
Evaluation Metrics
Evaluation metrics are used to measure the quality of the statistical or machine learning model.
Machine Learning Confusion Matrixread 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)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 Posterior Probability Prior Probabilityread 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) Autoencoderread it

Active Learning
Active learning is a form of semisupervised machine learning where the algorithm chooses which data to learn from and queries a teacher for guidance.
Natural Language Processing Supervised Learning Machine Learningread it

Attention Models
Attention models break down complicated tasks into smaller areas of attention that are processed sequentially.
Vector Neural Network Computer Visionread 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.
read it

Posterior Probability
In statistics, the posterior probability expresses how likely a hypothesis is given a particular set of data.
Probability Bayesian Inference Machine Learningread 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 Stochastic Gradient Descentread 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.
Machine Learning Vector Neural Networkread it

Disentangled Representation Learning
Disentangled representation is an unsupervised learning technique that breaks down, or disentangles, each feature into separate, lower dimension variables.
Distributed Representations Unsupervised Learning Vectorread it
Definitions
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