Installing CPU and GPU TensorFlow on Windows
In this tutorial, we cover how to install both the CPU and GPU version of TensorFlow onto 64bit Windows 10 (also works on Windows 7 and 8). TensorFlow is a Python library for doing operations on tensors, which is used for machine learning in general, but mostly deep learning.
From playlist Machine Learning with Python
Calculus 3: Tensors (1 of 28) What is a Tensor?
Visit http://ilectureonline.com for more math and science lectures! In this video I will explain what is a tensor. A tensor is a mathematical representation of a scalar (tensor of rank 0), a vector (tensor of rank 1), a dyad (tensor of rank 2), a triad (tensor or rank 3). Next video in t
From playlist CALCULUS 3 CH 10 TENSORS
Crash Course on TensorFlow Tensors and their Applications
We discuss the most important features of tensors in TensorFlow, useful tensor methods you should know, and where you would use them in your Deep Learning projects. Notebook Link: https://colab.research.google.com/drive/1Zcrw257e9XjInjTwz-pHtrJ_YuEsR45u?usp=sharing TIMESTAMPS: 0:00 Int
From playlist Math for Machine Learning
A Concrete Introduction to Tensor Products
The tensor product of vector spaces (or modules over a ring) can be difficult to understand at first because it's not obvious how calculations can be done with the elements of a tensor product. In this video we give an explanation of an explicit construction of the tensor product and work
From playlist Tensor Products
Introduction To TensorFlow 2.0
TensorFlow 2.0 is all about ease of use, and there has never been a better time to get started. In this talk, we will introduce model-building styles for beginners and experts, including the Sequential, Functional, and Subclassing APIs. We will share complete, end-to-end code examples in e
From playlist Machine Learning
Tensor Analysis and Applications
Tensors are used in various areas of mathematics and physics, particularly in theoretical calculations involving fields in vector spaces. The Einstein's summation convention implies summation over the dummy indices that appear twice in a term as in matrix-matrix or matrix-vector products.
From playlist Wolfram Technology Conference 2021
What Is A Tensor Lesson #1: Elementary vector spaces
We define a vector space and lay the foundation of a solid understanding of tensors.
From playlist What is a Tensor?
Lek-Heng Lim: "What is a tensor? (Part 1/2)"
Watch part 2/2 here: https://youtu.be/Lkpmd5-mpHY Tensor Methods and Emerging Applications to the Physical and Data Sciences Tutorials 2021 "What is a tensor? (Part 1/2)" Lek-Heng Lim - University of Chicago, Statistics Abstract: We discuss the three best-known definitions of a tensor:
From playlist Tensor Methods and Emerging Applications to the Physical and Data Sciences 2021
Lek-Heng Lim: "What is a tensor? (Part 2/2)"
Watch part 1/2 here: https://youtu.be/MkYEh0UJKcE Tensor Methods and Emerging Applications to the Physical and Data Sciences Tutorials 2021 "What is a tensor? (Part 2/2)" Lek-Heng Lim - University of Chicago, Statistics Abstract: We discuss the three best-known definitions of a tensor:
From playlist Tensor Methods and Emerging Applications to the Physical and Data Sciences 2021
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
Ming Yuan: "Low Rank Tensor Methods in High Dimensional Data Analysis (Part 1/2)"
Watch part 2/2 here: https://youtu.be/5IA4z9On3Mg Tensor Methods and Emerging Applications to the Physical and Data Sciences Tutorials 2021 "Low Rank Tensor Methods in High Dimensional Data Analysis (Part 1/2)" Ming Yuan - Columbia University, Statistics Abstract: Large amount of multid
From playlist Tensor Methods and Emerging Applications to the Physical and Data Sciences 2021
Design of the parametric Kalman filter dynamics... - Pannekoucke - Workshop 2 - CEB T3 2019
Pannekoucke (Meteo France, FR) / 13.11.2019 Design of the parametric Kalman filter dynamics: from the symbolic computation to the numerical integration ---------------------------------- Vous pouvez nous rejoindre sur les réseaux sociaux pour suivre nos actualités. Facebook : htt
From playlist 2019 - T3 - The Mathematics of Climate and the Environment
Stanford Seminar - fastai: A Layered API for Deep Learning
Jeremy Howard fastai and University of San Francisco February 19, 2020 fastai is a deep learning library which provides practitioners with high-level components that can quickly and easily provide state-of-the-art results in standard deep learning domains, and provides researchers with l
From playlist Stanford EE380-Colloquium on Computer Systems - Seminar Series
Stanford Seminar - Dataflow for convergence of AI and HPC - GroqChip!
Dennis Abts, Groq Oskar Mencer, Maxeler/Groq May 18, 2022 This talk provides a journey through Dataflow history, arriving at the recent convergence of AI and HPC, with the novel Groq architecture, the tensor streaming processor (TSP), combining elements from traditional dataflow architect
From playlist Stanford EE380-Colloquium on Computer Systems - Seminar Series
Live Stream #135: May 4th Challenge + TensorFlow.js Continued
In this live stream, I attempt a Star Wars themed coding challenge. I also continue tutorials about TensorFlow.js. Finally, I create a 2D water simulation in Processing. 12:40 - May 4th challenge 46:03 - TensorFlow.js: Variables + Operations 1:36:20 - TensorFlow.js: Memory management 2:06
From playlist Live Stream Archive
Keras vs TensorFlow vs Pytorch | Deep Learning Frameworks Comparison 2021 | Simplilearn
With the Deep Learning scene being dominated by three main frameworks, it is very easy to get confused on which one to use? In this video on Keras vs Tensorflow vs Pytorch, we will clear all your doubts on which framework is better and which framework should be used by beginners, intermedi
From playlist AI & Machine Learning | Ronald Van Loon [2022 Updated]
Quantum Simulating Gauge Theories: from Tensor field theory to Rydberg Atom.... by Yannick Meurice
PROGRAM NONPERTURBATIVE AND NUMERICAL APPROACHES TO QUANTUM GRAVITY, STRING THEORY AND HOLOGRAPHY (HYBRID) ORGANIZERS: David Berenstein (University of California, Santa Barbara, USA), Simon Catterall (Syracuse University, USA), Masanori Hanada (University of Surrey, UK), Anosh Joseph (II
From playlist NUMSTRING 2022
Jules Hedges - compositional game theory - part I
Compositional game theory is an approach to game theory that is designed to have better mathematical (loosely “algebraic” and “geometric”) properties, while also being intended as a practical setting for microeconomic modelling. It gives a graphical representation of games in which the flo
From playlist compositional game theory
TensorFlow is a tool for machine learning capable of building deep neural networks with high-level Python code. It provides developer-friendly APIs that help software engineers train, analyze, and deploy ML models. #programming #deeplearning #100secondsofcode đź”— Resources TensorFlow D
From playlist 100 Seconds of Code
Lei Wang: "Tropical Tensor Networks"
Tensor Methods and Emerging Applications to the Physical and Data Sciences 2021 Workshop I: Tensor Methods and their Applications in the Physical and Data Sciences "Tropical Tensor Networks" Lei Wang - Chinese Academy of Sciences Abstract: I will present a unified exact tensor network ap
From playlist Tensor Methods and Emerging Applications to the Physical and Data Sciences 2021