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  1. Stackups
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  5. NumPy vs Theano

NumPy vs Theano

OverviewComparisonAlternatives

Overview

NumPy
NumPy
Stacks4.3K
Followers799
Votes15
GitHub Stars30.7K
Forks11.7K
Theano
Theano
Stacks32
Followers65
Votes0
GitHub Stars10.0K
Forks2.5K

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Detailed Comparison

NumPy
NumPy
Theano
Theano

Besides its obvious scientific uses, NumPy can also be used as an efficient multi-dimensional container of generic data. Arbitrary data-types can be defined. This allows NumPy to seamlessly and speedily integrate with a wide variety of databases.

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

Powerful n-dimensional arrays; Numerical computing tools; Interoperable; Performant; Easy to use
-
Statistics
GitHub Stars
30.7K
GitHub Stars
10.0K
GitHub Forks
11.7K
GitHub Forks
2.5K
Stacks
4.3K
Stacks
32
Followers
799
Followers
65
Votes
15
Votes
0
Pros & Cons
Pros
  • 10
    Great for data analysis
  • 4
    Faster than list
No community feedback yet
Integrations
Python
Python
Python
Python

What are some alternatives to NumPy, 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.

Pandas

Pandas

Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more.

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.

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