Definitions

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

  •

    Evaluation Metrics

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

    Machine Learning Confusion Matrix
    05/17/2019 ∙ 1988 ∙

    read it

  • Convolutional Neural Network

    A convolutional neural network, or CNN, is a deep learning neural network designed for processing structured arrays of data such as images.

    ImageNet Classifier Estimator (Statistics)
    05/17/2019 ∙ 1501 ∙

    read it

  • Batch Normalization

    Batch Normalization is a supervised learning technique that converts selected inputs in a neural network layer into a standard format, called normalizing.

    Supervised Learning Deep Learning Loss Function
    05/17/2019 ∙ 1480 ∙

    read it

  • Generative Adversarial Network

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

    Classifier Estimator (Statistics) Autoencoder
    07/22/2020 ∙ 1426 ∙

    read it

  • Bayes Theorem

    Bayes’ theorem is a formula that governs how to assign a subjective degree of belief to a hypothesis and rationally update that probability with new evidence. Mathematically, it's the the likelihood of event B occurring given that A is true.

    Machine Learning Odds (Probability) Prior Probability
    05/17/2019 ∙ 1361 ∙

    read it

  • 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
    05/17/2019 ∙ 1338 ∙

    read it

  • Attention Models

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

    Vector Neural Network Computer Vision
    05/17/2019 ∙ 1195 ∙

    read it

  • Posterior Probability

    In statistics, the posterior probability expresses how likely a hypothesis is given a particular set of data.

    Machine Learning Bayesian Inference Bayes Theorem
    05/17/2019 ∙ 1137 ∙

    read it

  • 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.

    05/17/2019 ∙ 1131 ∙

    read it

  • Deep Belief Network

    Deep Belief Networks (DBNs) are a laddering of individual unsupervised networks that use each network’s hidden layer as the input for the next layer.

    Supervised Learning Unsupervised Learning Restricted Boltzmann Machine
    05/17/2019 ∙ 1118 ∙

    read it

  • 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
    05/17/2019 ∙ 1070 ∙

    read it

Sign up for DeepAI

Join one of the world's largest A.I. communities

Already have an account? Login here

Login to DeepAI

Don't have an account? Signup here

SHARE