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Exclusive Interview with Dr. Sunil Kumar Vuppala – A Deep Learning Expert and IoT Veteran

Analytics Vidhya

Introduction There are multiple ways to learn data science, machine learning and deep learning concepts. You can watch videos, read articles, enroll in courses, The post Exclusive Interview with Dr. Sunil Kumar Vuppala – A Deep Learning Expert and IoT Veteran appeared first on Analytics Vidhya.

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Artificial intelligence and machine learning adoption in European enterprise

O'Reilly on Data

In a recent survey , we explored how companies were adjusting to the growing importance of machine learning and analytics, while also preparing for the explosion in the number of data sources. As interest in machine learning (ML) and AI grow, organizations are realizing that model building is but one aspect they need to plan for.

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8 Microsoft Free Courses- AI, IoT, Machine Learning and Data Science

Analytics Vidhya

Ready to elevate your skills in Artificial Intelligence, the Internet of Things (IoT), Machine Learning, and Data Science? Whether you’re a seasoned pro looking to stay ahead […] The post 8 Microsoft Free Courses- AI, IoT, Machine Learning and Data Science appeared first on Analytics Vidhya.

IoT 190
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Highlights from the Strata Data Conference in New York 2018

O'Reilly on Data

Watch highlights from expert talks covering data science, machine learning, algorithmic accountability, and more. Preserving privacy and security in machine learning. Ben Lorica offers an overview of recent tools for building privacy-preserving and secure machine learning products and services. Watch " Wait.

IoT 217
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Choosing the right Machine Learning Framework

Domino Data Lab

Machine learning (ML) frameworks are interfaces that allow data scientists and developers to build and deploy machine learning models faster and easier. Machine learning is used in almost every industry, notably finance , insurance , healthcare , and marketing. How to choose the right ML Framework.

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Top 10 Data Innovation Trends During 2020

Rocket-Powered Data Science

2) MLOps became the expected norm in machine learning and data science projects. 3) Concept drift by COVID – as mentioned above, concept drift is being addressed in machine learning and data science projects by MLOps, but concept drift so much bigger than MLOps. will look like).

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Architect Machine Learning with IoT

Paul DeBeasi

Developers with no data science experience are now able to integrate Machine Learning (ML) with IoT. As the number of IoT endpoints proliferate, the need for organizations to understand how to architect machine learning with IoT will grow rapidly. IoT architects often focus on IoT infrastructure (e.g.,

IoT 75