| Description | MLflow is a futuristic machine learning platform that helps developers manage the entire machine learning lifecycle in an efficient manner. In addition, it also helps users to proceed with experimentation, deployment, and reproducibility of codes. Currently, MLflow offers four components to individual users. The first component is Tracking, which helps developers with logging parameters, metrics, code versions, and output files while running the machine learning code and result analytics part. The second component is Projects that include a command-line and other API tools facilitating seamless management of projects in progress. This also makes it possible for developers to bring all projects with a single workflow. The third component being Models, which can be used for packaging machine learning models, besides proceeding with deployment in diverse serving environments. Finally, Registry- a centralized model serves as a store for APIs and UI, besides helping out users to proceed with the full life cycle of an MLflow Model. Real-time integration facilities with Kubernetes, Google Cloud, and TensorFlow, enables seamless business management. Read more | Amazon SageMaker is a fully integrated service that allows data scientists and developers to easily and quickly train, deploy, and build machine learning models at any range by bringing all bot set capabilities together. It allows users to upload data quickly, tune and train models, compare results and deploy production models all in one place. This software offers a single web-based visual interface to perform all machine learning development steps and enhance data science and team productivity. Moreover, Amazon SageMaker comprises the autopilot features that eliminate the heavy lifting of building a machine learning model and helps users automatically train, build, and tune the ideal machine learning model based on their data. Amazon SageMaker autopilot will automatically search different solutions to discover the best model. Users then can directly deploy the model to production in one click to enhance the model quality. Amazon SageMaker offers other extensive features that assists users in simplifying the data preparation process and helping complete the data preparation workflow. Amazon SageMaker offers a premium and follows a subscription-based pricing strategy. Read more | Workvivo is a new breed of employee communication platform designed to build natural, meaningful bonds between teams while helping companies reach and engage their employees in ways that traditional tools simply can’t. Read more | Qualified's assessment platform is the most effective technique to evaluate coding abilities. Use standardised tests to better understand the strengths and shortcomings of developers. All of the tests have been professionally developed and are intended to evaluate real-world abilities that are relevant to your vacant positions.Create a comprehensive developer profile that includes language and framework-specific competencies, soft skills, and working style. Analyze candidate performance to see how they stack up against your team or all other developers on the Qualified platform.It has a vast list of features such as - Create your own assessments, from little to large-scale projects, without ever leaving their platform. Detailed benchmarking statistics to help you understand the relative complexity of each evaluation, as well as how each developer compares to other software engineers across the world.One of its most beneficial features is code review tools - provides a comprehensive set of code review tools that help save time and gain insight into the quality of developer’s code and working style.Recreate your code project to deploy and grade it at scale. Read more |
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MLflow Custom |
Amazon SageMaker Others |
Workvivo Custom |
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Azure Machine Learning Studio
4.5 Based on 65 Ratings 
Algorithmia
4.6 Based on 13 Ratings |
Databricks
4 Based on 130 Ratings
Azure Machine Learning Studio
4.5 Based on 65 Ratings 
Google Cloud AutoML
4.3 Based on 22 Ratings |
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| Company Details | Located in: San Francisco, California |
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Located in: Cork city, Ireland Founded in: 2017 | Located in: San Francisco, California Founded in: 2016 |
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Not available https://mlflow.org/ |
Not available https://aws.amazon.com/sagemaker/ |
Not available https://www.workvivo.com/ |
Not available https://www.qualified.io/ |
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