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  1. Stackups
  2. AI
  3. Development & Training Tools
  4. Machine Learning Tools
  5. ML Visualization IDE vs OpenVINO

ML Visualization IDE vs OpenVINO

OverviewComparisonAlternatives

Overview

OpenVINO
OpenVINO
Stacks15
Followers32
Votes0
ML Visualization IDE
ML Visualization IDE
Stacks2
Followers8
Votes0

ML Visualization IDE vs OpenVINO: What are the differences?

ML Visualization IDE: Make powerful, interactive machine learning visualizations. Debug your machine learning models in realtime with powerful, interactive visualizations Quickly log charts from your Python script, visualize your model development in live dashboards, and share interactive plots with your team, in just 2 minutes.; OpenVINO: A free toolkit facilitating the optimization of a Deep Learning model. It is a comprehensive toolkit for quickly developing applications and solutions that emulate human vision. Based on Convolutional Neural Networks (CNNs), the toolkit extends CV workloads across Intel® hardware, maximizing performance.

ML Visualization IDE and OpenVINO can be primarily classified as "Machine Learning" tools.

Some of the features offered by ML Visualization IDE are:

  • Powerful, interactive visualizations
  • Quickly log charts
  • Visualize your model development in live dashboards

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

  • Optimize and deploy deep learning solutions across multiple Intel® platforms
  • Accelerate and optimize low-level, image-processing capabilities using the OpenCV library
  • Maximize the performance of your application for any type of processor

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Detailed Comparison

OpenVINO
OpenVINO
ML Visualization IDE
ML Visualization IDE

It is a comprehensive toolkit for quickly developing applications and solutions that emulate human vision. Based on Convolutional Neural Networks (CNNs), the toolkit extends CV workloads across Intel® hardware, maximizing performance.

Debug your machine learning models in realtime with powerful, interactive visualizations. Quickly log charts from your Python script, visualize your model development in live dashboards, and share interactive plots with your team, in just 2 minutes.

Optimize and deploy deep learning solutions across multiple Intel® platforms; Accelerate and optimize low-level, image-processing capabilities using the OpenCV library; Maximize the performance of your application for any type of processor
Powerful, interactive visualizations; Quickly log charts; Visualize your model development in live dashboards; Share interactive plots with your team
Statistics
Stacks
15
Stacks
2
Followers
32
Followers
8
Votes
0
Votes
0

What are some alternatives to OpenVINO, ML Visualization IDE?

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.

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.

Keras

Keras

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

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

Polyaxon

Polyaxon

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

Streamlit

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

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

H2O

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.

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