ML Platforms Definitions

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  • A

    adversarial machine learning

    Adversarial machine learning is a technique used in machine learning (ML) to fool or misguide a model with malicious input.

  • AI winter

    AI winter is a quiet period for artificial intelligence research and development.

  • Amazon Bedrock (AWS Bedrock)

    Amazon Bedrock -- also known as AWS Bedrock -- is a machine learning platform used to build generative artificial intelligence (AI) applications on the Amazon Web Services cloud computing platform.

  • anomaly detection

    Anomaly detection is the process of identifying data points, entities or events that fall outside the normal range.

  • automated machine learning (AutoML)

    Automated machine learning (AutoML) is the process of applying machine learning (ML) models to real-world problems using automation.

  • B

    backpropagation algorithm

    Backpropagation, or backward propagation of errors, is an algorithm that is designed to test for errors working back from output nodes to input nodes.

  • C

    case-based reasoning (CBR)

    Case-based reasoning (CBR) is an experience-based approach to solving new problems by adapting previously successful solutions to similar problems.

  • clustering in machine learning

    Clustering is a data science technique in machine learning that groups similar rows in a data set.

  • cognitive bias

    Cognitive bias is a systematic thought process caused by the tendency of the human brain to simplify information processing through a filter of personal experience and preferences.

  • cognitive computing

    Cognitive computing is the use of computerized models to simulate the human thought process in complex situations where the answers might be ambiguous and uncertain.

  • conversational AI (conversational artificial intelligence)

    Conversational AI (conversational artificial intelligence) is a type of AI that enables computers to understand, process and generate human language.

  • convolutional neural network (CNN)

    A convolutional neural network (CNN) is a category of machine learning model, namely a type of deep learning algorithm well suited to analyzing visual data.

  • D

    data splitting

    Data splitting is when data is divided into two or more subsets. Typically, with a two-part split, one part is used to evaluate or test the data and the other for training the model.

  • decision tree in machine learning

    A decision tree is a flow chart created by a computer algorithm to make decisions or numeric predictions based on information in a digital data set.

  • deconvolutional networks (deconvolutional neural networks)

    Deconvolutional networks are convolutional neural networks (CNN) that work in a reversed process.

  • deep learning

    Deep learning is a type of machine learning and artificial intelligence (AI) that imitates the way humans gain certain types of knowledge.

  • dropout

    Dropout refers to data, or noise, that's intentionally dropped from a neural network to improve processing and time to results.

  • E

    expert system

    An expert system is a computer program that uses artificial intelligence (AI) technologies to simulate the judgment and behavior of a human or an organization that has expertise and experience in a particular field.

  • F

    face detection

    Face detection, also called facial detection, is an artificial intelligence (AI)-based computer technology used to find and identify human faces in digital images and video.

  • facial recognition

    Facial recognition is a category of biometric software that maps an individual's facial features mathematically and stores the data as a faceprint.

  • fuzzy logic

    Fuzzy logic is an approach to computing based on "degrees of truth" rather than the usual "true or false" (1 or 0) Boolean logic on which the modern computer is based.

  • G

    Gemma

    Gemma is a collection of lightweight open source generative AI models designed mainly for developers and researchers.

  • generative adversarial network (GAN)

    A generative adversarial network (GAN) is a machine learning (ML) model in which two neural networks compete with each other by using deep learning methods to become more accurate in their predictions.

  • generative modeling

    Generative modeling is the use of artificial intelligence (AI), statistics and probability in applications to produce a representation or abstraction of observed phenomena or target variables that can be calculated from observations.

  • GPT-3

    GPT-3, or the third-generation Generative Pre-trained Transformer, is a neural network machine learning model trained using internet data to generate any type of text.

  • What is generative AI? Everything you need to know

    Generative AI is a type of artificial intelligence technology that can produce various types of content, including text, imagery, audio and synthetic data.

  • K

    knowledge graph in ML

    In the realm of machine learning (ML), a knowledge graph is a graphical representation that captures the connections between different entities.

  • L

    LangChain

    LangChain is an open source framework that lets software developers working with artificial intelligence (AI) and its machine learning subset combine large language models with other external components to develop LLM-powered applications.

  • language modeling

    Language modeling, or LM, is the use of various statistical and probabilistic techniques to determine the probability of a given sequence of words occurring in a sentence. Language models analyze bodies of text data to provide a basis for their word predictions.

  • linear regression

    Linear regression identifies the relationship between the mean value of one variable and the corresponding values of one or more other variables.

  • M

    machine learning bias (AI bias)

    Machine learning bias, also sometimes called algorithm bias or AI bias, is a phenomenon that occurs when an algorithm produces results that are systemically prejudiced due to erroneous assumptions in the machine learning process.

  • machine learning engineer (ML engineer)

    A machine learning engineer (ML engineer) is a person in IT who focuses on researching, building and designing self-running artificial intelligence (AI) systems to automate predictive models.

  • machine teaching

    Machine teaching is the practice of infusing context -- and often business consequences -- into the selection of training data used in machine learning (ML) so that the most relevant outputs are produced by the ML algorithms.

  • machine translation

    Machine translation technology enables the conversion of text or speech from one language to another using computer algorithms.

  • masked language models (MLMs)

    Masked language models (MLMs) are used in natural language processing (NLP) tasks for training language models.

  • What is machine learning and how does it work? In-depth guide

    Machine learning (ML) is a type of artificial intelligence (AI) focused on building computer systems that learn from data. The broad range of techniques ML encompasses enables software applications to improve their performance over time.

  • N

    narrow AI (weak AI)

    Narrow AI is an application of artificial intelligence technologies to enable a high-functioning system that replicates -- and perhaps surpasses -- human intelligence for a dedicated purpose.

  • natural language processing (NLP)

    Natural language processing (NLP) is the ability of a computer program to understand human language as it’s spoken and written -- referred to as natural language.

  • natural language understanding (NLU)

    Natural language understanding (NLU) is a branch of artificial intelligence (AI) that uses computer software to understand input in the form of sentences using text or speech.

  • neural network

    A neural network is a machine learning (ML) model designed to mimic the function and structure of the human brain.

  • neural radiance field (NeRF)

    Neural radiance fields (NeRF) are a technique that generates 3D representations of an object or scene from 2D images by using advanced machine learning.

  • O

    OpenAI

    OpenAI is a private research laboratory that aims to develop and direct artificial intelligence (AI) in ways that benefit humanity as a whole.

  • P

    predictive modeling

    Predictive modeling is a mathematical process used to predict future events or outcomes by analyzing patterns in a given set of input data.

  • PyTorch

    PyTorch is an open source machine learning (ML) framework based on the Python programming language and the Torch library.

  • Q

    Q-learning

    Q-learning is a machine learning approach that enables a model to iteratively learn and improve over time by taking the correct action.

  • R

    recurrent neural networks

    A recurrent neural network (RNN) is a type of artificial neural network commonly used in speech recognition and natural language processing.

  • reinforcement learning

    Reinforcement learning is a machine learning training method based on rewarding desired behaviors and punishing undesired ones.

  • Retrieval-Augmented Language Model pre-training

    A Retrieval-Augmented Language Model, also referred to as REALM or RALM, is an artificial intelligence language model designed to retrieve text and then use it to perform question-based tasks.

  • S

    self-driving car (autonomous car or driverless car)

    A self-driving car (sometimes called an autonomous car or driverless car) is a vehicle that uses a combination of sensors, cameras, radar and artificial intelligence (AI) to travel between destinations without a human operator.

  • singularity

    In technology, the singularity describes a hypothetical future where technology growth is out of control and irreversible.

  • supervised learning

    Supervised learning is an approach to creating artificial intelligence (AI) where a computer algorithm is trained on input data that has been labeled for a particular output.

  • U

    unsupervised learning

    Unsupervised learning is a type of machine learning (ML) technique that uses artificial intelligence (AI) algorithms to identify patterns in data sets that are neither classified nor labeled.

  • V

    vector embeddings

    Vector embeddings are numerical representations that capture the relationships and meaning of words, phrases and other data types.

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