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  1. Stackups
  2. AI
  3. Development & Training Tools
  4. Machine Learning Tools
  5. Theano vs Torch

Theano vs Torch

OverviewComparisonAlternatives

Overview

Torch
Torch
Stacks355
Followers61
Votes0
GitHub Stars9.1K
Forks2.4K
Theano
Theano
Stacks32
Followers65
Votes0
GitHub Stars10.0K
Forks2.5K

Theano vs Torch: What are the differences?

What is Theano? Define, optimize, and evaluate mathematical expressions involving multi-dimensional arrays efficiently. Theano is a Python library that lets you to define, optimize, and evaluate mathematical expressions, especially ones with multi-dimensional arrays (numpy.ndarray). Using Theano it is possible to attain speeds rivaling hand-crafted C impleme.

What is Torch? An open-source machine learning library and a script language based on the Lua programming language. It is easy to use and efficient, thanks to an easy and fast scripting language, LuaJIT, and an underlying C/CUDA implementation.

Theano and Torch belong to "Machine Learning Tools" category of the tech stack.

Theano is an open source tool with 8.9K GitHub stars and 2.5K GitHub forks. Here's a link to Theano's open source repository on GitHub.

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Detailed Comparison

Torch
Torch
Theano
Theano

It is easy to use and efficient, thanks to an easy and fast scripting language, LuaJIT, and an underlying C/CUDA implementation.

Theano is a Python library that lets you to define, optimize, and evaluate mathematical expressions, especially ones with multi-dimensional arrays (numpy.ndarray).

A powerful N-dimensional array; Lots of routines for indexing, slicing, transposing; Amazing interface to C, via LuaJIT; Linear algebra routines; Neural network, and energy-based models; Numeric optimization routines; Fast and efficient GPU support; Embeddable, with ports to iOS and Android backends
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Statistics
GitHub Stars
9.1K
GitHub Stars
10.0K
GitHub Forks
2.4K
GitHub Forks
2.5K
Stacks
355
Stacks
32
Followers
61
Followers
65
Votes
0
Votes
0
Integrations
Python
Python
SQLFlow
SQLFlow
GraphPipe
GraphPipe
Flair
Flair
Pythia
Pythia
Databricks
Databricks
Comet.ml
Comet.ml
NumPy
NumPy
Python
Python

What are some alternatives to Torch, Theano?

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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