Machine Learning Platforms
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Machine Learning Studio is a powerfully simple browser-based, visual drag-and-drop authoring environment where no coding is necessary. Go from idea to deployment in a matter of clicks. Microsoft Azure Machine Learning Studio is a collaborative, drag-and-drop tool you can use to build, test, and deploy predictive analytics solutions on your data. Machine Learning Studio publishes models as web services that can easily be consumed by custom apps or BI tools such as Excel.

Cloud Machine Learning Engine is a managed service that lets developers and data scientists build and run superior machine learning models in production. Cloud ML Engine offers training and prediction services, which can be used together or individually. It has been used by enterprises to solve problems ranging from identifying clouds in satellite images, ensuring food safety, and responding four times faster to customer emails. The training and prediction services within ML Engine are now referred to as AI Platform Training and AI Platform Prediction.

The Databricks Data Intelligence Platform allows your entire organization to use data and AI. It’s built on a lakehouse to provide an open, unified foundation for all data and governance, and is powered by a Data Intelligence Engine that understands the uniqueness of your data. From ETL to data warehousing to generative AI, Databricks helps you simplify and accelerate your data and AI goals.

MATLAB is a high-level language and interactive environment for numerical computation, visualization, and programming. It is a programming and numeric computing platform used by millions of engineers and scientists to analyze data, develop algorithms, and create models.

Amazon Machine Learning is an Amazon Web Services product that allows a developer to discover patterns in end-user data through algorithms, construct mathematical models based on these patterns and then create and implement predictive applications.

Microsoft Fabric is a platform that allows users to get, create, share, and visualize data using an array of tools. Give your data teams all the tools they need in a unified experience that helps reduce the cost and effort of data integration, governance, and security.

TFX is an end-to-end platform for deploying production ML pipelines. A TFX pipeline is a sequence of components that implement an ML pipeline which is specifically designed for scalable, high-performance machine learning tasks. Components are built using TFX libraries which can also be used individually. When you're ready to move your models from research to production, TFX can be used to create and manage a production pipeline.

Bringing together widely adopted AWS machine learning (ML) and analytics capabilities, Amazon SageMaker delivers an integrated experience for analytics and AI with unified access to all your data. Collaborate and build faster from a unified studio (preview) using familiar AWS tools for model development, generative AI, data processing, and SQL analytics, accelerated by Amazon Q Developer, the most capable generative AI assistant for software development.

deepsense.ai is a data science company, which helps organizations gain competitive advantage by providing them with AI-based end-to-end solutions, with the main focus on computer vision, predictive analytics and natural language processing. The company also delivers machine learning and deep learning training programs to support enterprises in building AI capabilities in-house.

Dataiku is the platform democratizing access to data and enabling enterprises to build their own path to AI in a human-centric way. With Dataiku, everyone can get involved in data and AI projects on a single platform for design and production that delivers use cases in days, not months. No matter where they sit, they work in a safe and governed way that helps manage risk and create trust to drive high-quality outputs and value for your business.

The DataRobot Enterprise AI platform includes two independent but fully integrable machine learning model building products, and each can be deployed in multiple ways to match your business needs and IT requirements. All configurations feature a constantly expanding set of diverse, best-in-class algorithms from R, Python, H2O, Spark, and other sources, giving you the best set of tools for your machine learning and AI projects.

Alteryx One connects data, business context, and AI for insights that lead to confident decisions. Intelligent enterprises connect data, analytics, and AI across operations for faster, smarter decisions. With Alteryx One, analytics and AI show up where work happens, not just in slides. IT sets the guardrails as teams move faster and new ideas spark. From first use case to broad rollout, you get one step closer to becoming an intelligent enterprise.

KNIME offers a complete platform for end-to-end data science, from creating analytical models, to deploying them and sharing insights within the organization, through to data apps and services. The free and open source KNIME Analytics Platform allows users to easily build analyses with an intuitive, low-code/no-code interface. KNIME Business Hub enables users across different disciplines to collaborate and productionize analytical solutions created using KNIME Analytics Platform.

H2O is a fully open source, distributed in-memory machine learning platform with linear scalability. H2O supports the most widely used statistical & machine learning algorithms including gradient boosted machines, generalized linear models, deep learning and more. H2O also has an industry leading AutoML functionality that automatically runs through all the algorithms and their hyperparameters to produce a leaderboard of the best models.