Deep Learning with Azure (PDF)
Artificial Intelligence (AI) is the new normal. Innovations...
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- Becomefamiliar with the tools, infrastructure, and services available for deep learning on Microsoft Azure such as Azure Machine Learning services and Batch AI
- Use pre-built AI capabilities (Computer Vision, OCR, gender, emotion, landmark detection, and more)
- Understand the common deep learning models, including convolutional neural networks (CNNs), recurrent neural networks (RNNs), generative adversarial networks (GANs) with sample code and understand how the field is evolving
- Discover the options for training and operationalizing deep learning models on Azure
Danielle Dean, PhD is a principal data science lead at Microsoft in the Cloud and AI division, where she leads a team of data scientists and engineers building artificial intelligence solutions with external companies utilizing Microsoft's Cloud AI platform.
Wee Hyong Tok, PhD is a principal data science manager at Microsoft in the Cloud and AI division. He leads the AI for Earth Engineering and Data Science team, where his team of data scientists and engineers are working to advance the boundaries of state-of-the-art deep learning algorithms and systems.
Danielle Dean, PhD is a principal data science lead at Microsoft in the Cloud and AI division, where she leads a team of data scientists and engineers building artificial intelligence solutions with external companies utilizing Microsoft's Cloud AI platform. Previously, she was a data scientist at Nokia, where she produced business value and insights from big data through data mining and statistical modeling on data-driven projects that impacted a range of businesses, products, and initiatives. She has a PhD in quantitative psychology from the University of North Carolina at Chapel Hill, where she studied the application of multi-level event history models to understand the timing and processes leading to events between dyads within social networks.
Wee Hyong Tok, PhD is a principal data science manager at Microsoft in the Cloud and AI division. He leads the AI for Earth Engineering and Data Science team, where his team of data scientists and engineers are working to
- Autoren: Mathew Salvaris , Danielle Dean , Wee Hyong Tok
- 2018, 1st ed, 284 Seiten, Englisch
- Verlag: Springer-Verlag GmbH
- ISBN-10: 1484236793
- ISBN-13: 9781484236796
- Erscheinungsdatum: 24.08.2018
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- Dateiformat: PDF
- Grösse: 7.61 MB
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