A deep learning processor (DLP), or a deep learning accelerator, is an electronic circuit designed for deep learning algorithms, usually with separate data memory and dedicated instruction set architecture. Deep learning processors range from mobile devices, such as neural processing units (NPUs) in Huawei cellphones,to cloud computing servers such as tensor processing units (TPU) in the Google Cloud Platform. The goal of DLPs is to provide higher efficiency and performance for deep learning algorithms than general central processing unit (CPUs) and graphics processing units (GPUs) would. Most DLPs employ a large number of computing components to leverage high data-level parallelism, a relatively larger on-chip buffer/memory to leverage the data reuse patterns, and limited data-width operators for error-resilience of deep learning. Deep learning processors differ from AI accelerators in that they are specialized for running learning algorithms, while AI accelerators are typically more specialized for inference. However, the two terms (DLP vs AI accelerator) are not used rigorously and there is often overlap between the two. (Wikipedia).
Deep learning is a machine learning technique that learns features and tasks directly from data. This data can include images, text, or sound. The video uses an example image recognition problem to illustrate how deep learning algorithms learn to classify input images into appropriate ca
From playlist Introduction to Deep Learning
Deep Learning with R for Beginners
Deep learning (also known as deep structured learning) is part of a broader family of machine learning methods based on artificial neural networks with representation learning. Learning can be supervised, semi-supervised or unsupervised. #Deep_learning architectures such as deep neural ne
From playlist Deep Learning
Deep Learning Lecture 6.1 - Greetings
Unsupervised Learning 1: PCA and Autoencoders
From playlist Deep Learning Lecture
Deep Learning Course Purdue University Fall 2016 https://docs.google.com/document/d/1_p4Y_9Y79uBiMB8ENvJ0Uy8JGqhMQILIFrLrAgBXw60
From playlist Deep-Learning-Course
What is a Deep Learning Library? - Ep. 16 (Deep Learning SIMPLIFIED)
Deep Learning libraries provide pre-written, professional-quality code that you can use for your own projects. Given the complexity of deep net applications, reusing code is a wise choice for a developer. Deep Learning TV on Facebook: https://www.facebook.com/DeepLearningTV/ Twitter: htt
From playlist Deep Learning SIMPLIFIED
Solving Problems - Big and Small
This video is part of the Udacity course "Deep Learning". Watch the full course at https://www.udacity.com/course/ud730
From playlist Deep Learning | Udacity
Basic linear algebra for deep learning
This a series for healthcare professionals and anyone else interested in learning how to create deep neural networks. In this video tutorial I demonstrate the very basic principles of linear algebra. For a more comprehensive view of the topic watch my playlist here: https://www.youtube.c
From playlist Introduction to deep learning for everyone
This video is part of the Udacity course "Deep Learning". Watch the full course at https://www.udacity.com/course/ud730
From playlist Deep Learning | Udacity
Deep Learning Lecture 1.6 - Intro End
Deep Learning Lecture - Intro Conclusion
From playlist Deep Learning Lecture
Stanford Seminar - Petascale Deep Learning on a Single Chip
EE380: Computer Systems Colloquium Seminar Petascale Deep Learning on a Single Chip Speaker: Tapabrata Ghosh, Vathys Vathys.ai is a deep learning startup that has been developing a new deep learning processor architecture with the goal of massively improved energy efficiency and performan
From playlist Stanford EE380-Colloquium on Computer Systems - Seminar Series
GRCon19 - AI and SDR: Software Meets Hardware Again... by Manuel Uhm
AI and SDR: Software Meets Hardware Again... by Manuel Uhm, Jason Vidmar Over the course of the last 30 years, SDR has become the de facto industry standard for the implementation of waveforms for communications, both military and commercial. During that time, the desire for waveforms to
From playlist GRCon 2019
Image Classification on ARM CPU: SqueezeNet on Raspberry Pi
See a demonstration of image classification using deep learning on a Raspberry Pi™ from MATLAB using the Raspberry Pi support package. - Deep Learning Inference for Object Detection on Raspberry Pi: http://bit.ly/2E5I8zp - Raspberry Pi Support from MATLAB: http://bit.ly/2GLCIe2 - Deep L
From playlist Raspberry Pi Tutorials
Stanford Seminar: HPC Opportunities in Deep Learning - Greg Diamos, Baidu
EE380: Computer Systems Colloquium HPC Opportunities in Deep Learning Speaker: Greg Diamos, Baidu Just this year, deep learning has fueled significant progress in computer vision, speech recognition, and natural language processing. We have seen a computer beat the world champion in Go
From playlist Stanford EE380-Colloquium on Computer Systems - Seminar Series
Running a Deep Learning Network on an FPGA to Detect Defects
See how to deploy a deep learning network from MATLAB® to a ZCU102 board and run predictions. Learn how to use the network to detect defects in the parts. - Embedded Systems | Developer Tech Showcase Playlist: https://www.youtube.com/playlist?list=PLn8PRpmsu08oYCg_v4ZZ6xmJlo3242Asj - AI
From playlist AI, Machine Learning, Data Science | Developer Tech Showcase
All about AI Accelerators: GPU, TPU, Dataflow, Near-Memory, Optical, Neuromorphic & more (w/ Author)
#ai #gpu #tpu This video is an interview with Adi Fuchs, author of a series called "AI Accelerators", and an expert in modern AI acceleration technology. Accelerators like GPUs and TPUs are an integral part of today's AI landscape. Deep Neural Network training can be sped up by orders of
From playlist All Videos
Stanford Seminar - NVIDIA GPU Computing: A Journey from PC Gaming to Deep Learning
EE380: Computer Systems Colloquium Seminar NVIDIA GPU Computing: A Journey from PC Gaming to Deep Learning Speaker: Stuart Oberman, NVIDIA Deep Learning and GPU Computing are now being deployed across many industries, helping to solve big data problems ranging from computer vision and na
From playlist Stanford EE380-Colloquium on Computer Systems - Seminar Series
CUDA Explained - Why Deep Learning uses GPUs
Artificial intelligence with PyTorch and CUDA. Let's discuss how CUDA fits in with PyTorch, and more importantly, why we use GPUs in neural network programming. Strange Loop: https://youtu.be/DBVLcgq2Eg0?t=1340 🕒🦎 VIDEO SECTIONS 🦎🕒 00:00 Welcome to DEEPLIZARD - Go to deeplizard.com for l
From playlist PyTorch - Python Deep Learning Neural Network API
IU PTI Workshop: IBM High Performance Computing with NVIDIA
Presented January 26, 2017. Dramatic shifts in the information technology industry offer new kinds of performance capabilities and throughput. Professionals in HPC, Deep Learning, Big Data Analytics and Life Sciences learned more about industry trends & directions and IT solutions from NV
From playlist Seminars/Workshops
Data Science PC Configs: From Low Range to Super-High Range
In this video, I will tell you which parts you should buy for building a home PC for machine learning and data science. Check out the details of NVIDIA Titan RTX here: https://nvda.ws/309DJGp Follow Damien here: https://twitter.com/Laurae_Cht Very-low range: https://pcpartpicker.com/lis
From playlist TITAN RTX YOUTUBERS
1.1 Machine Learning: an introduction
Deep Learning Course Purdue University Fall 2016
From playlist Deep-Learning-Course