TensorFlow vs cnvrg.io Comparison | StackShare

Overview

TensorFlow

Stacks3.8K

Followers3.5K

Votes106

GitHub Stars192.3K

Forks74.9K

cnvrg.io

Stacks11

Followers22

Votes0

TensorFlow vs cnvrg.io: What are the differences?

Developers describe TensorFlow as "Open Source Software Library for Machine Intelligence". 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. On the other hand, cnvrg.io is detailed as "An end-to-end machine learning platform to build and deploy AI models at scale". It is an AI OS, transforming the way enterprises manage, scale and accelerate AI and data science development from research to production. The code-first platform is built by data scientists, for data scientists and offers unrivaled flexibility to run on-premise or cloud.

TensorFlow and cnvrg.io can be primarily classified as "Machine Learning" tools.

TensorFlow is an open source tool with 146K GitHub stars and 82K GitHub forks. Here's a link to TensorFlow's open source repository on GitHub.

Advice on TensorFlow, cnvrg.io

Adithya

Student at PES UNIVERSITY

May 11, 2020

Needs advice

I have just started learning some basic machine learning concepts. So which of the following frameworks is better to use: Keras / TensorFlow/PyTorch. I have prior knowledge in python(and even pandas), java, js and C. It would be nice if something could point out the advantages of one over the other especially in terms of resources, documentation and flexibility. Also, could someone tell me where to find the right resources or tutorials for the above frameworks? Thanks in advance, hope you are doing well!!

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Detailed Comparison

TensorFlow	cnvrg.io
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.	It is an AI OS, transforming the way enterprises manage, scale and accelerate AI and data science development from research to production. The code-first platform is built by data scientists, for data scientists and offers unrivaled flexibility to run on-premise or cloud.
-	Machine Learning Pipelines; AI Library; Open Compute; Dataset Management; Machine Learning Tracking; Machine Learning Model Deployment; Scalable Streaming Endpoints
Statistics
GitHub Stars 192.3K	GitHub Stars -
GitHub Forks 74.9K	GitHub Forks -
Stacks 3.8K	Stacks 11
Followers 3.5K	Followers 22
Votes 106	Votes 0
Pros & Cons
Pros 32 High Performance 19 Connect Research and Production 16 Deep Flexibility 12 Auto-Differentiation 11 True Portability Cons 9 Hard 6 Hard to debug 2 Documentation not very helpful	No community feedback yet
Integrations
JavaScript	Apache Spark PostgreSQL Kubernetes Google BigQuery Python Amazon S3 MySQL Keras Kafka Red Hat OpenShift

What are some alternatives to TensorFlow, cnvrg.io?

Ubuntu

Ubuntu is an ancient African word meaning ‘humanity to others’. It also means ‘I am what I am because of who we all are’. The Ubuntu operating system brings the spirit of Ubuntu to the world of computers.

Debian

Debian systems currently use the Linux kernel or the FreeBSD kernel. Linux is a piece of software started by Linus Torvalds and supported by thousands of programmers worldwide. FreeBSD is an operating system including a kernel and other software.

Arch Linux

A lightweight and flexible Linux distribution that tries to Keep It Simple.

Fedora

Fedora is a Linux-based operating system that provides users with access to the latest free and open source software, in a stable, secure and easy to manage form. Fedora is the largest of many free software creations of the Fedora Project. Because of its predominance, the word "Fedora" is often used interchangeably to mean both the Fedora Project and the Fedora operating system.

Linux Mint

The purpose of Linux Mint is to produce a modern, elegant and comfortable operating system which is both powerful and easy to use.

CentOS

The CentOS Project is a community-driven free software effort focused on delivering a robust open source ecosystem. For users, we offer a consistent manageable platform that suits a wide variety of deployments. For open source communities, we offer a solid, predictable base to build upon, along with extensive resources to build, test, release, and maintain their code.

Linux

A clone of the operating system Unix, written from scratch by Linus Torvalds with assistance from a loosely-knit team of hackers across the Net. It aims towards POSIX and Single UNIX Specification compliance.

scikit-learn

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

CoreOS

It is designed for security, consistency, and reliability. Instead of installing packages via yum or apt, it uses Linux containers to manage your services at a higher level of abstraction. A single service's code and all dependencies are packaged within a container that can be run on one or many machines.

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.