Article: The Five Ways To Build Machine Learning Models

Free, Language, Libre, Open Data, Open Software

The Five Ways To Build Machine Learning Models

Machine learning is powering most of the recent advancements in AI, including computer vision, natural language processing, predictive analytics, autonomous systems, and a wide range of applications. Machine learning systems are core to enabling each of these seven patterns of AI.

In order to move up the data value chain from the information level  to the knowledge level, we need to apply machine learning that will enable systems to identify patterns in data and learn from those patterns to apply to new, never before seen data. Machine learning is not all of AI, but it is a big part of it.

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Article: Reactive, reproducible, collaborative: computational notebooks evolve

Document, Free, Libre, Open Software, Research

Reactive, reproducible, collaborative: computational notebooks evolve

This year marks ten years since the launch of the IPython Notebook. The open-source tool, now known as the Jupyter Notebook, has become an exceedingly popular piece of data-science kit, with millions of notebooks deposited to the GitHub code-sharing site.

Computational notebooks combine code, results, text and images in a single document, yielding what Stephen Wolfram, creator of the Mathematica software package, has called a “computational essay”. And whether written using Jupyter, Mathematica, RStudio or any other platform, researchers can use them for iterative data exploration, communication, teaching and more.

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