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Artificial Intelligence in Society

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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Machine learning in Python: the top programming language

Machine learning in Python: the top programming language

Phyton’s most notable points are:
-Is a great library ecosystem (Scikit-learn, Pandas, Matplotlib, NLTK, Scikit-image, PyBrain, Caffe, StatsModels, TensorFlow, Keras, etc).
-Growing popularity.
-Has a low entry barrier, has flexibility, is a platform independence, has readability, good visualization options, good community support and growing popularity.

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