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Core technologies and tools for AI, big data, and cloud computing

O'Reilly on Data

Recent improvements in tools and technologies has meant that techniques like deep learning are now being used to solve common problems, including forecasting, text mining and language understanding, and personalization. AI and machine learning in the enterprise. Deep Learning. Foundational data technologies.

Big Data 209
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Themes and Conferences per Pacoid, Episode 8

Domino Data Lab

Paco Nathan ‘s latest column dives into data governance. This month’s article features updates from one of the early data conferences of the year, Strata Data Conference – which was held just last week in San Francisco. Introduction. Welcome back to our monthly burst of themes and conferences.

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Data Science, Past & Future

Domino Data Lab

data science’s emergence as an interdisciplinary field – from industry, not academia. why data governance, in the context of machine learning is no longer a “dry topic” and how the WSJ’s “global reckoning on data governance” is potentially connected to “premiums on leveraging data science teams for novel business cases”.

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Themes and Conferences per Pacoid, Episode 11

Domino Data Lab

Paco Nathan ‘s latest article covers program synthesis, AutoPandas, model-driven data queries, and more. In other words, using metadata about data science work to generate code. ” BTW, that Knuth article from 1983 was probably the first time that I ever saw the word “Web” used as a computer-related meaning.

Metadata 105
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Becoming a machine learning company means investing in foundational technologies

O'Reilly on Data

Here are some typical ways organizations begin using machine learning: Build upon existing analytics use cases: e.g., one can use existing data sources for business intelligence and analytics, and use them in an ML application. Use ML to unlock new data types—e.g., A typical data pipeline for machine learning.