Der Security Awareness Computer Based Training-Marktforschungsbericht enthält ...


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Der Marktbericht für die Security Awareness Computer Based Training-Marktprognose 2020-2025 umfasst Hersteller, Typen, Anwendungen, ......
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Getting Started with Distributed TensorFlow on GCP

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Posted by Nikita Namjoshi, Machine Learning Solutions Engineer For many in the world of data science, distributed training can seem a daunting task. In addition to building and thoughtfully evaluating a high-quality ML model, you have to be aware of h

Announcing ML.NET 1.4 general availability (Machine Learning for .NET)

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Coinciding with the Microsoft Ignite 2019 conference, we are thrilled to announce the GA release of ML.NET 1.4 and updates to Model Builder in Visual Studio, with exciting new machine learning features that will allow you to innovate your .NET applicat

What's new with Red Hat Enterprise Linux (Rhel) 8?

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What's new with Red Hat Enterprise Linux (Rhel) 8? Red Hat Enterprise Linux (RHEL) 8 is based upon the principles of "operational consistency, security, and cloud foundation." Utilizing kernel 4.18x, RHEL 8 is based on Fedora 28 and will run on Intel/AMD 64-bi

Using ML.NET for deep learning on images in Azure

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Introduction In March 2020, ML.NET added support for training Image Classification models in Azure. Although the image classification scenario was released in late 2019, users were limited by the resources on their local compute environments. Training

What’s new in TensorFlow 2.4?

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Posted by Goldie Gadde and Nikita Namjoshi for the TensorFlow Team TF 2.4 is here! With increased support for distributed training and mixed precision, new NumPy frontend and tools for monitoring and diagnosing bottlenecks, this release is all about

Introducing the Model Garden for TensorFlow 2

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Posted by Jaeyoun Kim, Technical Program Manager, and Jing Li, Software EngineerWe would like to introduce an update to the Model Garden that provides TensorFlow users a centralized place to find code examples for state-of-the-art models and reusable modeling librar

USN-3415-1: tcpdump vulnerabilities

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Ubuntu Security Notice USN-3415-1 13th September, 2017 tcpdump vulnerabilities A security issue affects these releases of Ubuntu and its derivatives: Ubuntu 17.04 Ubuntu 16.04 LTS Ubuntu 14.04 LTS Summary Several security issues were fixe

USN-3415-2: tcpdump vulnerabilities

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Ubuntu Security Notice USN-3415-2 13th September, 2017 tcpdump vulnerabilities A security issue affects these releases of Ubuntu and its derivatives: Ubuntu 12.04 LTS Summary Several security issues were fixed in tcpdump Software description tcpdump

Train your TensorFlow model on Google Cloud using TensorFlow Cloud

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Posted by Jonah Kohn and Pavithra Vijay, Software Engineers at GoogleTensorFlow Cloud is a python package that provides APIs for a seamless transition from debugging and training your TensorFlow code in a local environment to distributed training in Goo

The 2019 SANS Security Awareness Report: Awareness Training Is Rising

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The Case for Security Awareness Training Cybersecurity and cyber security awareness are critical to business survival in an era dominated by growing virtual crime. It might be true that most people know about costly identity theft and reputation-destroying ne

PCFG Cracker - Probabilistic Context Free Grammar (PCFG) Password Guess Generator

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PCFG = Probabilistic Context Free GrammarPCFG = Pretty Cool Fuzzy GuesserIn short: A collection of tools to perform research into how humans generate passwords. These can be used to crack password hashes, but also create synthetic passwords (honeywords), or help develop better password strength algorithmsDocumentationAcademic Papers:Original 2009 IEEE Security and Privacy paper on PCFGs for password

Fine-tune natural language processing models using Azure Machine Learning service

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In the natural language processing (NLP) domain, pre-trained language representations have traditionally been a key topic for a few important use cases, such as named entity recognition (Sang and Meulder, 2003), question answering (Rajpurkar et al., 2016)

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