Caffe vs Numba

Overview

Caffe

Stacks66

Followers73

Votes0

GitHub Stars34.7K

Forks18.6K

Numba

Stacks20

Followers44

Votes0

GitHub Stars0

Forks0

Numba vs Caffe: What are the differences?

What is Numba? An open source JIT compiler that translates a subset of Python and NumPy code into fast machine code. 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.

What is Caffe? A deep learning framework. It is a deep learning framework made with expression, speed, and modularity in mind.

Numba and Caffe can be primarily classified as "Machine Learning" tools.

Some of the features offered by Numba are:

On-the-fly code generation
Native code generation for the CPU (default) and GPU hardware
Integration with the Python scientific software stack

On the other hand, Caffe provides the following key features:

Extensible code
Speed
Community

Caffe is an open source tool with 29.2K GitHub stars and 17.6K GitHub forks. Here's a link to Caffe's open source repository on GitHub.

🔥 Trending in Development & Training Tools on StackShare

CUDA AI Development Training Tools

It provides everything you need to develop GPU-accelerated applications

Try it View Docs Alternatives

Try

0

215

Detailed Comparison

Caffe	Numba
It is a deep learning framework made with expression, speed, and modularity in mind.	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.
Extensible code; Speed; Community;	On-the-fly code generation; Native code generation for the CPU (default) and GPU hardware; Integration with the Python scientific software stack
Statistics
GitHub Stars 34.7K	GitHub Stars 0
GitHub Forks 18.6K	GitHub Forks 0
Stacks 66	Stacks 20
Followers 73	Followers 44
Votes 0	Votes 0
Integrations
TensorFlow Keras Amazon SageMaker Pythia	C++ TensorFlow Python GraphPipe Ludwig

What are some alternatives to Caffe, Numba?

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 is a Python module for machine learning built on top of SciPy and distributed under the 3-Clause BSD license.

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

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

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

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

An enterprise-grade open source platform for building, training, and monitoring large scale deep learning applications.

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 is an open source platform for managing the end-to-end machine learning lifecycle.

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.