Machine Learning

All about machine learning and deep learning

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What is TensorFlow? The machine learning library explained

TensorFlow is a Python-friendly open source library for numerical computation that makes machine learning faster and easier

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Virtual assistants don’t need developers or AI

Virtual assistants could do so much more for enterprises, if only we’d realize they are essentially command-line interfaces that don’t require custom coding or AI tech to work

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Why today’s real-time economy needs machine learning

The combined power of machine learning and artificial intelligence enable industries to process, analyze, and act on data in real time

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Review: Amazon SageMaker scales deep learning

AWS machine learning service offers easy scalability for training and inference, includes a good set of algorithms, and supports any others you supply

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ML Kit: Google brings machine learning APIs to mobile developers

The beta machine learning kit supports iOS and Android apps via the Firebase IDE and with TensorFlow Lite support

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Real-time AI gets closer with Project Brainwave

Microsoft’s Project Brainwave extends Azure ML to datacenter and network hardware, to bring the machine learning processing where the data is

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A lesson on today’s AI for the masses

When it comes to off-the-shelf artificial intelligence solutions, the more things change, the more they stay the same

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What’s new in TensorFlow machine learning

Google’s TensorFlow 1.8 machine learning library adds improved support for Google Cloud TPUs and prefetching to GPU memory

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Python developers profiled: What you use, what you do

A survey of 9,500 developers shows what Python programmers use and what they work on. See how typical you are as a Python developer

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Why you should use Python for machine learning

Learn why Python has become the go-to programming language for machine learning and deep learning applications

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The 5 best programming languages for AI development

Which programming language should you pick for your machine learning or deep learning project? These are your best options

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Monetizing your models with machine learning solutions

Connecting the business user to the science is a necessary step for companies looking to extend their leadership position

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‘To supervise or not to supervise’ is a question at the heart of machine learning

A guide to unsupervised and supervised machine learning and understanding their application by businesses today

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Demystifying machine learning

Businesses need more than a machine learning engine or framework to successfully extract the valuable and actionable insights from their data—and not all machine learning solutions are created equal

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Google Cloud tutorial: Get started with Google Cloud

From virtual machines and Kubernetes clusters to serverless functions and machine learning APIs — how to navigate Google’s cloud riches

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How to get started with AI—before it’s too late

Put these five prerequisites in place so you can actually execute on your artificial intelligence strategy

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Data governance 2.0

Part 1 of a conversation with Jason Fishbain, chief data officer, University of Wisconsin at Madison

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Is the cloud the key to democratizing AI?

How cloud services are springing up to offer AI to companies that may otherwise lack the skills

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