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E-Learning-Inclusivo (Mashup)
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Ben, pois unha das técnicas utilizadas na intelixencia artificial é a coñecida como machine learning ou aprendizaxe automática. Trátase dun conxunto de algoritmos cos que se constrúe un modelo de clasificación a partir de conxuntos de datos coñecidos. Con este modelo a máquina vai ser capaz de clasificar datos de entrada novos que non eran coñecidos de antemán pero que se axustan aos parámetros do modelo. Via Gumersindo Fernández 
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There’s no doubt that machine learning has a lot to offer eLearning. What are the benefits of machine learning and is applying it in eLearning essential? Via CommLab India
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November 17, 2018
Learn more / En savoir plus / Mehr erfahren:
https://www.scoop.it/t/21st-century-learning-and-teaching/?&tag=machine+learning
Via Gust MEES
Gust MEES's curator insight,
November 20, 2018 10:37 AM
November 17, 2018
Learn more / En savoir plus / Mehr erfahren:
https://www.scoop.it/t/21st-century-learning-and-teaching/?&tag=machine+learning
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Aprendizaje automático o machine learning . Habrás oído la palabra en infinidad de ocasiones. Y es probable que sepas más menos qué significa. Tratamos de rellenar los huecos que te queden de la mano de Israel Olalla, ingeniero de Google Via Silvano Poblano Morales
EntreCulturas's curator insight,
October 20, 2017 3:40 AM
¿Qué es el aprendizaje automático o machine learning? ¿Para qué sirve? ¿Qué consecuencias tendrá sobre e l empleo? ¿Cómo se relaciona con la inteligencia humana? Este breve video contesta a todas las preguntas y nos da las claves de un fenómeno en desarrollo.
Maltrespuntocero's curator insight,
October 20, 2017 10:38 AM
Una cuestión tan profunda y aparentemente complicada que queda explicada en escasos dos minutos y medio. Lo recomiendo. Esta rama de la inteligencia artificial es un paso para acercarse a la inteligencia humana pero, que no teman los más escépticos, en ningún caso sustituirla.
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"This blog on What is Deep Learning will provide you an overview of Artificial Intelligence, Machine Learning and Deep Learning with its applications ..." Via Leona Ungerer
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Posted by Mike Schuster (Google Brain Team), Melvin Johnson (Google Translate) and Nikhil Thorat (Google Brain Team) In the last 1
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Originally published by Jason Brownlee in 2013, it still is a goldmine for all machine learning professionals. The algorithms are broken down in several categories…
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This article explains in brief the differences between Machine Learning & Statistical modeling including the algorithms, required efforts, output & a case study.
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Deep learning. Neural networks. Backpropagation. Over the past year or two, I've heard these buzz words being tossed around a lot, and it's something that has definitely seized my curiosity recently. Deep learning is an area of active research these days, and if you've kept up with the field of computer science, I'm sure you've come across at least some of these terms at least once.
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Serdar Yegulalp, InfoWorld Tap the predictive power of machine learning with these diverse, easy-to-implement libraries and frameworks. Via Gonzalo San Gil, PhD.
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Using massive amounts of data to recognize photos and speech, deep-learning computers are taking a big step towards true artificial intelligence. Via Szabolcs Kósa, luiy
R Schumacher & Associates LLC's curator insight,
January 15, 2014 1:43 PM
The monikers such as "deep learning" may be new, but Artificial Intelligence has always been the Holy Grail of computer science. The applications are many, and the path is becoming less of an uphill climb. 
luiy's curator insight,
February 26, 2014 6:19 AM
Deep learning itself is a revival of an even older idea for computing: neural networks. These systems, loosely inspired by the densely interconnected neurons of the brain, mimic human learning by changing the strength of simulated neural connections on the basis of experience. Google Brain, with about 1 million simulated neurons and 1 billion simulated connections, was ten times larger than any deep neural network before it. Project founder Andrew Ng, now director of the Artificial Intelligence Laboratory at Stanford University in California, has gone on to make deep-learning systems ten times larger again.
Such advances make for exciting times in artificial intelligence (AI) — the often-frustrating attempt to get computers to think like humans. In the past few years, companies such as Google, Apple and IBM have been aggressively snapping up start-up companies and researchers with deep-learning expertise. For everyday consumers, the results include software better able to sort through photos, understand spoken commands and translate text from foreign languages. For scientists and industry, deep-learning computers can search for potential drug candidates, map real neural networks in the brain or predict the functions of proteins. |
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El término Pensamiento Computacional es propenso a ser malinterpretado. Y el hecho de que aún no exista una definición consensuada, no ayuda demasiado. Así que, en lugar de comenzar definiendo qué es el Pensamiento Computacional, vamos a comenzar por decir lo que NO es. Via Gumersindo Fernández
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where we explain machine learning concepts and how to get started using it, for real. Via Mickael Ruau, Bruno De Lièvre
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![[R] OpenAI: Better Language Models and Their Implications : MachineLearning | E-Learning-Inclusivo (Mashup) | Scoop.it](https://img.scoop.it/pcksbs3E6S-ddOryFchNgzl72eJkfbmt4t8yenImKBVvK0kTmF0xjctABnaLJIm9)
https://blog.openai.com/better-language-models/ "We’ve trained a large-scale unsupervised language model which generates coherent paragraph
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El MIT anuncia la creación de un nuevo centro, el Stephen A. Schwarzman College of Computing, dedicado a reorientar la institución para llevar el poder de la computación y la inteligencia artificial a todos los campos de estudio, posibilitando que el futuro de la computación y la inteligencia artificial se forme a partir de ideas de todas las otras disciplinas. Via Angel Acción Lamas
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The six concepts introduced here will help eLearning developers understand where machine learning can fit into online learning. Via Marta Torán
Marta Torán's curator insight,
February 21, 2018 3:57 PM
Katie Stroud escribe un artículo explicando de manera sencilla qué es Machine Learning. Aprendizaje Automático. Está de moda.
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Algorithms were supposed to free us from our unconscious mistakes. But now there’s a new set of problems to solve. "Although AI decision-making is often regarded as inherently objective, the data and processes that inform it can invisibly bake inequality into systems that are intended to be equitable. Avoiding that bias requires an understanding of both very complex technology and very complex social issues." (from the article) Via Sharrock
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By Ron Drabkin - Machine learning will be steadily adopted in a variety of educational technology tools. How will that affect you? Via Marta Torán
Marta Torán's curator insight,
April 8, 2017 2:36 PM
Algunas aplicaciones del Machine Learning en Educación. La "próxima gran cosa".
Personalización y adaptación. Analíticas de aprendizaje. Clasificación de recursos educativos.
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Le rôle et l'intérêt du ML, c'est un peu comme un physionomiste à l'entrée d'une discothèque...
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"Who here remembers taking computer programming in school? Whether you learned programming by punching holes in a never ending series of cards, or by ..." Via Leona Ungerer
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Machine learning is coming into a golden age, and with it we’re seeing an awakening of possibilities formerly reserved for science fiction. Via Pascale_Masson, Jean-Pierre Blanger
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From
gigaom
Though these technologies are complex, it’s crucial that we understand them and how they work since they are powering the next wave of applications, performing tasks so complicated that traditional programming techniques can’t solve them.
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