AI News, BOOK REVIEW: Data Science and Artificial Intelligence artificial intelligence

AI for Data Science: Artificial Intelligence Frameworks and Functionality for Deep Learning, Optimization, and Beyond by Yunus Emrah Bulut, Zacharias Voulgaris PhD

Closing Thoughts Our hope is that you have received a very broad yet practical perspective on AI from this book.

Since this field changes so rapidly, with advances in AI coming from both older and newer players around the world, keep your eyes out for the upcoming second edition!

Artificial Intelligence and Data Analytics: 2019 Trends That Might Impact You

Artificial intelligence (AI) and data analytics are much more than intriguing, possibilities expanding topics – they’re disruptive technologies for your business.

Here’s a look at DMI’s list of important AI and analytics trends: Applying artificial intelligence algorithms to data analytics will prove transformative but the complex merger requires a roadmap – which most organizations don’t yet have.

However, DMI points out that while right now AI and data analytics are used mostly for customer interaction, a combination can glean insights that can be used across an entire business.

Maybe it’s the AI version of “Wonder Twin powers, activate!” DMI contents that AI and data analytics are crucial to the development of “digital twins” or computerized facsimiles of physical processes like a production line in a factory.

Quiz: How Well Do You Understand Blockchain?  With better security, more government agencies and healthcare organizations will embrace the cloud in 2019, writes DMI, generating huge new datasets to inform advanced machine learning.

Emerging Technologies Initiative for Network Intelligence

The objective of the Data Science and Artificial Intelligence for Communications Series of the IEEE Communications Magazine is to provide a forum across industry and academia to advance the development of network and system solutions using data science and artificial intelligence.

Innovations in artificial intelligence, machine learning, reinforcement learning and network data analytics introduce new opportunities in various areas, such as channel modeling and estimation, cognitive communications, interference alignment, mobility management, resource allocation, network control and management, network tomography, multi-agent systems, prioritization of network ultra-broadband deployments.

For detailed submission guidelines please refer to the magazine website for the list of guidelines that must be followed by all submissions to the IEEE Communications Magazine: https://www.comsoc.org/commag/paper-submission-guidelines Authors are encouraged to contact the Series Editor before submitting an article in order to ensure that the article will be appropriate for the Series.

Artificial Intelligence Vs Machine Learning Vs Data science Vs Deep learning

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