Overview
In this course you will learn how to train, finetune and deploy deep learning models using Amazon SageMaker. You’ll begin by learning what deep learning is, where it is used, and the tools used by deep learning engineers. Next we will learn about artificial neurons and neural networks and how to train them. After that we will learn about advanced neural network architectures like Convolutional Neural Networks and BERT as well as how to finetune them for specific tasks. Finally, you will learn about Amazon SageMaker and you will take everything you learned and do them in SageMaker Studio.
Contents
Syllabus
- Introduction to Deep Learning Topics within Computer Vision and NLP
- In this lesson, we will give a background around Deep Learning for Computer Vision and NLP and preparing you to be successful in the rest of this course.
- Introduction to Deep Learning
- In this lesson, you will learn about neural networks, cost functions, optimization, and how to train a neural network.
- Common Model Architecture Types and Fine-Tuning
- In this lesson you will learn about Model Architectures, Convolutions, and Fine-tuning.
- Deploy Deep Learning Models on SageMaker
- In this lesson, you will learn how to apply all you have learned about deep learning in AWS SageMaker.
- Image Classification using AWS SageMaker
- In this project, you will use AWS SageMaker to finetune a pretrained model and perform a image classification using profiling, debugging, and hyperparameter tuning.
