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  1. Stackups
  2. AI
  3. Development & Training Tools
  4. Machine Learning Tools
  5. Caffe2 vs Ludwig

Caffe2 vs Ludwig

OverviewComparisonAlternatives

Overview

Caffe2
Caffe2
Stacks49
Followers83
Votes2
Ludwig
Ludwig
Stacks35
Followers101
Votes0

Caffe2 vs Ludwig: What are the differences?

Caffe2: 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; Ludwig: A code-free deep learning toolbox, by Uber. Ludwig is a toolbox built on top of TensorFlow that allows to train and test deep learning models without the need to write code. All you need to provide is a CSV file containing your data, a list of columns to use as inputs, and a list of columns to use as outputs, Ludwig will do the rest.

Caffe2 and Ludwig can be primarily classified as "Machine Learning" tools.

Caffe2 and Ludwig are both open source tools. Caffe2 with 8.46K GitHub stars and 2.13K forks on GitHub appears to be more popular than Ludwig with 4.95K GitHub stars and 526 GitHub forks.

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Detailed Comparison

Caffe2
Caffe2
Ludwig
Ludwig

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.

Ludwig is a toolbox built on top of TensorFlow that allows to train and test deep learning models without the need to write code. All you need to provide is a CSV file containing your data, a list of columns to use as inputs, and a list of columns to use as outputs, Ludwig will do the rest.

Statistics
Stacks
49
Stacks
35
Followers
83
Followers
101
Votes
2
Votes
0
Pros & Cons
Pros
  • 1
    Open Source
  • 1
    Mobile deployment
No community feedback yet
Integrations
No integrations available
Pandas
Pandas
TensorFlow
TensorFlow
Python
Python
scikit-learn
scikit-learn
scikit-image
scikit-image
NumPy
NumPy

What are some alternatives to Caffe2, Ludwig?

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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