AWS DeepLens | Getting Started Flashcards
What MXNet network architecture layers does AWS DeepLens support?
Getting Started
AWS DeepLens | Machine Learning
AWS DeepLens offers support for 20 different network architecture layers. The layers supported are:
Activation
BatchNorm
Concat
Convolution
elemwise_add
Pooling
Flatten
FullyConnected
InputLayer
UpSampling
Reshape
ScaleShift
SoftmaxActivation
SoftmaxOutput
transpose
_contrib_MultiBoxPrior
_contrib_MultiBoxDetection
_Plus
Deconvolution
_mul
What comes in the box and how do I get started?
Getting Started
AWS DeepLens | Machine Learning
Inside the box, developers will find a Getting Started guide, the AWS DeepLens device, a power supply and a 32GB microSD card. Setup and configuration of the DeepLens device can be done in minutes using the AWS DeepLens console, and by configuring the device through a browser on your laptop or PC.
Can I train my models on the device?
Getting Started
AWS DeepLens | Machine Learning
No, AWS DeepLens is capable of running inference or predictions using trained models. You can train your models in Amazon SageMaker, a machine learning platform to train and host your models. AWS DeepLens offers a simple 1-click deploy feature to publish trained models from Amazon SageMaker.
What AWS services are integrated with AWS DeepLens?
Getting Started
AWS DeepLens | Machine Learning
DeepLens is pre-configured for integration with AWS Greengrass, Amazon SageMaker and Amazon Kinesis Video Streams. You can integrate with many other AWS services, such as Amazon S3, Amazon Lambda, Amazon Dynamo, Amazon Rekognition using AWS DeepLens.
Can I SSH into AWS DeepLens?
Getting Started
AWS DeepLens | Machine Learning
Yes, we have designed AWS DeepLens to be easy to use, yet accessible for advanced developers. You can SSH into the device using the command: ssh aws_cam@
What programming languages are supported by AWS DeepLens?
Getting Started
AWS DeepLens | Machine Learning
You can define and run models on the camera data stream locally in Python 2.7.
Do I need to be connected to internet to run the models?
Getting Started
AWS DeepLens | Machine Learning
No. You can run the models that you have deployed to AWS DeepLens without being connected to the internet. However, you need internet to deploy the model from the cloud to the device initially. After transferring your model, AWS DeepLens can perform inference on the device locally without requiring cloud connectivity. However, if you have components in your project that require interaction with cloud, you will need to have internet for those components.
