machine learning wikipedia - EAS

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  1. machine learning - Wiktionary

    https://en.wiktionary.org/wiki/machine_learning

    Noun. machine learning ( initialism ML ) ( artificial intelligence) A field of study concerned with the design and development of algorithms and techniques that allow computers to learn . quotations . 2019 February 3, “UN Study: China, US, Japan Lead World AI Development”, in Voice of America ‎ [1], archived from the original on 7 ...

  2. Machine Learning - MediaWiki

    https://www.mediawiki.org/wiki/Machine_Learning

    07/12/2021 · Our purpose. Design, build, and maintain the foundation's machine learning infrastructure. Plan, train, deploy, and manage production machine learning models created or requested by Wikimedia teams or Wiki communities. Develop best practices for applied ethical machine learning.

  3. Machine learning - Wikiquote

    https://en.wikiquote.org/wiki/Machine_learning

    25/05/2021 · Machine learning is the science and technology of developing and applying computer algorithms that improve automatically through comparing algorithmic results with training data using logically precise rules for success and by the use of extensive data sets. ML is one the major subdomains of artificial intelligence.

  4. Machine learning - OpenStreetMap Wiki

    https://wiki.openstreetmap.org/wiki/Machine_Learning

    Machine Learning is a subdomain of Artificial Intelligence centered around the idea that machines can be trained to recognize patterns based on annotated input data. In the context of maps and OSM, a common application is to annotate a sample set of imagery (aerial or street-level) in order to automatically derive information and/or map ...

  5. Machine Learning Models Explained - AI Wiki

    https://docs.paperspace.com/machine-learning/wiki/...

    Machine learning models are akin to mathematical functions -- they take a request in the form of input data, make a prediction on that input data, and then serve a response. In supervised and unsupervised machine learning, the model describes the signal in the noise or the pattern detected from the training data.

  6. Adversarial machine learning - Wikipedia

    https://it.wikipedia.org/wiki/Adversarial_machine_learning

    Adversarial machine learning (Apprendimento automatico antagonistico) è una serie di tecniche volte a compromettere il corretto funzionamento di un sistema informatico che faccia uso di algoritmi di apprendimento automatico, tramite la costruzione di input speciali in grado di ingannare tali algoritmi: più nello specifico, lo scopo di tali tecniche è quello di causare la …

  7. Machine Learning by Stanford University | Coursera

    https://www.coursera.org/learn/machine-learning

    Machine learning is the science of getting computers to act without being explicitly programmed. In the past decade, machine learning has given us self-driving cars, practical speech recognition, effective web search, and a vastly improved understanding of the human genome.

  8. What is a Pipeline in Machine Learning? How to create one ...

    https://medium.com/analytics-vidhya/what-is-a...

    10/12/2019 · Machine learning pipelines are iterative as every step is repeated to continuously improve the accuracy of the model and achieve a successful algorithm. To build better machine learning models ...

  9. Future Scope of Machine Learning (ML) | Intellipaat Blog

    https://intellipaat.com/blog/future-scope-of-machine-learning

    29/01/2022 · Future Scope of Machine Learning. Machine Learning is one of the best career choices of the 21st century. It has plenty of job opportunities with a high-paying salary. Also, the future scope of Machine Learning is on its way to make a drastic change in the world of automation. Further, there is a wide scope of Machine Learning in India.

  10. ¿Qué es Machine Learning? – Cleverdata

    https://cleverdata.io/que-es-machine-learning-big-data

    Machine Learning es una disciplina científica del ámbito de la Inteligencia Artificial que crea sistemas que aprenden automáticamente.Aprender en este contexto quiere decir identificar patrones complejos en millones de datos.La máquina que realmente aprende es un algoritmo que revisa los datos y es capaz de predecir comportamientos futuros. ...



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