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Top 10 Data Innovation Trends During 2020

Rocket-Powered Data Science

Customer purchase patterns, supply chain, inventory, and logistics represent just a few domains where we see new and emergent behaviors, responses, and outcomes represented in our data and in our predictive models. 7) Deep learning (DL) may not be “the one algorithm to dominate all others” after all. will look like).

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15 best data science bootcamps for boosting your career

CIO Business Intelligence

The course includes instruction in statistics, machine learning, natural language processing, deep learning, Python, and R. Due to the short nature of the course, it’s tailored to those already in the industry who want to learn more about data science or brush up on the latest skills. Remote courses are also available.

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The unreasonable importance of data preparation

O'Reilly on Data

This need will grow as smart devices, IoT, voice assistants, drones, and augmented and virtual reality become more prevalent. A bright future would see data preparation and data quality as first-class citizens in the data workflow, alongside machine learning, deep learning, and AI.

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How Big Data Has Become Integral to Commercial Fleet Success

Smart Data Collective

A critical component of smarter data-driven operations is commercial IoT or IIoT, which allows for consistent and instantaneous fleet tracking. The global IoT fleet management market is expected to reach $17.5 Predictive models, estimates and identified trends can all be sent to the project management team to speed up their decisions.

Big Data 100
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The Cloud Connection: How Governance Supports Security

Alation

They strove to ramp up skills in all manner of predictive modeling, machine learning, AI, or even deep learning. Organizations launched initiatives to be “ data-driven ” (though we at Hired Brains Research prefer the term “data-aware”).

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Topics to watch at the Strata Data Conference in New York 2019

O'Reilly on Data

Our call for speakers for Strata NY 2019 solicited contributions on the themes of data science and ML; data engineering and architecture; streaming and the Internet of Things (IoT); business analytics and data visualization; and automation, security, and data privacy. Deep learning,” for example, fell year over year to No.

IoT 20