety of algorithms and techniques used to develop an AI model using a very small amount of training data. Few-shot learning...
Transformer Neural Networks Described Transformers are a type of machine learning model that specializes in processing and interpreting sequential data, making them optimal for natural language processing...
Edge AI is one of the most notable new sectors of artificial intelligence, and it aims to let people run AI processes without having to be...
One of the most powerful machine learning techniques is ensemble learning. Ensemble learning is the use of multiple machine learning models to improve the reliability and...
What is Dimensionality Reduction? Dimensionality reduction is a process used to reduce the dimensionality of a dataset, taking many features and representing them as fewer features....
Generative Adversarial Networks (GANs) are types of neural network architectures capable of generating new data that conforms to learned patterns. GANs can be used to generate...
As technology advances, things don’t always become bigger and better, objects also become smaller. In fact, nanotechnology is one of the fastest-growing technological fields, worth over...
As deepfakes become easier to make and more prolific, more attention is paid to them. Deepfakes have become the focal point of discussions involving AI ethics,...
What is Federated Learning? The traditional method of training AI models involves setting up servers where models are trained on data, often through the use of...
Many of the most impressive advances in natural language processing and AI chatbots are driven by Recurrent Neural Networks (RNNs) and Long Short-Term Memory (LSTM) networks....
What is K-Nearest Neighbors (KNN)? K-Nearest Neighbors is a machine learning technique and algorithm that can be used for both regression and classification tasks. K-Nearest Neighbors...
What is Linear Regression? Linear regression is an algorithm used to predict, or visualize, a relationship between two different features/variables. In linear regression tasks, there are...
What are Support Vector Machines? Support vector machines are a type of machine learning classifier, arguably one of the most popular kinds of classifiers. Support vector...
What is Overfitting? When you train a neural network, you have to avoid overfitting. Overfitting is an issue within machine learning and statistics where a model...
What is Backpropagation? Deep learning systems are able to learn extremely complex patterns, and they accomplish this by adjusting their weights. How are the weights of...
