Software Alternatives & Reviews

Theano VS Infer.NET

Compare Theano VS Infer.NET and see what are their differences

Theano logo Theano

Theano is a Python library that allows you to define, optimize, and evaluate mathematical expressions involving multi-dimensional arrays efficiently. Theano features: tight integration with NumPy – Use numpy.

Infer.NET logo Infer.NET

Infer.NET is a framework for running Bayesian inference in graphical models. It can also be used for probabilistic programming.
  • Theano Landing page
    Landing page //
    2023-09-19
  • Infer.NET Landing page
    Landing page //
    2023-01-24

Theano videos

Theano 5 function 用法 (神经网络 教学教程tutorial)

Infer.NET videos

Yordan Zaykov: "Probabilistic programming in production with Infer.NET"

Category Popularity

0-100% (relative to Theano and Infer.NET)
Data Science And Machine Learning
AI
100 100%
0% 0
Data Science Tools
0 0%
100% 100
Business & Commerce
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0% 0

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What are some alternatives?

When comparing Theano and Infer.NET, you can also consider the following products

TensorFlow - TensorFlow is an open-source machine learning framework designed and published by Google. It tracks data flow graphs over time. Nodes in the data flow graphs represent machine learning algorithms. Read more about TensorFlow.

Open Text Magellan - OpenText Magellan - the power of AI in a pre-wired platform that augments decision making and accelerates your business. Learn more.

Keras - Keras is a minimalist, modular neural networks library, written in Python and capable of running on top of either TensorFlow or Theano.

Kira - Gain visibility into contract repositories, accelerate and improve the accuracy of contract review, mitigate risk of errors, win new business, and improve the value you provide to your clients.

Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.

Infrrd.ai - Cheaper, Lighter, Faster Enterprise AI platform that makes sense of your image, text and behavioral data to automate decision for cost/man power reduction or revenue increase.