horovod VS robot

Compare horovod vs robot and see what are their differences.

horovod

Distributed training framework for TensorFlow, Keras, PyTorch, and Apache MXNet. [Moved to: https://github.com/horovod/horovod] (by uber)
Tensorflow Uber Machine Learning Machinelearning Mpi baidu Deep Learning Deeplearning Keras Pytorch Mxnet Spark Ray

DISCONTINUED

Suggest alternative
Edit details

robot

Functions and classes for gradient-based robot motion planning, written in Ivy. [Moved to: https://github.com/unifyai/robot] (by ivy-dl)
Python Machine Learning Deep Learning Mxnet Tensorflow Numpy Pytorch Robot path-planning motion-planning trajectory-optimization Ivy

DISCONTINUED

Suggest alternative
Edit details
InfluxDB
Our great sponsors
  • InfluxDB - Power Real-Time Data Analytics at Scale
  • WorkOS - The modern identity platform for B2B SaaS
  • SaaSHub - Software Alternatives and Reviews
Our great sponsors
horovod robot
1 1
11,889 14
- -
9.4 8.0
over 2 years ago over 2 years ago
Python Python
GNU General Public License v3.0 or later Apache License 2.0
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

horovod

Posts with mentions or reviews of horovod. We have used some of these posts to build our list of alternatives and similar projects.

robot

Posts with mentions or reviews of robot. We have used some of these posts to build our list of alternatives and similar projects.
  • [R] Unifying all Machine Learning Frameworks - Link to a free online lecture by the author in comments
    1 project | /r/MachineLearning | 23 Jan 2022
    In this talk, we will show how unifying all Machine Learning (ML) frameworks could save everybody a HUGE amount of time and energy. Through interactive coding sessions and live demos, we will explain how Ivy (checkout lets-unify.ai) is solving this unification problem. We will focus on demos using Ivy’s 3D vision and robotics libraries, solving 3D robotic navigation and perception tasks in a 3D simulator, all in real-time. Checkout https://github.com/ivy-dl/robot for examples! Finally, we will explore how you can join and contribute to the growing Ivy community, and help us in our mission to truly unify all ML frameworks once and for all.

What are some alternatives?

When comparing horovod and robot you can also consider the following projects:

tf-encrypted - A Framework for Encrypted Machine Learning in TensorFlow

robot - Functions and classes for gradient-based robot motion planning, written in Ivy.

rxray - Ray distributed computing integration for RxPY

ivy - The Unified Machine Learning Framework [Moved to: https://github.com/unifyai/ivy]

seq2seq - A general-purpose encoder-decoder framework for Tensorflow

dymos - Open Source Optimization of Dynamic Multidisciplinary Systems

polyaxon - MLOps Tools For Managing & Orchestrating The Machine Learning LifeCycle

ray_snowflake - Ray Data Connector for Snowflake

client - DagsHub client libraries

deep-significance - Enabling easy statistical significance testing for deep neural networks.

dns-tunnelling-with-dl - Deep Learning Based DNS Tunneling Detection and Blocking System

livelossplot - Live training loss plot in Jupyter Notebook for Keras, PyTorch and others

horovod vs tf-encrypted robot vs robot horovod vs rxray robot vs ivy horovod vs seq2seq robot vs dymos horovod vs polyaxon horovod vs ray_snowflake horovod vs client horovod vs deep-significance horovod vs dns-tunnelling-with-dl horovod vs livelossplot