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Avis et commentaires pour d'étudiants pour Hands-on Machine Learning with AWS and NVIDIA par Amazon Web Services

À propos du cours

Machine learning (ML) projects can be complex, tedious, and time consuming. AWS and NVIDIA solve this challenge with fast, effective, and easy-to-use capabilities for your ML project. This course is designed for ML practitioners, including data scientists and developers, who have a working knowledge of machine learning workflows. In this course, you will gain hands-on experience on building, training, and deploying scalable machine learning models with Amazon SageMaker and Amazon EC2 instances powered by NVIDIA GPUs. Amazon SageMaker helps data scientists and developers prepare, build, train, and deploy high-quality ML models quickly by bringing together a broad set of capabilities purpose-built for ML. Amazon EC2 instances powered by NVIDIA GPUs along with NVIDIA software offer high performance GPU-optimized instances in the cloud for efficient model training and cost effective model inference hosting. In this course, you will first get an overview of Amazon SageMaker and NVIDIA GPUs. Then, you will get hands-on, by running a GPU powered Amazon SageMaker notebook instance. You will then learn how to prepare a dataset for model training, build a model, execute model training, and deploy and optimize the ML model. You will also learn, hands-on, how to apply this workflow for computer vision (CV) and natural language processing (NLP) use cases. After completing this course, you will be able to build, train, deploy, and optimize ML workflows with GPU acceleration in Amazon SageMaker and understand the key Amazon SageMaker services applicable to computer vision and NLP ML tasks....
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1 - 2 sur 2 Avis pour Hands-on Machine Learning with AWS and NVIDIA

par Chih-Wei C

30 juin 2022

The course contents in Computer Vision and Natural Language Processing are pretty up-to-date and the depth is okay for an introductory course; however, the learning experience of labs in week 2 and 4 was so painful when there were quite some technical issues to resolve with the course notebooks on AWS. If AWS and NVIDIA try to use this course as a branding opportunity for SageMaker with GPUs, asking potential clients to debug for free is obviously not a good idea.

par Yariv L

10 août 2022

I have finished all labs and quizzes besides the single lab on week 1 as I had an issue with permission on my PC. My overall course completion is 99%, but I can't go back and start the lab on week 1 exercise as it said I've used all my 180 minutes. Can someone please help? I've put lots of time and effort into this course.