filmov
tv
Deep Learning on AWS made simple - AWS Online Tech Talks
Показать описание
TensorFlow and PyTorch are the two most popular deep learning (DL) frameworks today for developing and running neural networks. These frameworks are easy to get started, but developers and data scientists find it challenging to setup and ensure that DL frameworks include the latest performance optimizations, and scale them to a large number of CPUs and GPUs to deliver faster results. In this session, you’ll learn how to leverage AWS optimized DL framework containers to train quickly and save cost with Amazon SageMaker, and skip the complicated process of managing and optimizing your framework environments.
Learning Objectives:
* Objective 1: Understand and dive into the most popular deep learning frameworks such as TensorFlow and PyTorch
* Objective 2: Learn how to get started with deep learning frameworks on Amazon SageMaker
* Objective 3: Evaluate how to train quickly and save cost with Amazon SageMaker by using AWS optimized DL framework containers
Follow Amazon Web Services:
☁️ AWS Online Tech Talks cover a wide range of topics and expertise levels through technical deep dives, demos, customer examples, and live Q&A with AWS experts. Builders can choose from bite-sized 15-minute sessions, insightful fireside chats, immersive virtual workshops, interactive office hours, or watch on-demand tech talks at your own pace. Join us to fuel your learning journey with AWS.
#AWS
Learning Objectives:
* Objective 1: Understand and dive into the most popular deep learning frameworks such as TensorFlow and PyTorch
* Objective 2: Learn how to get started with deep learning frameworks on Amazon SageMaker
* Objective 3: Evaluate how to train quickly and save cost with Amazon SageMaker by using AWS optimized DL framework containers
Follow Amazon Web Services:
☁️ AWS Online Tech Talks cover a wide range of topics and expertise levels through technical deep dives, demos, customer examples, and live Q&A with AWS experts. Builders can choose from bite-sized 15-minute sessions, insightful fireside chats, immersive virtual workshops, interactive office hours, or watch on-demand tech talks at your own pace. Join us to fuel your learning journey with AWS.
#AWS
0:46:18
Deep Learning on AWS made simple - AWS Online Tech Talks
0:32:05
AWS AMER Summit 2020 | Deep learning with TensorFlow, PyTorch, and MXNet on AWS
1:27:55
Artificial Intelligence | Deep Learning - Deploying Deep Learning Models on AWS
0:31:41
Deep Learning on AWS with MXNet
0:04:47
Introduction to Amazon SageMaker
0:54:09
AWS re:Invent 2022 - Deep learning on AWS with NVIDIA: From training to deployment (PRT219)
0:04:05
How to Create and Deploy a Deep Learning Project With AWS DeepLens
0:40:25
End To End Machine Learning Project Implementation Using AWS Sagemaker
0:19:10
Fundamentals of Generative AI - Lesson 2: Foundation Models and LLMs
0:55:16
Webinar: Interactive Deep Learning on Seismic Made Possible with Bluware & AWS
0:31:04
Leverage the Power of AWS Deep Learning Containers with Kubernetes for Training Deep Learning Models
0:19:57
AWS NY Summit - Machine Learning Made Easy with Amazon SageMaker
0:02:33
Using Machine Learning on AWS - Raising the Barr
0:28:59
AWS Quick Start - Build Intelligent Applications with Machine Learning on AWS
0:49:35
AWS re:Invent 2021 - How to select Amazon EC2 GPU instances for deep learning (sponsored by NVIDIA)
0:43:24
AWS Transformation Day - London: Introduction to Amazon AI and Deep Learning
0:59:18
AWS re:Invent 2021 - Accelerate innovation with machine learning
0:34:46
AWS ML Summit 2021 | Accelerate deep learning in the cloud with custom ML environments
0:11:46
Top 50+ AWS Services Explained in 10 Minutes
0:02:35
Machine Learning Explained in 100 Seconds
0:26:07
Deep learning on the cloud (AWS) | My setup
0:24:38
Demystifying Machine Learning on AWS (Level 200)
0:07:02
AWS Machine Learning in Motion: the costs of running machine learning models on AWS
0:05:39
DEEP LEARNING ON AWS | BUILD, TRAIN, DEPLOY ML MODEL AT SCALE USING PYTORCH AND Amazon SageMaker.
Комментарии