The need for continual learning In the ever-evolving landscape of machine learning and artificial intelligence, the ability to adapt and learn continuously (continual learning) has become...

The need for continual learning In the ever-evolving landscape of machine learning and artificial intelligence, the ability to adapt and learn continuously (continual learning) has become...
What is sequence-to-sequence? Sequence-to-sequence (Seq2Seq) is a deep learning architecture used in natural language processing (NLP) and other sequence modelling tasks. It is designed to handle...
What is cross-entropy loss? Cross-entropy Loss, often called "cross-entropy," is a loss function commonly used in machine learning and deep learning, particularly in classification tasks. It...
What is natural language generation? Natural Language Generation (NLG) is a subfield of artificial intelligence (AI) and natural language processing (NLP) that focuses on the automatic generation of...
What are loss functions? Loss functions, also known as a cost or objective functions, are critical component in training machine learning models. It quantifies a machine learning model's performance...
What is cross-lingual transfer learning? Cross-lingual transfer learning is a machine learning technique that involves transferring knowledge or models from one language to another, typically to...
What is text labelling? Text labelling, or text annotation or tagging, assigns labels or categories to text data to make it more understandable and usable for various natural language processing...
What is language identification? Language identification is a critical component of Natural Language Processing (NLP), a field dedicated to interacting with computers and human languages. At its...
Understanding Multilingual NLP In the era of globalization and digital interconnectedness, the ability to understand and process multiple languages is no longer a luxury; it's a necessity....
What is text cleaning in NLP? Text cleaning, also known as text preprocessing or text data cleansing, is preparing and transforming raw text data into a cleaner, more structured format for analysis,...
Introduction To NLP Exploratory Data Analysis In today's data-driven world, Natural Language Processing (NLP) has emerged as a transformative field, enabling machines to understand, interpret, and...
What is Mean Average Precision? Mean Average Precision (MAP) is a widely used evaluation metric in information retrieval, search engines, recommendation systems, and object detection tasks. It...
What is Hierarchical Clustering? Hierarchical clustering is a popular method in data analysis and data mining for grouping similar data points or objects into clusters or groups. It creates a...
What is Imputation? Imputation is a statistical and data analysis technique to fill in or estimate missing values within a dataset. Data may not be complete in real-world situations for multiple...
What is Non-Negative Matrix Factorization? Non-Negative Matrix Factorization (NMF) is a mathematical and computational technique used in data analysis, machine learning, and various scientific...
What is a Vector Space Model? The Vector Space Model (VSM) is a mathematical framework used in information retrieval and natural language processing (NLP) to represent and analyze textual data. It's...
In today's data-driven world, making sense of vast volumes of text data is paramount. Natural Language Processing (NLP) techniques are at the forefront of unlocking the insights hidden within text,...
What is information retrieval? Information retrieval (IR) is the process of obtaining information from an extensive repository of data or documents. It involves searching for and retrieving relevant...
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