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Category: Tutorial
Connecting On-premises Networks with Azure Virtual Networks

Connecting On-premises Networks with Azure Virtual Networks
MP4 | Video: AVC 1280x720 | Audio: AAC 44KHz 2ch | Duration: 1 Hour | 131 MB
Genre: eLearning | Language: English

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Category: Tutorial
Connecting Microsoft Azure Virtual Networks

Connecting WeiRuan-->WeiRuan Azure Virtual Networks
MP4 | Video: AVC 1280x720 | Audio: AAC 44KHz 2ch | Duration: 1 Hour | 166 MB
Genre: eLearning | Language: English

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Category: Tutorial
Deep Learning: Convolutional Neural Networks in Python (Updated 8/2018)
Deep Learning: Convolutional Neural Networks in Python (Updated 8/2018)
$120 | HIGHEST RATED | Last Updated 8/2018
Duration: 6.5 hours | Video: h264, 1280x720 | Audio: AAC, 48 KHz, 2 Ch | 1 GB
Genre: eLearning | Language: English + Sub | 47 Lectures

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Category: Tutorial
Managing Microsoft Azure Virtual Networks

Managing WeiRuan-->WeiRuan Azure Virtual Networks
MP4 | Video: AVC 1280x720 | Audio: AAC 44KHz 2ch | Duration: 1 Hour 39M | 261 MB
Genre: eLearning | Language: English

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Category: Tutorial
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F5-Networks-Administering-BIG-IP-v12 F5-NetAdmin-v12
English | Size: 180.04 MB /
Category: Networking | Security

F5 Networks Administering BIG-IP V12 (F5-NetAdmin-V12)
This course gives network administrators, network operators, and network engineers a functional understanding of the BIG-IP system as it is commonly deployed in an application delivery network. The course introduces students to the BIG-IP system, its configuration objects, how it processes traffic, and how typical administrative and operational activities are performed. The course includes lecture, hands-on labs, interactive demonstrations, and discussions.
Course Objectives
Describe the role of the BIG-IP system as a full proxy device in an application delivery network
Set up, start/restart/stop, license, and provision the BIG-IP system out-of-the-box
Create a basic network configuration on the BIG-IP system including VLANs and self IPs
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Category: Tutorial
Hands-On Neural Networks From Scratch for Absolute Beginners
Hands-On Neural Networks From Scratch for Absolute Beginners
.MP4, AVC, 1000 kbps, 1280x720 | English, AAC, 128 kbps, 2 Ch | 2h 21m | 1.22 GB
Created by John Williams

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Category: E-Book
Broadband Access Networks: Technologies and Deployments

Broadband Access Networks: Technologies and Deployments by Abdallah Shami
English | PDF | 2009 | 385 Pages | ISBN : 0387921303 | 10.13 MB
Broadband Access Networks: Technologies and Deployments presents the research, design, and deployment experience of state-of-the-art access networks. The material consolidates and disseminates the latest developments and advances in the area of broadband access network technologies and architectures. It discusses the emergent technologies developed and devised in the last few years as well as shares the many experiences and lessons learned from the deployments of field/testing trials of these technologies.
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Category: Tutorial
CompTIA Network+ (N10-007) Cert Prep: 1 Understanding Networks
CompTIA Network+ (N10-007) Cert Prep: 1 Understanding Networks
MP4 | Video: h264, 1280x720 | Audio: AAC, 48 KHz, 2 Ch
Genre: eLearning | Language: English + .SRT
Level: Beginner | Duration: 51m | 474 MB


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Category: E-Book
Peer to Peer Accommodation Networks

Peer to Peer Accommodation Networks: An Examination
Goodfellow | English | 2018 | ISBN-10: 1911396528 | 256 pages | PDF | 16.41 MB
by Sara Dolnicar (Author)
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Category: E-Book
Evolutionary Algorithms and Neural Networks: Theory and Applications

Evolutionary Algorithms and Neural Networks: Theory and Applications by Seyedali Mirjalili
English | PDF,EPUB | 2018 (2019 Edition) | 164 Pages | ISBN : 3319930249 | 12.28 MB
This book introduces readers to the fundamentals of artificial neural networks, with a special emphasis on evolutionary algorithms. At first, the book offers a literature review of several well-regarded evolutionary algorithms, including particle swarm and ant colony optimization, genetic algorithms and biogeography-based optimization. It then proposes evolutionary version of several types of neural networks such as feed forward neural networks, radial basis function networks, as well as recurrent neural networks and multi-later perceptron. Most of the challenges that have to be addressed when training artificial neural networks using evolutionary algorithms are discussed in detail. The book also demonstrates the application of the proposed algorithms for several purposes such as classification, clustering, approximation, and prediction problems. It provides a tutorial on how to design, adapt, and evaluate artificial neural networks as well, and includes source codes for most of the proposed techniques as supplementary materials.
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