Embark on a transformative journey into the world of machine learning with "Hands-on Machine Learning with AWS and NVIDIA." This comprehensive course is designed for ML practitioners, including data scientists and developers, seeking to enhance their knowledge and skills in building, training, and deploying scalable machine learning models.
Throughout the course, you will delve into the powerful capabilities of Amazon SageMaker and Amazon EC2 instances powered by NVIDIA GPUs. From understanding the basics of Amazon SageMaker and GPUs in the cloud to hands-on training on GPU-powered Amazon SageMaker notebook instances, you will gain practical insights into preparing, building, training, and deploying high-quality ML models with efficiency and ease.
Moreover, the course delves into GPU-accelerated machine learning workflows with RAPIDS and Amazon SageMaker, providing a deep dive into dataset acquisition, data ETL, data visualization, model design and training, model inference and deployment, as well as automated machine learning and hyperparameter optimization.
Furthermore, the modules dedicated to computer vision and natural language processing offer an immersive exploration of common CV tasks, object detection, NLP tasks, BERT architecture, pretraining, fine-tuning, and deploying BERT models on Amazon SageMaker.
By the end of the course, you will be equipped with the knowledge and practical skills to build, train, deploy, and optimize ML workflows with GPU acceleration in Amazon SageMaker, along with a deeper understanding of key Amazon SageMaker services applicable to computer vision and NLP ML tasks.
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This course comprises modules that provide in-depth training on Amazon SageMaker, NVIDIA GPUs, RAPIDS, computer vision, and natural language processing, empowering you to accelerate your machine learning workflows with AWS and NVIDIA.
Delve into the fundamentals of Amazon SageMaker and NVIDIA GPUs, gaining insights into modern-day ML, Amazon SageMaker basics, GPUs in the cloud, Amazon SageMaker Studio, and optimizing GPU performance.
Explore GPU-accelerated machine learning workflows with RAPIDS and Amazon SageMaker, focusing on dataset acquisition, data ETL, data visualization, model design and training, model inference and deployment, and automated machine learning and hyperparameter optimization.
Dive into the realm of computer vision, uncovering common CV tasks, working with image data, object detection, R-CNN, and deploying and accelerating inference with Amazon SageMaker and NVIDIA NGC.
Immerse yourself in the intricacies of natural language processing, understanding BERT, its architecture, pretraining, fine-tuning, and deploying BERT models on Amazon SageMaker, and running Triton Inference Server with Amazon SageMaker.
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