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Última actualización : Apr 24, 2019
Not on the current edition
This blip is not on the current edition of the Radar. If it was on one of the last few editions it is likely that it is still relevant. If the blip is older it might no longer be relevant and our assessment might be different today. Unfortunately, we simply don't have the bandwidth to continuously review blips from previous editions of the Radar Understand more
Apr 2019
Adoptar ? Creemos firmemente que la industria debería adoptar estos elementos. Nosotros los utilizamos cuando es apropiado para nuestros proyectos.

Over the past couple of years, we've noticed a steady rise in the popularity of analytics notebooks. These are Mathematica-inspired applications that combine text, visualization and code in a living, computational document. Jupyter Notebooks are widely used by our teams for prototyping and exploration in analytics and machine learning. We've moved Jupyter to Adopt for this issue of the Radar to reflect that it has emerged as the current default for Python notebooks. However, we caution to use Jupyter Notebooks in production.

May 2018
Probar ? Vale la pena intentarlo. Es importante entender cómo construir esta habilidad. Las empresas deberían implementar esta tecnología en un proyecto que pueda manejar el riesgo.

Over the last couple of years, we've noticed a steady rise in the popularity of analytics notebooks. These are Mathematica-inspired applications that combine text, visualization and code in a living, computational document. Increased interest in machine learning — along with the emergence of Python as the programming language of choice for practitioners in this field — has focused particular attention on Python notebooks, of which Jupyter seems to be gaining the most traction among ThoughtWorks teams. People seem to keep finding creative uses for Jupyter beyond a simple analytics tool. For example, see Jupyter for automated testing.

Nov 2017
Evaluar ? Vale la pena explorarlo con el objetivo de entender cómo afectará a tu empresa.

Over the last couple of years, we've noticed a steady rise in the popularity of analytics notebooks. These are Mathematica-inspired applications that combine text, visualization and code in a living, computational document. In a previous edition, we mentioned GorillaREPL, a Clojure variant of these. But increased interest in machine learning — along with the emergence of Python as the programming language of choice for practitioners in this field — has focused particular attention on Python notebooks, of which Jupyter seems to be gaining the most traction among Thoughtworks teams.

Publicado : Nov 30, 2017
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