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  1. Stackups
  2. AI
  3. Development & Training Tools
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  5. AWS DeepLens vs Caffe2

AWS DeepLens vs Caffe2

OverviewComparisonAlternatives

Overview

Caffe2
Caffe2
Stacks49
Followers83
Votes2
AWS DeepLens
AWS DeepLens
Stacks1
Followers11
Votes0

Caffe2 vs AWS DeepLens: What are the differences?

Developers describe Caffe2 as "Open Source Cross-Platform Machine Learning Tools (by Facebook)". Caffe2 is deployed at Facebook to help developers and researchers train large machine learning models and deliver AI-powered experiences in our mobile apps. Now, developers will have access to many of the same tools, allowing them to run large-scale distributed training scenarios and build machine learning applications for mobile. On the other hand, AWS DeepLens is detailed as "Deep learning enabled video camera for developers". It helps put machine learning in the hands of developers, literally, with a fully programmable video camera, tutorials, code, and pre-trained models designed to expand deep learning skills.

Caffe2 and AWS DeepLens can be categorized as "Machine Learning" tools.

Caffe2 is an open source tool with 8.46K GitHub stars and 2.08K GitHub forks. Here's a link to Caffe2's open source repository on GitHub.

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Detailed Comparison

Caffe2
Caffe2
AWS DeepLens
AWS DeepLens

Caffe2 is deployed at Facebook to help developers and researchers train large machine learning models and deliver AI-powered experiences in our mobile apps. Now, developers will have access to many of the same tools, allowing them to run large-scale distributed training scenarios and build machine learning applications for mobile.

It helps put machine learning in the hands of developers, literally, with a fully programmable video camera, tutorials, code, and pre-trained models designed to expand deep learning skills.

-
A new way to learn machine learning; Custom built for deep learning; Build custom models with Amazon SageMaker; Broad framework support; Integrated with AWS
Statistics
Stacks
49
Stacks
1
Followers
83
Followers
11
Votes
2
Votes
0
Pros & Cons
Pros
  • 1
    Open Source
  • 1
    Mobile deployment
No community feedback yet
Integrations
No integrations available
Amazon S3
Amazon S3
Amazon DynamoDB
Amazon DynamoDB
TensorFlow
TensorFlow
Amazon SQS
Amazon SQS
Amazon SNS
Amazon SNS
Amazon SageMaker
Amazon SageMaker
Caffe
Caffe
Amazon IoT
Amazon IoT

What are some alternatives to Caffe2, AWS DeepLens?

TensorFlow

TensorFlow

TensorFlow is an open source software library for numerical computation using data flow graphs. Nodes in the graph represent mathematical operations, while the graph edges represent the multidimensional data arrays (tensors) communicated between them. The flexible architecture allows you to deploy computation to one or more CPUs or GPUs in a desktop, server, or mobile device with a single API.

scikit-learn

scikit-learn

scikit-learn is a Python module for machine learning built on top of SciPy and distributed under the 3-Clause BSD license.

PyTorch

PyTorch

PyTorch is not a Python binding into a monolothic C++ framework. It is built to be deeply integrated into Python. You can use it naturally like you would use numpy / scipy / scikit-learn etc.

Keras

Keras

Deep Learning library for Python. Convnets, recurrent neural networks, and more. Runs on TensorFlow or Theano. https://keras.io/

Kubeflow

Kubeflow

The Kubeflow project is dedicated to making Machine Learning on Kubernetes easy, portable and scalable by providing a straightforward way for spinning up best of breed OSS solutions.

TensorFlow.js

TensorFlow.js

Use flexible and intuitive APIs to build and train models from scratch using the low-level JavaScript linear algebra library or the high-level layers API

Polyaxon

Polyaxon

An enterprise-grade open source platform for building, training, and monitoring large scale deep learning applications.

Streamlit

Streamlit

It is the app framework specifically for Machine Learning and Data Science teams. You can rapidly build the tools you need. Build apps in a dozen lines of Python with a simple API.

MLflow

MLflow

MLflow is an open source platform for managing the end-to-end machine learning lifecycle.

H2O

H2O

H2O.ai is the maker behind H2O, the leading open source machine learning platform for smarter applications and data products. H2O operationalizes data science by developing and deploying algorithms and models for R, Python and the Sparkling Water API for Spark.

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