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 DeepRacer vs Streamlit

AWS DeepRacer vs Streamlit

OverviewComparisonAlternatives

Overview

Streamlit
Streamlit
Stacks403
Followers407
Votes12
GitHub Stars42.1K
Forks3.9K
AWS DeepRacer
AWS DeepRacer
Stacks3
Followers6
Votes0

Streamlit vs AWS DeepRacer: What are the differences?

Streamlit: A Python app framework built specifically for Machine Learning and Data Science teams. 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; AWS DeepRacer: The fastest way to get rolling with machine learning. Developers of all skill levels can get hands on with machine learning through a cloud based 3D racing simulator, fully autonomous 1/18th scale race car driven by reinforcement learning, and global racing league.

Streamlit and AWS DeepRacer can be categorized as "Machine Learning" tools.

Some of the features offered by Streamlit are:

  • Free and open source
  • Build apps in a dozen lines of Python with a simple API
  • No callbacks

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

  • A fun way to learn machine learning
  • Master the basics with time-trial racing
  • Expand your skills with head-to-head racing

Streamlit is an open source tool with 10.2K GitHub stars and 874 GitHub forks. Here's a link to Streamlit'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

Streamlit
Streamlit
AWS DeepRacer
AWS DeepRacer

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.

Developers of all skill levels can get hands on with machine learning through a cloud based 3D racing simulator, fully autonomous 1/18th scale race car driven by reinforcement learning, and global racing league.

Free and open source; Build apps in a dozen lines of Python with a simple API; No callbacks; No hidden state; Works with TensorFlow, Keras, PyTorch, Pandas, Numpy, Matplotlib, Seaborn, Altair, Plotly, Bokeh, Vega-Lite, and more
A fun way to learn machine learning; Master the basics with time-trial racing; Expand your skills with head-to-head racing
Statistics
GitHub Stars
42.1K
GitHub Stars
-
GitHub Forks
3.9K
GitHub Forks
-
Stacks
403
Stacks
3
Followers
407
Followers
6
Votes
12
Votes
0
Pros & Cons
Pros
  • 11
    Fast development
  • 1
    Fast development and apprenticeship
No community feedback yet
Integrations
Python
Python
Plotly.js
Plotly.js
PyTorch
PyTorch
Pandas
Pandas
Bokeh
Bokeh
Keras
Keras
NumPy
NumPy
Matplotlib
Matplotlib
TensorFlow
TensorFlow
Altair GraphQL
Altair GraphQL
No integrations available

What are some alternatives to Streamlit, AWS DeepRacer?

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.

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.

PredictionIO

PredictionIO

PredictionIO is an open source machine learning server for software developers to create predictive features, such as personalization, recommendation and content discovery.

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