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10 Examples of How Big Data in Logistics Can Transform The Supply Chain

datapine

You can use big data analytics in logistics, for instance, to optimize routing, improve factory processes, and create razor-sharp efficiency across the entire supply chain. Did you know? According to studies, 92% of data leaders say their businesses saw measurable value from their data and analytics investments.

Big Data 275
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Top 10 Data Innovation Trends During 2020

Rocket-Powered Data Science

The year 2020 was remarkably different in many ways from previous years. In at least one way, it was not different, and that was in the continued development of innovations that are inspired by data. 1) Automated Narrative Text Generation tools became incredibly good in 2020, being able to create scary good “deep fake” articles.

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Deciphering The Seldom Discussed Differences Between Data Mining and Data Science

Smart Data Collective

You should learn what a big data career looks like , which involves knowing the differences between different data processes. Online courses and universities are offering a growing number of programs of study that center around the data science specialty. The first thing you see is that the areas of applications are very different.

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Pros and Cons of Having a Data-Driven eCommerce Business on Amazon

Smart Data Collective

There are many ways that you can use big data to create a profitable business. One of the smartest ways for entrepreneurs to utilize data is by creating an ecommerce business. You can run a profitable ecommerce business through Amazon. You can leverage these benefits even more by utilizing big data.

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Where Programming, Ops, AI, and the Cloud are Headed in 2021

O'Reilly on Data

Sometimes they’re only apparent if you look carefully at the data; sometimes it’s just a matter of keeping your ear to the ground. This study is based on title usage on O’Reilly online learning. We made a (very) few exceptions, usually when there are two different ways to search for the same concept. Methodology.

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Why you should care about debugging machine learning models

O'Reilly on Data

Not least is the broadening realization that ML models can fail. This article is meant to be a short, relatively technical primer on what model debugging is, what you should know about it, and the basics of how to debug models in practice. That’s where model debugging comes in.

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Themes and Conferences per Pacoid, Episode 6

Domino Data Lab

Spoiler alert: a research field called curiosity-driven learning is emerging at the nexis of experimental cognitive psychology and industry use cases for machine learning, particularly in gaming AI. Overall, these topics are among the themes you can expect at the next Rev , see you there! Introduction. This is not that.