Machine Learning Software in North America

Comparing 38 vendors in Machine Learning Software across 114 criteria.
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IBM Watson machine learning software helps enterprises to use their data to create, train, and deploy self-learning models. It also helps users in building analytical models and neural networks. IBM data science experience is a cloud-based, social workspace that helps data professionals to consolidate, create, and collaborate across multiple open sources tools, such as R and Python.
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SAS best machine learning software offers major features like automated model tuning, powerful data manipulation and management, flexible web-based programming environment, integrated text analytics, model assessment and scoring, and modern statistical, data mining, and machine-learning techniques. It facilitates the end-to-end data mining and machine learning process with a visual and programming interface. It also boosts analytics teams of all skill levels with a simple yet powerful and automated way to tackle all tasks in the analytics life cycle.
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Microsoft Azure Machine Learning is a fully managed machine learning software service for advanced analytics in the cloud. It enables enterprises to build advanced analytic web services quickly and eradicate much of the heavy lifting associated with deploying machine learning in modern data-driven applications.
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Google Cloud AutoML Machine Learning Software includes portable models, notebook developer experience, scalable service, managed service, HyperTune, and the ability to discover and share samples. The company's Advanced Solutions Lab (ASL) supports businesses to partner with Google Cloud and apply machine learning software to tackle high-impact business challenges. The solution offers a unique opportunity for technical teams to understand from Google’s machine learning software experts.
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SAP Intelligent Robotic Process Automation controls robotic process automation, machine learning, and conversational AI in an integrated way to automate business processes with SAP Intelligent Robotic Process Automation services. The services offered help to reduce manual activities, respond to customer needs proactively, and make smarter decisions. It is capable to build intelligent bots with machine learning and conversational AI for hands-free execution and stability.

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Amazon Machine Learning Software Amazon Forecast eases the job of obtaining predictions for user’s applications using simple APIs without the need to implement custom prediction generation code or handle any infrastructure. It is considered to be highly scalable, and has the ability to generate billions of predictions on a daily basis and can serve those predictions in real-time and at a high throughput as well.
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2.7
Baidu’s open-source deep learning platform, PaddlePaddle (Parallel Distributed Deep Learning) supports neural network architectures, including convolutional neural networks and recurrent neural networks. The platform is fully scalable and is designed to enhance mathematical operations using BLAS libraries, including Intel MKL, ATLAS, OpenBLAS and cuBLAS. The company has made most of its software and systems open source and provided access to it on an “as-a-service” basis. 
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FICO has introduced new explainable artificial intelligence toolkit (xAI Toolkit) which meets customers’ increasing demand for industry-leading artificial intelligence. This solution enhances decision performance by integrating predictive and prescriptive models directly into real-time business operations to create faster, more impactful business outcomes. It also offers intuitive end-user experience and delivers direct and immediate access to data and insights dynamically.
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Oracle Machine Learning allows data scientists, citizen data scientists, and data analysts to work together to discover their data visually and develop analytical methodologies in the Autonomous Data Warehouse Cloud. Oracle Machine Learning consists of complementary components supporting scalable machine learning algorithms for in-database and big data environments, notebook technology, SQL and R APIs, and Hadoop/Spark environments.

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Dell ML comprises an enhanced solution stack along with data science and framework optimization, enabling swift setup. The solution also leverages DataRobot - an advanced enterprise automated machine learning solution that encapsulates the knowledge, experience and best practices of the world’s leading data scientists, enabling you to quickly build accurate predictive models without previous coding and ML skills.

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2.5

BigML ML software offers a selection of robustly-engineered ML algorithms proven to solve real-world problems by applying a single, standardized framework across the company. It helps avoid dependencies in disparate libraries that enhance complexity, maintenance costs, and technical debt. BigML enables unlimited predictive applications across industries including aerospace, automotive, energy, entertainment, financial services, food, healthcare, IoT, pharmaceutical, transportation, and telecommunications.

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HPE ML Ops solution extends the capabilities of the BlueData EPIC container software platform, providing data science teams with on-demand access to containerized environments for distributed AI / ML and analytics. HPE acquired BlueData in November 2018 to bolster its AI, analytics, and container offerings, and complements HPE’s Hybrid IT solutions and HPE Pointnext Services for enterprise AI deployments.
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2.3

H2O Sparkling Water permits users to combine the quick, scalable machine learning algorithms of H2O with the capabilities of Spark. Spark is an elegant and powerful general-purpose, open-source, an in-memory platform with tremendous momentum. H2O is an in-memory platform for machine learning that is reshaping how people apply math and predictive analytics to business problems. Integrating these two open-source environments provides a seamless experience for users who want to make a query using Spark SQL, feed the results into H2O to build a model and make predictions, and then use the results again in Spark.

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Intel offers a machine learning software platform based on Intel architecture, that helps organizations to transform data into actionable BI through accelerated model training, fast scoring, and highly scalable infrastructure. Intel data analytics acceleration High-Performance Computing reference architectures are optimized for machine learning software.
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KNIME Analytics Platform is the open source software for creating data science. Intuitive, open, and continuously integrating new developments, KNIME makes understanding data and designing data science workflows and reusable components accessible to everyone.

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The platform is designed to create potent machine learning models easy. It enables one to click through the interface for most use cases, whether one is an expert Data Scientist or a beginner. Dataiku makes it easy to leverage machine learning technologies and get instant visual and statistical feedback on model performance.

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RapidMiner Auto Model provides a complete solution on a unified platform that supports the entire Machine Learning workflow from data preparation through model deployment to ongoing model management. The quick-to-learn and easy-to-use workflow designer accelerates end-to-end data science for improved productivity. With the cutting-edge tools and innovative solutions that RapidMiner provides, insights can be delivered swiftly and at scale.

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Altair Knowledge Studio is an advanced data mining, machine learning software, and predictive analytics workbench, well known for industry-leading, patented Decision Trees, Strategy Trees, and its workflow and wizard-driven GUI. Altair Knowledge Studio distinguishes itself by offering a solution that can quickly and easily be adopted into an organization, providing an enhanced user experience that delivers insightful analytics swiftly.

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With organizations understanding the importance of Machine Learning technologies, it is moving out of the realm of untouchable subjects. Alpine Data Labs provides the data scientists with big data machine learning capabilities along with a high level of governance required by each and every organization today. The company is based on the philosophy of tracking movement or lack of movement of data. Alpine is known for its ability to access data sources directly.
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Fractal Analytics enables to reveal valuable insights by accurately recognizing objects in images and videos. From surveilling people in real-time at events to detecting if products are in the right place in shopping aisles, AI can drive value in many ways. This helps in creating in-depth analyses by placing image objects into relevant segments. Fractal Analytics AI-based algorithms help insurers analyze home and auto damage to create more accurate claims for customers.

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TIBCO Software is AI-powered, search-driven experience with built-in data wrangling and advanced analytics. It connects the creativity of the entire team, citizens to experts.  It is capable to combine AutoML, intuitive drag-and-drop workflows, and embedded Jupyter Notebooks that make creating and sharing reusable modules easy.

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1.9

Domino is a data science platform that allows data science teams to quickly develop and deploy models that drive ground-breaking innovation and competitive advantage. The platform automates DevOps for data science so that one can spend more time doing research and test more ideas faster. Enables automatic tracking of work for easy reproducibility, reusability, and collaboration.

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The analytics platform that boasts a built-in machine learning engine provides a wide variety of descriptive, predictive and prescriptive analytics; autonomous decision making and visualization tools. The platform is compatible with SQL, R, and Python, and can interface with visualization and BI tools like RStudio, SAS and Jupyter.

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Luminoso Score Drivers, a machine learning-powered solution helps companies intelligently automate the process of finding drivers in qualitative and quantitative feedback from their customers and employees. Score Drivers analyzes unstructured reviews and survey feedback and reveals how this unstructured data correlates with quantitative ratings.

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