YoVDO

Introduction to Tensors - PyTorch with GPU Series Part 2

Offered By: Samuel Chan via YouTube

Tags

PyTorch Courses Deep Learning Courses CUDA Courses Tensors Courses GPU Acceleration Courses

Course Description

Overview

Explore the fundamentals of tensors in this 29-minute video tutorial, part of the PyTorch with GPU series. Discover four different methods for initializing tensors in PyTorch, learn how to move tensors to CUDA/GPU, and master various tensor operations including arithmetic, slicing, and indexing. Gain insights into the shared memory locations between CPU tensors and NumPy arrays, and get introduced to PyTorch's Profiler context manager for performance optimization. Perfect for those looking to enhance their understanding of tensor manipulation and GPU acceleration in PyTorch.

Syllabus

Intro
Initializing a tensor 4 different ways in PyTorch!
Moving pytorch tensor to cuda / gpu
Operations on Tensor arithmetic, slicing, indexing
Tensors on CPU and numpy arrays can share their memory locations!
PyTorch's Profiler context manager


Taught by

Samuel Chan

Related Courses

Fundamentals of Accelerated Computing with CUDA C/C++
Nvidia via Independent
Using GPUs to Scale and Speed-up Deep Learning
IBM via edX
Deep Learning
IBM via edX
Deep Learning with IBM
IBM via edX
Accelerating Deep Learning with GPUs
IBM via Cognitive Class