Definitions

The data science and artificial intelligence
terms you need while reading the latest research

Bayes Theorem

What is Bayes' Theorem in statistics and machine learning?

Machine Learning Posterior Probability Prior Probability
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Convolutional Neural Networks

A convolutional neural network is a type of neural network that is most commonly applied to processing and analyzing visual imagery.

Neural Network Natural Language Processing Artificial Intelligence
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Active Learning

Active learning is a form of semi-supervised machine learning where the algorithm chooses which data to learn from and queries a teacher for guidance.

Natural Language Processing Supervised Learning Machine Learning
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Generative Adversarial Network

A generative adversarial network (GAN) is an unsupervised machine learning technique that trains two neural networks by forcing them to “outwit” each other.

Classifier Unsupervised Learning Machine Learning
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Natural Language Processing

In simple words, Natural Language Processing is a field which aims to make computer systems understand human speech. NLP is comprised of techniques to process, structure, categorize raw text and extract information.

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Evaluation Metrics

Evaluation metrics are used to measure the quality of the statistical or machine learning model.

Machine Learning Confusion Matrix
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Manifold Hypothesis

What is the Manifold Hypothesis?

Degree of Freedom Machine Learning High-Dimensional Data
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Feature Extraction

Feature extraction is a process by which an initial set of data is reduced by identifying key features of the data for machine learning.

Machine Learning Natural Language Processing Unsupervised Learning
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Tensor

A Tensor is a mathematical object similar to, but more general than, a vector and often represented by an array of components that describe functions relevant to coordinates of a space. Put simply, a Tensor is an array of numbers that transform according to certain rules under a change of coordinates.

Neural Network Vector Machine Learning
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Attention Models

Attention models break down complicated tasks into smaller areas of attention that are processed sequentially.

Vector Neural Network Computer Vision
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Statistical Learning Theory

Statistical learning theory is the broad framework for studying the concept of inference in both supervised and unsupervised machine learning.

Probability Machine Learning Deep Learning
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