StackShareStackShare
Follow on
StackShare

Discover and share technology stacks from companies around the world.

Follow on

© 2025 StackShare. All rights reserved.

Product

  • Stacks
  • Tools
  • Feed

Company

  • About
  • Contact

Legal

  • Privacy Policy
  • Terms of Service
  1. Stackups
  2. AI
  3. Development & Training Tools
  4. Machine Learning Tools
  5. AWS DeepLens vs ScalaNLP

AWS DeepLens vs ScalaNLP

OverviewComparisonAlternatives

Overview

ScalaNLP
ScalaNLP
Stacks2
Followers12
Votes0
GitHub Stars3.5K
Forks694
AWS DeepLens
AWS DeepLens
Stacks1
Followers11
Votes0

ScalaNLP vs AWS DeepLens: What are the differences?

Developers describe ScalaNLP as "A suite of machine learning and numerical computing libraries". ScalaNLP is a suite of machine learning and numerical computing libraries. 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.

ScalaNLP and AWS DeepLens belong to "Machine Learning Tools" category of the tech stack.

Some of the features offered by ScalaNLP are:

  • ScalaNLP is the umbrella project for several libraries:
  • Breeze is a set of libraries for machine learning and numerical computing
  • Epic is a high-performance statistical parser and structured prediction library

On the other hand, AWS DeepLens provides the following key features:

  • A new way to learn machine learning
  • Custom built for deep learning
  • Build custom models with Amazon SageMaker

ScalaNLP is an open source tool with 3.15K GitHub stars and 687 GitHub forks. Here's a link to ScalaNLP's open source repository on GitHub.

Share your Stack

Help developers discover the tools you use. Get visibility for your team's tech choices and contribute to the community's knowledge.

View Docs
CLI (Node.js)
or
Manual

Detailed Comparison

ScalaNLP
ScalaNLP
AWS DeepLens
AWS DeepLens

ScalaNLP is a suite of machine learning and numerical computing libraries.

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.

ScalaNLP is the umbrella project for several libraries:; Breeze is a set of libraries for machine learning and numerical computing; Epic is a high-performance statistical parser and structured prediction library
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
GitHub Stars
3.5K
GitHub Stars
-
GitHub Forks
694
GitHub Forks
-
Stacks
2
Stacks
1
Followers
12
Followers
11
Votes
0
Votes
0
Integrations
Scala
Scala
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 ScalaNLP, 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.

Related Comparisons

Postman
Swagger UI

Postman vs Swagger UI

Mapbox
Google Maps

Google Maps vs Mapbox

Mapbox
Leaflet

Leaflet vs Mapbox vs OpenLayers

Twilio SendGrid
Mailgun

Mailgun vs Mandrill vs SendGrid

Runscope
Postman

Paw vs Postman vs Runscope