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6 trends framing the state of AI and ML

O'Reilly on Data

We use it as a data source for our annual platform analysis , and we’re using it as the basis for this report, where we take a close look at the most-used and most-searched topics in machine learning (ML) and artificial intelligence (AI) on O’Reilly [1]. Reinforcement learning fell by 5% in 2019; it’s up hugely—1,500+%—since 2017, however.

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Towards optimal experimentation in online systems

The Unofficial Google Data Science Blog

Experiments, Parameters and Models At Youtube, the relationships between system parameters and metrics often seem simple — straight-line models sometimes fit our data well. To find optimal values of two parameters experimentally, the obvious strategy would be to experiment with and update them in separate, sequential stages.

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Digital listening reveals 3 leading innovation drivers

CIO Business Intelligence

It surpasses blockchain and metaverse projects, which are viewed as experimental or in the pilot stage, especially by established enterprises. higher [in 2022] than in 2017.” Big Data collection at scale is increasing across industries, presenting opportunities for companies to develop AI models and leverage insights from that data.

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Themes and Conferences per Pacoid, Episode 6

Domino Data Lab

In Paco Nathan ‘s latest column, he explores the role of curiosity in data science work as well as Rev 2 , an upcoming summit for data science leaders. Welcome back to our monthly series about data science. and dig into details about where science meets rhetoric in data science. Introduction. This is not that.

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Havmor’s VP IT Dhaval Mankad on ‘melting’ hurdles with a scoop of digital innovation

CIO Business Intelligence

My prominent achievements include managing the intricate implementation of GST and its setup in L&T in 2017 and at Havmor, where I recently completed 5 years, the SAP S4 HANA Greenfield implementation. What are some of the unique data and cybersecurity challenges that Havmor faces as a vast customer-centric business?

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On the Hunt for Patterns: from Hippocrates to Supercomputers

Ontotext

Ever since Hippocrates founded his school of medicine in ancient Greece some 2,500 years ago, writes Hannah Fry in her book Hello World: Being Human in the Age of Algorithms , what has been fundamental to healthcare (as she calls it “the fight to keep us healthy”) was observation, experimentation and the analysis of data.

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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. In this case, code gets generated for data preparation, where so much of the “time and labor” in data science work is concentrated.

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