Best Machine Learning Software for Splunk User Behavior Analytics
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Compare the Top Machine Learning Software that integrates with Splunk User Behavior Analytics as of August 2025
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This a list of Machine Learning software that integrates with Splunk User Behavior Analytics. Use the filters on the left to add additional filters for products that have integrations with Splunk User Behavior Analytics. View the products that work with Splunk User Behavior Analytics in the table below.
What is Machine Learning Software for Splunk User Behavior Analytics?
Machine learning software enables developers and data scientists to build, train, and deploy models that can learn from data and make predictions or decisions without being explicitly programmed. These tools provide frameworks and algorithms for tasks such as classification, regression, clustering, and natural language processing. They often come with features like data preprocessing, model evaluation, and hyperparameter tuning, which help optimize the performance of machine learning models. With the ability to analyze large datasets and uncover patterns, machine learning software is widely used in industries like healthcare, finance, marketing, and autonomous systems. Overall, this software empowers organizations to leverage data for smarter decision-making and automation. Compare and read user reviews of the best Machine Learning software for Splunk User Behavior Analytics currently available using the table below. This list is updated regularly.
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Splunk Cloud Platform
Splunk
Turn data into answers with Splunk deployed and managed securely, reliably and scalably as a service. With your IT backend managed by our Splunk experts, you can focus on acting on your data. Splunk-provisioned and managed infrastructure delivers a turnkey, cloud-based data analytics solution. Go live in as little as two days. Managed software upgrades ensure you always have the latest functionality. Tap into the value of your data in days with fewer requirements to turn data into action. Splunk Cloud meets the FedRAMP security standards, and helps U.S. federal agencies and their partners drive confident decisions and decisive actions at mission speeds. Drive productivity and contextual insights with Splunk’s mobile apps, augmented reality and natural language capabilities. Extend the utility of your Splunk solutions to any location with a simple phrase or the tap of a finger. From infrastructure management to data compliance, Splunk Cloud is built to scale. -
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Amazon SageMaker
Amazon
Amazon SageMaker is an advanced machine learning service that provides an integrated environment for building, training, and deploying machine learning (ML) models. It combines tools for model development, data processing, and AI capabilities in a unified studio, enabling users to collaborate and work faster. SageMaker supports various data sources, such as Amazon S3 data lakes and Amazon Redshift data warehouses, while ensuring enterprise security and governance through its built-in features. The service also offers tools for generative AI applications, making it easier for users to customize and scale AI use cases. SageMaker’s architecture simplifies the AI lifecycle, from data discovery to model deployment, providing a seamless experience for developers. -
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Amazon Augmented AI (A2I)
Amazon
Amazon Augmented AI (Amazon A2I) makes it easy to build the workflows required for human review of ML predictions. Amazon A2I brings human review to all developers, removing the undifferentiated heavy lifting associated with building human review systems or managing large numbers of human reviewers. Many machine learning applications require humans to review low confidence predictions to ensure the results are correct. For example, extracting information from scanned mortgage application forms can require human review in some cases due to low-quality scans or poor handwriting. But building human review systems can be time consuming and expensive because it involves implementing complex processes or “workflows”, writing custom software to manage review tasks and results, and in many cases, managing large groups of reviewers.
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