Masterclass of AWS-Deep Learning AMI

Description

Masterclass of AWS-Deep Learning AMI

Learning about deep learning: The DLAMI is a great choice for learning or teaching machine learning and deep learning frameworks. It takes the headache away from troubleshooting the installations of each framework and getting them to play along on the same computer. The DLAMI comes with a Jupyter notebook and makes it easy to run the tutorials provided by the frameworks for people new to machine learning and deep learning. App development: If you're an app developer and are interested in using deep learning to make your apps utilize the latest advances in AI, the DLAMI is the perfect test bed for you. Each framework comes with tutorials on how to get started with deep learning, and many of them have model zoos that make it easy to try out deep learning without having to create the neural networks yourself or to do any of the model training. Some examples show you how to build an image detection application in just a few minutes, or how to build a speech recognition app for your own chatbot. Machine learning and data analytics: If you're a data scientist or interested in processing your data with deep learning, you'll find that many of the frameworks have support for R and Spark. You will find tutorials on how to do simple regressions, all the way up to building scalable data processing systems for personalization and predictions systems. Research: If you're a researcher and want to try out a new framework, test out a new model, or train new models, the DLAMI and AWS capabilities for scale can alleviate the pain of tedious installations and management of multiple training nodes. You can use EMR and AWS CloudFormation templates to easily launch a full cluster of instances that are ready to go for scalable training.

Preinstalled Frameworks There are currently two primary flavors of the DLAMI with other variations related to the operating system (OS) and software versions: • Deep Learning AMI with Conda (p. 4) - frameworks installed separately using conda packages and separate Python environments • Deep Learning Base AMI (p. 6) - no frameworks installed; only NVIDIA CUDA and other dependencies The Deep Learning AMI with Conda uses Anaconda environments to isolate each framework, so you can switch between them at will and not worry about their dependencies conflicting. For more information on selecting the best DLAMI for you, take a look at Getting Started (p. 4). This is the full list of supported frameworks by Deep Learning AMI with Conda: • Apache MXNet • Chainer • Keras • PyTorch • TensorFlow • TensorFlow 2

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