Network performance refers to measures of service quality of a network as seen by the customer. There are many different ways to measure the performance of a network, as each network is different in nature and design. Performance can also be modeled and simulated instead of measured; one example of this is using state transition diagrams to model queuing performance or to use a Network Simulator. (Wikipedia).
Network Security, Part 1 : Basic Encryption Techniques
Fundamental concepts of network security are discussed. It provides a good overview of secret Key and public key Encryption. Important data encryption standards are presented.
From playlist Network Security
What Is Network Security? | Introduction To Network Security | Network Security Tutorial|Simplilearn
In this video on What is Network Security, we will give you a small introduction to network security and cover its working and types. We also take a look at the transport and application layer security protocols, and end the tutorial by learning about some key tools and benefits of network
From playlist Networking
If you are interested in learning more about this topic, please visit http://www.gcflearnfree.org/ to view the entire tutorial on our website. It includes instructional text, informational graphics, examples, and even interactives for you to practice and apply what you've learned.
From playlist Networking
From playlist Communications & Network Systems
If you are interested in learning more about this topic, please visit http://www.gcflearnfree.org/ to view the entire tutorial on our website. It includes instructional text, informational graphics, examples, and even interactives for you to practice and apply what you've learned.
From playlist The Internet
GRCon19 - Performance Evaluation of MIMO Techniques With an SDR-Based Prototype by Evariste Some
Performance Evaluation of MIMO Techniques With an SDR-Based Prototype by Evariste Some, Kevin K Gifford There is tremendous pressure on modern wireless communication systems. First, there are more people than ever using wireless communications as their primary source of information and co
From playlist GRCon 2019
Computer Literacy - (unit 4) - the internet - 1 of 4
Forth unit of a series for newbie computer users. See http://proglit.com/computer-skills/ for additional information and material.
From playlist Computer Literacy - (unit 4) - the internet
An intro to the core protocols of the Internet, including IPv4, TCP, UDP, and HTTP. Part of a larger series teaching programming. See codeschool.org
From playlist The Internet
Computer Literacy - (unit 4) - the internet - 2 of 4
Forth unit of a series for newbie computer users. See http://proglit.com/computer-skills/ for additional information and material.
From playlist Computer Literacy - (unit 4) - the internet
Lottery Ticket Hypothesis paper presentation (live stream)
A live stream where Prince Grover summarizes the famous Lottery Ticket Hypothesis paper. Follow Prince on Twitter @groverpr4 or find his blog at https://medium.com/@pgrover3. Join my FREE course Basics of Graph Neural Networks (https://www.graphneuralnets.com/p/basics-of-gnns/?src=yt)!
From playlist Live Talks
Reinhard Heckel - The role of data and models for deep-learning based image reconstruction
Recorded 01 December 2022. Reinhard Heckel of the Technical University of Munich presents "The role of data and models for deep-learning based image reconstruction" at IPAM's Multi-Modal Imaging with Deep Learning and Modeling Workshop. Abstract: Deep-learning methods give state-of-the-art
From playlist 2022 Multi-Modal Imaging with Deep Learning and Modeling
Kaggle Reading Group: Weight Agnostic Neural Networks (Part 2) | Kaggle
Today we're continuing with the paper "Weight Agnostic Neural Networks" by Gaier & Ha from NeurIPS 2019. Link to paper: https://arxiv.org/pdf/1906.04358.pdf SUBSCRIBE: https://www.youtube.com/c/kaggle?sub_... About Kaggle: Kaggle is the world's largest community of data scientists. Join
From playlist Kaggle Reading Group | Kaggle
One Neural network learns EVERYTHING ?!
We explore a neural network architecture that can solve multiple tasks: multimodal Neural Network. We discuss important components and concepts along the way. If you like this video, hit that like button. If you really like this video, hit that SUBSCRIBE button. And if you just love me hi
From playlist Deep Learning Research Papers
The Evolution of Convolution Neural Networks
From the one that started it all "LeNet" (1998) to the deeper networks we see today like Xception (2017), here are some important CNN architectures you should know. If you like the video, show your support with a like, and SUBSCRIBE for more awesome content on Machine Learning, deep Learni
From playlist Deep Learning Research Papers
NVIDIA Deep Learning Course Class #1 – Introduction to Deep Learning
Register for the full course at https://developer.nvidia.com/deep-learning-courses This first in a series of webinars Introduction to Deep Learning covers basics of Deep Learning, why it excels when running on GPUs, and the three major frameworks available for taking advantage of Deep Lear
From playlist Deep Neural Networks
The Lottery Ticket Hypothesis: Finding Sparse, Trainable Neural Networks
Stunning evidence for the hypothesis that neural networks work so well because their random initialization almost certainly contains a nearly optimal sub-network that is responsible for most of the final performance. https://arxiv.org/abs/1803.03635 Abstract: Neural network pruning techn
From playlist Deep Learning Architectures
When BERT Plays the Lottery, All Tickets Are Winning (Paper Explained)
BERT is a giant model. Turns out you can prune away many of its components and it still works. This paper analyzes BERT pruning in light of the Lottery Ticket Hypothesis and finds that even the "bad" lottery tickets can be fine-tuned to good accuracy. OUTLINE: 0:00 - Overview 1:20 - BERT
From playlist Papers Explained
Stanford Seminar - Computing with Physical Systems
Peter McMahon, Cornell University June 1, 2022 With conventional digital computing technology reaching its limits, there has been a renaissance in analog computing across a wide range of physical substrates. In this talk I will introduce the concept of Physical Neural Networks [1] and des
From playlist Stanford EE380-Colloquium on Computer Systems - Seminar Series
In this video we discuss the definition and physical meaning of the bandwidth of a dynamic system. We’ll see that this is a performance metric that is used to assess the ability of the system to respond to time-varying signals, particularly sinusoidal inputs. This effectively measures ho
From playlist Control Theory