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Intelligent assistants and the enterprise
While there is still room for improvement, with continued use, training and adoption, these intelligent assistants will soon deliver the benefits promised of AI.
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Inside look at methods to quell machine learning bias
Machine learning expert Ben Cox of H2O.ai discusses the problem of bias in predictive models that confronts data scientists daily and his techniques to identify and neutralize it.
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Google Cloud, Harvard release COVID-19 Public Forecasts
Google Cloud, in partnership with the Harvard Global Health Institute, released public models that can predict new COVID-19 cases, deaths and hospitalizations 14 days out.
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Autoencoders streamline machine learning algorithms
Autoencoders are neural networks that serve machine learning models -- from denoising to dimensionality reduction. Seven use cases explore the practical application of autoencoder technology.
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We designed this expert guide to help you better understand all of the considerations for building and maintaining the infrastructure and engine that support the initiatives. Plus, learn about the products and players, like Amazon, Google, IBM, and 16 more to help you make the best buying decision.
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AI careers Manage
4 AI career path trajectories for IT professionals
As the desire for AI and machine learning in-house skills skyrocket, those looking to break into the market have a variety of career path options, including AI architect and BI developer.
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Big data and machine learning Evaluate
Deep learning's role in the evolution of machine learning
Machine learning has continued to evolve since its beginnings some seven decades ago. Learn how deep learning has catalyzed a new phase in the evolution of machine learning.
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AI case studies News
Using ModelOps, a financial services company scales out
Using model operations (ModelOps), a fintech startup was able to scale up its model deployment quickly, while also maintaining model governance at scale.
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Neural networks and deep learning Evaluate
Autoencoders streamline machine learning algorithms
Autoencoders are neural networks that serve machine learning models -- from denoising to dimensionality reduction. Seven use cases explore the practical application of autoencoder technology.
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AI technologies News
Process automation in education helps school during COVID-19
Using process automation, a school in Sydney helped keep classes going online by automating the daily roll call process. Organizations have increasingly turned to automation and AI during COVID-19.
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AI business strategies Evaluate
Intelligent assistants and the enterprise
While there is still room for improvement, with continued use, training and adoption, these intelligent assistants will soon deliver the benefits promised of AI.
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Find Solutions For Your Project
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Evaluate
Intelligent assistants and the enterprise
While there is still room for improvement, with continued use, training and adoption, these intelligent assistants will soon deliver the benefits promised of AI.
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Autoencoders streamline machine learning algorithms
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How AI is making gamers emotional
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GAN applications and the enterprise
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Problem Solve
Inside look at methods to quell machine learning bias
Machine learning expert Ben Cox of H2O.ai discusses the problem of bias in predictive models that confronts data scientists daily and his techniques to identify and neutralize it.
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Dismantling the black box
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6 ways to reduce different types of bias in machine learning
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Solving AI's last-mile delivery problem
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The artificial intelligence of things
The combination of artificial intelligence and IoT has led to better predictive capabilities for devices, informed data storage, and enterprise machine optimization.
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Inside the rise of AIOps and MLOps
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AI in tax preparation gets a boost from classification tech
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How to build a machine learning model in 7 steps
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E-Handbook | November 2019
Data visualization process yields 360 AI-driven analytics view
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E-Handbook | October 2019
Neural network applications in business run wide, fast and deep
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E-Handbook | July 2019
Machine learning platform architecture demands deep analysis
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Buyer's Handbook | June 2019
Pinpoint the right RPA products to advance your organization
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E-Handbook | May 2019
Computer vision AI looks beyond the narrow into the mainstream
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Enterprise Artificial Intelligence Basics
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unsupervised learning
Unsupervised learning refers to the use of artificial intelligence (AI) algorithms to identify patterns in data sets containing data points that are neither classified nor labeled.
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supervised learning
Supervised learning is an approach to creating artificial intelligence, where the program is given labeled input data and the expected output results.
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Learn the business value of AI's various techniques
To drive business value from AI, business managers need to distinguish between the various AI techniques, starting with the many flavors of machine learning.
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AI evolution timeline: A decade perspective
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Vendor Resources
- Maximum Efficiency for Inferencing with Your AI Workloads on HPE ProLiant And ... –Data Sheet
- Development of a Highly Autonomous Driving Infrastructure –White Paper
- Taking the Enterprise AI Journey –Analyst Report
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AI technologies
Google Cloud, Harvard release COVID-19 Public Forecasts
Google Cloud, in partnership with the Harvard Global Health Institute, released public models that can predict new COVID-19 cases, deaths and hospitalizations 14 days out.
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Artificial intelligence platforms
Intuit AI, knowledge engineering help power Aid Assist
The principal product manager at Intuit talks about the company's use of machine learning, natural language processing and knowledge engineering in its new Aid Assist tool.
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AI technologies
Salesforce's AI-powered Einstein Call Coaching now available
Salesforce's Einstein Call Coaching has moved out of pilot testing, during which a steel building manufacturer saw a 60% reduction in time spent manually analyzing customer calls.