Training Mule Alternatives
TensorFlow is an open source software library for machine learning in various kinds of perceptual and language understanding tasks. It was originally developed by the Google and later released under the Apache 2.0 open source license on Nov 9, 2015.
TensorFlow has no features, suggest some!
- - TensorFlow is the most popular Mac & Linux alternative to Training Mule.
- - TensorFlow is the most popular Open Source & free alternative to Training Mule.
A desktop application with a UX built for through-put, HyperLabel is a complete toolset for quality labeling process management and training data creation.
- - HyperLabel is the most popular Windows alternative to Training Mule.
mlpack is a C++ machine learning library with emphasis on scalability, speed, and ease-of-use. Its aim is to make machine learning possible for novice users by means of a simple, consistent API, while simultaneously exploiting C++ language features.
mlpack has no features, suggest some!
- - mlpack is the most popular Web-based alternative to Training Mule.
Supervisely helps people with and without machine learning expertise to create state-of-the-art computer vision applications. We care about entire workflow from raw data to building and deploying neural networks for your special task without coding.Supervisely has no features, suggest some!
Eclipse Deeplearning4j is the first commercial-grade, open-source, distributed deep-learning library written for Java and Scala. Integrated with Hadoop and Apache Spark, DL4J brings AI to business environments for use on distributed GPUs and CPUs.Deeplearning4j has no features, suggest some!
A downloadable annotation tool for NLP and computer vision tasks such as named entity recognition, text classification, object detection, image segmentation, A/B evaluation and more.
Prodigy ML has no features, suggest some!
- - Prodigy ML is the most popular SaaS alternative to Training Mule.
- - Prodigy ML is the most popular commercial alternative to Training Mule.
MXNet is a deep learning framework designed for both efficiency and flexibility. It allows you to mix symbolic and imperative programming to maximize efficiency and productivity. At its core, MXNet contains a dynamic dependency scheduler that automatically parallelizes both...MXNet has no features, suggest some!