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Publicación sobre Inteligencia Artificial

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Deep Learning or Machine Learning? (MathWorks)

“In this ebook, we discuss some of the key differences between deep learning and traditional machine learning approaches. We look at three factors that might influence your decision and then step through an example that combines the two approaches”. (MathWorks).

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Artificial Intelligence in Society

“The artificial intelligence (AI) landscape has evolved significantly from 1950 when Alan Turing first posed the question of whether machines can think. Today, AI is transforming societies and economies. It promises to generate productivity gains, improve well-being and help address global challenges, such as climate change, resource scarcity and health crises. Yet, as AI applications are adopted around the world, their use can raise questions and challenges related to human values, fairness, human determination, privacy, safety and accountability, among others. This report helps build a shared understanding of AI in the present and near-term by mapping the AI technical, economic, use case and policy landscape and identifying major public policy considerations. It is also intended to help co-ordination and consistency with discussions in other national and international fora”. (OECD)

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Inteligencia artificial centrada en el ser humano: confiable y segura

El objetivo de este documento es alentar a los investigadores de inteligencia artificial y diseñadores de productos a cambiar del pensamiento unidimensional sobre los niveles de automatización / autonomía a un nuevo marco HCAI bidimensional.

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Matriz de recursos de Deep Learning

El siguiente recurso describe los siguientes marcos:
TensorFlow
Theano
Cafe
MXNet
apache
SystemML (proyecto de incubadora)
BigDL
DistBelief

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TPOT is a Python Automated Machine Learning tool

Consider TPOT your Data Science Assistant. TPOT is a Python Automated Machine Learning (AutoML) tool that optimizes machine learning pipelines using genetic programming.

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C++ Notes for Professionals book

C++ Notes for Professionals book is compiled from Stack Overflow Documentation,. 708 pages, published on May 2018

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AutoML: a introduction tutorial about H2O Driverless AI

“H2O has been the driver for building models at scale. We are talking about billions of claims. You can’t do this with standard off the shelf open source techniques”. (H2o.ai).