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  1. Stackups
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  5. Numba vs Replicate

Numba vs Replicate

OverviewComparisonAlternatives

Overview

Numba
Numba
Stacks20
Followers44
Votes0
GitHub Stars0
Forks0
Replicate
Replicate
Stacks53
Followers12
Votes0

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CLI (Node.js)
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Detailed Comparison

Numba
Numba
Replicate
Replicate

It translates Python functions to optimized machine code at runtime using the industry-standard LLVM compiler library. It offers a range of options for parallelising Python code for CPUs and GPUs, often with only minor code changes.

It lets you run machine learning models with a few lines of code, without needing to understand how machine learning works.

On-the-fly code generation; Native code generation for the CPU (default) and GPU hardware; Integration with the Python scientific software stack
Thousands of models, ready to use; Automatic API; Automatic scale; Pay by the second
Statistics
GitHub Stars
0
GitHub Stars
-
GitHub Forks
0
GitHub Forks
-
Stacks
20
Stacks
53
Followers
44
Followers
12
Votes
0
Votes
0
Integrations
C++
C++
TensorFlow
TensorFlow
Python
Python
GraphPipe
GraphPipe
Ludwig
Ludwig
Python
Python
Cog
Cog
Next.js
Next.js
JavaScript
JavaScript
Vercel
Vercel
CUDA
CUDA

What are some alternatives to Numba, Replicate?

Git

Git

Git is a free and open source distributed version control system designed to handle everything from small to very large projects with speed and efficiency.

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.

Mercurial

Mercurial

Mercurial is dedicated to speed and efficiency with a sane user interface. It is written in Python. Mercurial's implementation and data structures are designed to be fast. You can generate diffs between revisions, or jump back in time within seconds.

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.

SVN (Subversion)

SVN (Subversion)

Subversion exists to be universally recognized and adopted as an open-source, centralized version control system characterized by its reliability as a safe haven for valuable data; the simplicity of its model and usage; and its ability to support the needs of a wide variety of users and projects, from individuals to large-scale enterprise operations.

Keras

Keras

Deep Learning library for Python. Convnets, recurrent neural networks, and more. Runs on TensorFlow or Theano. https://keras.io/

NanoNets

NanoNets

Build a custom machine learning model without expertise or large amount of data. Just go to nanonets, upload images, wait for few minutes and integrate nanonets API to your application.

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

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