OpenVINO vs Continuous Machine Learning: What are the differences?

What is 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.

What is Continuous Machine Learning? CI/CD for Machine Learning Projects. Continuous Machine Learning (CML) is an open-source library for implementing continuous integration & delivery (CI/CD) in machine learning projects. Use it to automate parts of your development workflow, including model training and evaluation, comparing ML experiments across your project history, and monitoring changing datasets.

OpenVINO and Continuous Machine Learning belong to "Machine Learning Tools" category of the tech stack.

Some of the features offered by OpenVINO are:

• 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

On the other hand, Continuous Machine Learning provides the following key features:

• GitFlow for data science
• Auto reports for ML experiments
• No additional services

Continuous Machine Learning is an open source tool with 1.72K GitHub stars and 87 GitHub forks. Here's a link to Continuous Machine Learning's open source repository on GitHub.