What are Variational Autoencoders (VAEs)? Autoencoders are ingenious, unsupervised learning mechanisms capable of learning efficient data representations. However, traditional autoencoders…
What are Embeddings from Language Models (ELMo)? ELMo, short for Embeddings from Language Models, revolutionized the landscape of NLP by…
What is t-SNE? t-SNE, or t-distributed Stochastic Neighbor Embedding, is a popular non-linear dimensionality reduction technique used primarily for visualizing…
What is Data2vec? Meta AI has introduced Data2vec, a groundbreaking framework for self-supervised learning that transcends the barriers between different…
What is Multimodal NLP? Multimodal NLP refers to the intersection of natural language processing (NLP) with other data or modalities,…
What is Self-Supervised Learning? Self-supervised learning (SSL) is a machine learning technique where a model learns representations or features directly…
What is Machine Learning with Graphs? Machine learning with graphs refers to applying machine learning techniques and algorithms to analyze,…
What is Representation Learning? Representation learning is a cornerstone in artificial intelligence, fundamentally altering how machines comprehend intricate data. Its…
What is a Prototypical Network? At its core, Prototypical Networks represent a groundbreaking approach to tackling the complexities of classification…
What is the Exploding Gradient Problem? Neural networks optimize their parameters using gradient-based optimization algorithms like gradient descent. Gradients represent…