Alternatives to Oracle Machine Learning
Compare Oracle Machine Learning alternatives for your business or organization using the curated list below. SourceForge ranks the best alternatives to Oracle Machine Learning in 2026. Compare features, ratings, user reviews, pricing, and more from Oracle Machine Learning competitors and alternatives in order to make an informed decision for your business.
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Google Cloud Vision AI
Google
Derive insights from your images in the cloud or at the edge with AutoML Vision or use pre-trained Vision API models to detect emotion, understand text, and more. Google Cloud offers two computer vision products that use machine learning to help you understand your images with industry-leading prediction accuracy. Automate the training of your own custom machine learning models. Simply upload images and train custom image models with AutoML Vision’s easy-to-use graphical interface; optimize your models for accuracy, latency, and size; and export them to your application in the cloud, or to an array of devices at the edge. Google Cloud’s Vision API offers powerful pre-trained machine learning models through REST and RPC APIs. Assign labels to images and quickly classify them into millions of predefined categories. Detect objects and faces, read printed and handwritten text, and build valuable metadata into your image catalog. -
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Get insightful text analysis with machine learning that extracts, analyzes, and stores text. Train high-quality machine learning custom models without a single line of code with AutoML. Apply natural language understanding (NLU) to apps with Natural Language API. Use entity analysis to find and label fields within a document, including emails, chat, and social media, and then sentiment analysis to understand customer opinions to find actionable product and UX insights. Natural Language with speech-to-text API extracts insights from audio. Vision API adds optical character recognition (OCR) for scanned docs. Translation API understands sentiments in multiple languages. Use custom entity extraction to identify domain-specific entities within documents, many of which don’t appear in standard language models, without having to spend time or money on manual analysis. Train your own high-quality machine learning custom models to classify, extract, and detect sentiment.
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Immuta
Immuta
Immuta is the market leader in secure Data Access, providing data teams one universal platform to control access to analytical data sets in the cloud. Only Immuta can automate access to data by discovering, securing, and monitoring data. Data-driven organizations around the world trust Immuta to speed time to data, safely share more data with more users, and mitigate the risk of data leaks and breaches. Founded in 2015, Immuta is headquartered in Boston, MA. Immuta is the fastest way for algorithm-driven enterprises to accelerate the development and control of machine learning and advanced analytics. The company's hyperscale data management platform provides data scientists with rapid, personalized data access to dramatically improve the creation, deployment and auditability of machine learning and AI. -
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Oracle Data Science
Oracle
A data science platform that improves productivity with unparalleled abilities. Build and evaluate higher-quality machine learning (ML) models. Increase business flexibility by putting enterprise-trusted data to work quickly and support data-driven business objectives with easier deployment of ML models. Using cloud-based platforms to discover new business insights. Building a machine learning model is an iterative process. In this ebook, we break down the process and describe how machine learning models are built. Explore notebooks and build or test machine learning algorithms. Try AutoML and see data science results. Build high-quality models faster and easier. Automated machine learning capabilities rapidly examine the data and recommend the optimal data features and best algorithms. Additionally, automated machine learning tunes the model and explains the model’s results. -
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Kraken
Big Squid
Kraken is for everyone from analysts to data scientists. Built to be the easiest-to-use, no-code automated machine learning platform. The Kraken no-code automated machine learning (AutoML) platform simplifies and automates data science tasks like data prep, data cleaning, algorithm selection, model training, and model deployment. Kraken was built with analysts and engineers in mind. If you've done data analysis before, you're ready! Kraken's no-code, easy-to-use interface and integrated SONAR© training make it easy to become a citizen data scientist. Advanced features allow data scientists to work faster and more efficiently. Whether you use Excel or flat files for day-to-day reporting or just ad-hoc analysis and exports, drag-and-drop CSV upload and the Amazon S3 connector in Kraken make it easy to start building models with a few clicks. Data Connectors in Kraken allow you to connect to your favorite data warehouse, business intelligence tools, and cloud storage.Starting Price: $100 per month -
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Altair Knowledge Studio
Altair
Data scientists and business analysts use Altair to generate actionable insight from their data. Knowledge Studio is a market-leading easy to use machine learning and predictive analytics solution that rapidly visualizes data as it quickly generates explainable results - without requiring a single line of code. A recognized analytics leader, Knowledge Studio brings transparency and automation to machine learning with features such as AutoML and explainable AI without restricting how models are configured and tuned, giving you control over model building. Knowledge Studio is designed to enable collaboration across the business. Data scientists and business analysts can complete complex projects in minutes or hours, not weeks or months. Results are easily understood and explained. The ease of use and automation of steps of the modeling process enable data scientists to efficiently develop more machine learning models faster than coding or using other tools. -
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Google Cloud AutoML
Google
Cloud AutoML is a suite of machine learning products that enables developers with limited machine learning expertise to train high-quality models specific to their business needs. It relies on Google’s state-of-the-art transfer learning and neural architecture search technology. Cloud AutoML leverages more than 10 years of proprietary Google Research technology to help your machine learning models achieve faster performance and more accurate predictions. Use Cloud AutoML’s simple graphical user interface to train, evaluate, improve, and deploy models based on your data. You’re only a few minutes away from your own custom machine learning model. Google’s human labeling service can put a team of people to work annotating or cleaning your labels to make sure your models are being trained on high-quality data. -
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Oracle Data Miner
Oracle
Oracle Data Miner enables data scientists, “citizen data scientists,” and business and data analysts to work directly with data inside the database using a graphical “drag and drop” workflow editor. Oracle Data Miner (ODMr), an extension to Oracle SQL Developer, captures and documents in graphical analytical workflows the steps users take while exploring data and developing machine learning methodologies. ODMr workflows are useful for re-executing analytical methodologies and for sharing insights with team members. ODMr generates SQL and PL/SQL scripts and offers a workflow API for accelerating model deployment throughout the enterprise. Eliminate data movement, achieve big data scalability, preserve security, and accelerate time from model development to model deployment. -
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Anaconda
Anaconda
Empowering the enterprise to do real data science at speed and scale with a full-featured machine learning platform. Spend less time managing tools and infrastructure, so you can focus on building machine learning applications that move your business forward. Anaconda Enterprise takes the headache out of ML operations, puts open-source innovation at your fingertips, and provides the foundation for serious data science and machine learning production without locking you into specific models, templates, or workflows. Software developers and data scientists can work together with AE to build, test, debug, and deploy models using their preferred languages and tools. AE provides access to both notebooks and IDEs so developers and data scientists can work together more efficiently. They can also choose from example projects and preconfigured projects. AE projects are automatically containerized so they can be moved between environments with ease. -
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Dataiku
Dataiku
Dataiku is an advanced data science and machine learning platform designed to enable teams to build, deploy, and manage AI and analytics projects at scale. It empowers users, from data scientists to business analysts, to collaboratively create data pipelines, develop machine learning models, and prepare data using both visual and coding interfaces. Dataiku supports the entire AI lifecycle, offering tools for data preparation, model training, deployment, and monitoring. The platform also includes integrations for advanced capabilities like generative AI, helping organizations innovate and deploy AI solutions across industries. -
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Profet AI
Profet AI
Profet AI’s end-to-end No-Code AutoML Platform is manufacturers’ Virtual Data Scientist. It empowers industry domain/IT experts to rapidly build high-quality prediction models and deploy Industrial AI applications to solve their everyday production and digitalization challenges. Profet AI AutoML Platform is widely adopted by world's leading customers across industries, including the world's leading EMS, Semi-OSAT, PCB, IC design House, display panel and materials solution providers. We leverage industry leading companies' successful cases to benefit our customers to implement AI within one week. -
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ML.NET
Microsoft
ML.NET is a free, open source, and cross-platform machine learning framework designed for .NET developers to build custom machine learning models using C# or F# without leaving the .NET ecosystem. It supports various machine learning tasks, including classification, regression, clustering, anomaly detection, and recommendation systems. ML.NET integrates with other popular ML frameworks like TensorFlow and ONNX, enabling additional scenarios such as image classification and object detection. It offers tools like Model Builder and the ML.NET CLI, which utilize Automated Machine Learning (AutoML) to simplify the process of building, training, and deploying high-quality models. These tools automatically explore different algorithms and settings to find the best-performing model for a given scenario.Starting Price: Free -
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PredictSense
Winjit
PredictSense is an end-to-end Machine Learning platform powered by AutoML to create AI-powered analytical solutions. Fuel the new technological revolution of tomorrow by accelerating machine intelligence. AI is key to unlocking value from enterprise data investments. PredictSense enables businesses to monetize critical data infrastructure and technology investments by creating AI driven advanced analytical solutions rapidly. Empower data science and business teams with advanced capabilities to quickly build and deploy robust technology solutions at scale. Easily integrate AI into the current product ecosystem and fast track GTM for new AI solutions. Incur huge savings in cost, time and effort by building complex ML models in AutoML. PredictSense democratizes AI for every individual in the organization and creates a simple, user-friendly collaboration platform to seamlessly manage critical ML deployments. -
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AutoKeras
AutoKeras
An AutoML system based on Keras. It is developed by DATA Lab at Texas A&M University. The goal of AutoKeras is to make machine learning accessible to everyone. AutoKeras supports several tasks with an extremely simple interface. -
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Decanter AI
MoBagel Inc.
Decanter AI is a no-code AI platform to help data scientists, domain experts, and business stakeholders to design and deploy AI solutions seamlessly. Data provides a record of a business's successes and failures, enabling review and process improvement. However, the high technical requirements of dealing with big data to make informed business decisions will become a significant challenge in the near future, particularly for enterprises with limited knowledge and experience in building AI models. Decanter AI utilizes automated machine learning (AutoML), automation of the machine learning process, to help enterprises make AI-driven decisions and generate business value from their data. Decanter AI empowers enterprises with world-class machine learning technologies through an intuitive interface. By rapidly building, testing, and deploying highly accurate machine learning models, Decanter AI enables enterprises to solve business challenges and unique needs using an AI-driven approach. -
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AutoML Translation lets you create custom translation models for translation queries to return results specific to your domain. AutoML Translation usage prices are calculated based on the amount of training required (measured in hours) and how many characters you send to translate. Dynamically detect and translate between languages. Integrated REST and gRPC APIs. Supports 50 language pairs. Translate with custom models. Cloud AutoML enables developers with limited machine learning expertise to train high-quality models specific to their business needs. Build your own custom machine learning model in minutes. Imagine you run a financial reporting service and there is an opportunity to expand it to new countries. In those markets, your urgent financial documents need to be translated in real time. AutoML Translation can help you automate your translation work in an easy way. scalable and to access new markets quickly.Starting Price: $45 per hour
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Vertex AI Notebooks
Google
Vertex AI Notebooks is a fully managed, scalable solution from Google Cloud that accelerates machine learning (ML) development. It provides a seamless, interactive environment for data scientists and developers to explore data, prototype models, and collaborate in real-time. With integration into Google Cloud’s vast data and ML tools, Vertex AI Notebooks supports rapid prototyping, automated workflows, and deployment, making it easier to scale ML operations. The platform’s support for both Colab Enterprise and Vertex AI Workbench ensures a flexible and secure environment for diverse enterprise needs.Starting Price: $10 per GB -
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Auger.AI
Auger.AI
Auger.AI has the most complete solution for ensuring machine learning model accuracy. Our MLRAM tool (Machine Learning Review and Monitoring) ensures your models are consistently accurate. It even computes the ROI of your predictive model! MLRAM works with any machine learning technology stack. If your ML system lifecyle doesn’t include consistent measurement of model accuracy, you’re likely losing money from inaccurate predictions. And frequent retraining of models is both expensive and, if they’re experiencing concept drift, may not fix the underlying problem. MLRAM provides value to both the data scientist and business user with features like accuracy visualization graphs, performance and accuracy alerts, anomaly detection and automated optimized retraining. Hooking up your predictive model to MLRAM is just a single line of code. We offer a free one month trial of MLRAM to qualified users. Auger.AI is the most accurate AutoML platform.Starting Price: $200 per month -
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Vectice
Vectice
Enabling all enterprise’s AI/ML initiatives to result in consistent and positive impact. Data scientists deserve a solution that makes all their experiments reproducible, every asset discoverable and simplifies knowledge transfer. Managers deserve a dedicated data science solution. to secure knowledge, automate reporting and simplify reviews and processes. Vectice is on a mission to revolutionize the way data science teams work and collaborate. The goal is to ensure consistent and positive AI/ML impact for all organizations. Vectice is bringing the first automated knowledge solution that is both data science aware, actionable and compatible with the tools data scientists use. Vectice auto-captures all the assets that AI/ML teams create such as datasets, code, notebooks, models or runs. Then it auto-generates documentation from business requirements to production deployments. -
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Deepnote
Deepnote
Deepnote is building the best data science notebook for teams. In the notebook, users can connect their data, explore, and analyze it with real-time collaboration and version control. Users can easily share project links with team collaborators, or with end-users to present polished assets. All of this is done through a powerful, browser-based UI that runs in the cloud. We built Deepnote because data scientists don't work alone. Features: - Sharing notebooks and projects via URL - Inviting others to view, comment and collaborate, with version control - Publishing notebooks with visualizations for presentations - Sharing datasets between projects - Set team permissions to decide who can edit vs view code - Full linux terminal access - Code completion - Automatic python package management - Importing from github - PostgreSQL DB connectionStarting Price: Free -
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Neuton AutoML
Neuton.AI
Neuton, a no-code AutoML solution, makes Machine Learning available to everyone. Explore data insights and make predictions leveraging Automated Artificial Intelligence. • NO coding • NO need for technical skills • NO need for data science knowledge Neuton provides comprehensive Explainability Office©, a unique set of tools that allow users to evaluate model quality at every stage, identify the logic behind the model analysis, understand why certain predictions have been made. • Exploratory Data Analysis • Feature Importance Matrix with class granularity • Model Interpreter • Feature Influence Matrix • Model-to-Data Relevance Indicators historical and for every prediction • Model Quality Index • Confidence Interval • Extensive list of supported metrics with Radar Diagram Neuton enables users to implement ML in days instead of months.Starting Price: $0 -
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Lityx
Lityx
Empower your team to deliver AI-based business solutions efficiently and at scale. Cloud-based, comprehensive, no-code machine learning. Accelerate team production. Efficiently capture actionable insights. Leverage your data to predict and optimize behaviors. Rapidly scale and take models into production. Gurobi Optimizer allows users to tackle even the toughest challenges. LityxIQ is the powerful yet easy-to-use, no-code AutoML platform built by data scientists for all your team members. A cloud-based SaaS, it works seamlessly with the tools you already have, integrating easily with other systems, source data platforms, data lakes and data warehouses, as well as the leading visualization tools. And fueled by the world’s fastest solver, you can tackle even the toughest analytics job. Our Solution Accelerators capability increases efficiency by reducing time to value. -
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H2O.ai
H2O.ai
H2O.ai is the open source leader in AI and machine learning with a mission to democratize AI for everyone. Our industry-leading enterprise-ready platforms are used by hundreds of thousands of data scientists in over 20,000 organizations globally. We empower every company to be an AI company in financial services, insurance, healthcare, telco, retail, pharmaceutical, and marketing and delivering real value and transforming businesses today. -
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RapidMiner
Altair
RapidMiner is reinventing enterprise AI so that anyone has the power to positively shape the future. We’re doing this by enabling ‘data loving’ people of all skill levels, across the enterprise, to rapidly create and operate AI solutions to drive immediate business impact. We offer an end-to-end platform that unifies data prep, machine learning, and model operations with a user experience that provides depth for data scientists and simplifies complex tasks for everyone else. Our Center of Excellence methodology and the RapidMiner Academy ensures customers are successful, no matter their experience or resource levels. Simplify operations, no matter how complex models are, or how they were created. Deploy, evaluate, compare, monitor, manage and swap any model. Solve your business issues faster with sharper insights and predictive models, no one understands the business problem like you do.Starting Price: Free -
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Comet
Comet
Manage and optimize models across the entire ML lifecycle, from experiment tracking to monitoring models in production. Achieve your goals faster with the platform built to meet the intense demands of enterprise teams deploying ML at scale. Supports your deployment strategy whether it’s private cloud, on-premise servers, or hybrid. Add two lines of code to your notebook or script and start tracking your experiments. Works wherever you run your code, with any machine learning library, and for any machine learning task. Easily compare experiments—code, hyperparameters, metrics, predictions, dependencies, system metrics, and more—to understand differences in model performance. Monitor your models during every step from training to production. Get alerts when something is amiss, and debug your models to address the issue. Increase productivity, collaboration, and visibility across all teams and stakeholders.Starting Price: $179 per user per month -
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Google Colab
Google
Google Colab is a free, hosted Jupyter Notebook service that provides cloud-based environments for machine learning, data science, and educational purposes. It offers no-setup, easy access to computational resources such as GPUs and TPUs, making it ideal for users working with data-intensive projects. Colab allows users to run Python code in an interactive, notebook-style environment, share and collaborate on projects, and access extensive pre-built resources for efficient experimentation and learning. Colab also now offers a Data Science Agent automating analysis, from understanding the data to delivering insights in a working Colab notebook (Sequences shortened. Results for illustrative purposes. Data Science Agent may make mistakes.) -
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SensiML Analytics Studio
SensiML
Sensiml analytics toolkit. Create smart iot sensor devices rapidly reduce data science complexity. Create compact algorithms that execute on tiny IoT endpoints, not in the cloud. Collect accurate, traceable, version controlled datasets. Utilize advanced AutoML code-gen to quickly produce autonomous working device code. Choose your interface, level of AI expertise, and retain full access to every aspect of your algorithm. Build edge tuning models that that customize behavior as they see more data. SensiML Analytics Toolkit suite automates each step of the process for creating optimized AI IoT sensor recognition code. The overall workflow uses a growing library of advanced ML and AI algorithms to generate code that can learn from new data either the development phase or once deployed. Non-invasive, rapid disease screening applications utilizing intelligent classification of one or more bio-sensing inputs are critical tools for healthcare decision support. -
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Wallaroo.AI
Wallaroo.AI
Wallaroo facilitates the last-mile of your machine learning journey, getting ML into your production environment to impact the bottom line, with incredible speed and efficiency. Wallaroo is purpose-built from the ground up to be the easy way to deploy and manage ML in production, unlike Apache Spark, or heavy-weight containers. ML with up to 80% lower cost and easily scale to more data, more models, more complex models. Wallaroo is designed to enable data scientists to quickly and easily deploy their ML models against live data, whether to testing environments, staging, or prod. Wallaroo supports the largest set of machine learning training frameworks possible. You’re free to focus on developing and iterating on your models while letting the platform take care of deployment and inference at speed and scale. -
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Apache PredictionIO
Apache
Apache PredictionIO® is an open-source machine learning server built on top of a state-of-the-art open-source stack for developers and data scientists to create predictive engines for any machine learning task. It lets you quickly build and deploy an engine as a web service on production with customizable templates. Respond to dynamic queries in real-time once deployed as a web service, evaluate and tune multiple engine variants systematically, and unify data from multiple platforms in batch or in real-time for comprehensive predictive analytics. Speed up machine learning modeling with systematic processes and pre-built evaluation measures, support machine learning and data processing libraries such as Spark MLLib and OpenNLP. Implement your own machine learning models and seamlessly incorporate them into your engine. Simplify data infrastructure management. Apache PredictionIO® can be installed as a full machine learning stack, bundled with Apache Spark, MLlib, HBase, Akka HTTP, etc.Starting Price: Free -
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Metaflow
Netflix
Successful data science projects are delivered by data scientists who can build, improve, and operate end-to-end workflows independently, focusing more on data science, less on engineering. Use Metaflow with your favorite data science libraries, such as Tensorflow or SciKit Learn, and write your models in idiomatic Python code with not much new to learn. Metaflow also supports the R language. Metaflow helps you design your workflow, run it at scale, and deploy it to production. It versions and tracks all your experiments and data automatically. It allows you to inspect results easily in notebooks. Metaflow comes packaged with the tutorials, so getting started is easy. You can make copies of all the tutorials in your current directory using the metaflow command line interface. -
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Predictive Modeling with Machine Learning and Explainable AI. FICO® Analytics Workbench™ is an integrated suite of state-of-the-art analytic authoring tools that empowers companies to improve business decisions across the customer lifecycle. With it, data scientists can build superior decisioning capabilities using a wide range of predictive data modeling tools and algorithms, including the latest machine learning (ML) and explainable artificial intelligence (xAI) approaches. We enhance the best of open source data science and machine learning with innovative intellectual property from FICO to deliver world-class analytic capabilities to discover, combine, and operationalize predictive signals in data. Analytics Workbench is built on the leading FICO® Platform to allow new predictive models and strategies to be deployed into production with ease.
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OCI Data Labeling
Oracle
OCI Data Labeling is a service that enables developers and data scientists to build accurately labelled datasets for training AI and machine-learning models. It supports documents (PDF, TIFF), images (JPEG, PNG), and text, allowing users to upload raw data, apply annotations (such as classification labels, object-detection bounding boxes, or key-value pairs), and export the results in line-delimited JSON for seamless integration into model-training workflows. The service offers custom templates for different annotation formats, user interfaces, and public APIs for dataset creation and management, and smooth interoperability with other data and AI services, so annotated data can feed directly into custom vision or language models, as well as Oracle’s AI services. OCI Data Labeling lets users create a dataset, generate records, annotate them, and then use the export snapshot for model development.Starting Price: $0.0002 per 1,000 transactions -
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IBM SPSS Modeler
IBM
IBM SPSS Modeler is a leading visual data science and machine learning (ML) solution designed to help enterprises accelerate time to value by speeding up operational tasks for data scientists. Organizations worldwide use it for data preparation and discovery, predictive analytics, model management and deployment, and ML to monetize data assets. IBM SPSS Modeler automatically transforms data into the best format for the most accurate predictive modeling. It now only takes a few clicks for you to analyze data, identify fixes, screen out fields and derive new attributes. Leverage IBM SPSS Modeler’s powerful graphics engine to bring your insights to life. The smart chart recommender finds the perfect chart for your data from among dozens of options, so you can share your insights quickly and easily using compelling visualizations. -
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Cloudera Data Science Workbench
Cloudera
Accelerate machine learning from research to production with a consistent experience built for your traditional platform. With Python, R, and Scala directly in the web browser, Cloudera Data Science Workbench (CDSW) delivers a self-service experience data scientists will love. Download and experiment with the latest libraries and frameworks in customizable project environments that work just like your laptop. Cloudera Data Science Workbench provides connectivity not only to CDH and HDP but also to the systems your data science teams rely on for analysis. Cloudera Data Science Workbench lets data scientists manage their own analytics pipelines, including built-in scheduling, monitoring, and email alerting. Quickly develop and prototype new machine learning projects and easily deploy them to production. -
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Apache Mahout
Apache Software Foundation
Apache Mahout is a powerful, scalable, and versatile machine learning library designed for distributed data processing. It offers a comprehensive set of algorithms for various tasks, including classification, clustering, recommendation, and pattern mining. Built on top of the Apache Hadoop ecosystem, Mahout leverages MapReduce and Spark to enable data processing on large-scale datasets. Apache Mahout(TM) is a distributed linear algebra framework and mathematically expressive Scala DSL designed to let mathematicians, statisticians, and data scientists quickly implement their own algorithms. Apache Spark is the recommended out-of-the-box distributed back-end or can be extended to other distributed backends. Matrix computations are a fundamental part of many scientific and engineering applications, including machine learning, computer vision, and data analysis. Apache Mahout is designed to handle large-scale data processing by leveraging the power of Hadoop and Spark. -
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Oracle Spatial
Oracle
In keeping with Oracle's mission to help people see data in new ways, discover insights, unlock endless possibilities, Oracle Database now includes machine learning, spatial and graph features. If you have an Oracle Database license, you can use all the industry-leading machine learning, spatial and graph capabilities for development and deployment purposes on-premise and in Oracle Cloud Database Services. Oracle's spatial database is included in Oracle's converged database, allowing developers and analysts to get started easily with location intelligence analytics and mapping services. It enables Geographic Information System (GIS) professionals to successfully deploy advanced geospatial applications. Organizations can manage different types of geospatial data, perform hundreds of spatial analytic operations, and use interactive map visualization tools with the spatial features in Oracle Autonomous Database and Oracle Database. -
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Vaex
Vaex
At Vaex.io we aim to democratize big data and make it available to anyone, on any machine, at any scale. Cut development time by 80%, your prototype is your solution. Create automatic pipelines for any model. Empower your data scientists. Turn any laptop into a big data powerhouse, no clusters, no engineers. We provide reliable and fast data driven solutions. With our state-of-the-art technology we build and deploy machine learning models faster than anyone on the market. Turn your data scientist into big data engineers. We provide comprehensive training of your employees, enabling you to take full advantage of our technology. Combines memory mapping, a sophisticated expression system, and fast out-of-core algorithms. Efficiently visualize and explore big datasets, and build machine learning models on a single machine. -
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Domino Enterprise MLOps Platform
Domino Data Lab
The Domino platform helps data science teams improve the speed, quality, and impact of data science at scale. Domino is open and flexible, empowering professional data scientists to use their preferred tools and infrastructure. Data science models get into production fast and are kept operating at peak performance with integrated workflows. Domino also delivers the security, governance and compliance that enterprises expect. The Self-Service Infrastructure Portal makes data science teams become more productive with easy access to their preferred tools, scalable compute, and diverse data sets. The Integrated Model Factory includes a workbench, model and app deployment, and integrated monitoring to rapidly experiment, deploy the best models in production, ensure optimal performance, and collaborate across the end-to-end data science lifecycle. The System of Record allows teams to easily find, reuse, reproduce, and build on any data science work to amplify innovation. -
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Actable AI
Actable AI
Powered by open-source state-of-the-art AutoML to train quality models without hassle. Leverages Deep Learning and pre-trained models for extra intelligence whenever applicable. Utilizes Causal AI with AutoML for fairness, causal inference and counterfactual predictions. All trained models are deployed instantly to be used interactively online or with an API. Full feature importances and model explanations with Shapley values. Our AI engine is entirely open-source. It means our algorithms can be fully audited and used everywhere. Clusters customers or products to similar cohorts with a rich set of features. Forecasts future by capturing temporal patterns from historical data. Trains predictive models with labelled data to predict unlabelled data.Starting Price: $80 per user per month -
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QC Ware Forge
QC Ware
Unique and efficient turn-key algorithms for data scientists. Powerful circuit building blocks for quantum engineers. Turn-key algorithm implementations for data scientists, financial analysts, and engineers. Explore problems in binary optimization, machine learning, linear algebra, and monte carlo sampling on simulators and real quantum hardware. No prior experience with quantum computing is required. Use NISQ data loader circuits to load classical data into quantum states to use with your algorithms. Use circuit building blocks for linear algebra with distance estimation and matrix multiplication circuits. Use our circuit building blocks to create your own algorithms. Get a significant performance boost for D-Wave hardware and use the latest improvements for gate-based approaches. Try out quantum data loaders and algorithms with guaranteed speed-ups on clustering, classification, and regression.Starting Price: $2,500 per hour -
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Zepl
Zepl
Sync, search and manage all the work across your data science team. Zepl’s powerful search lets you discover and reuse models and code. Use Zepl’s enterprise collaboration platform to query data from Snowflake, Athena or Redshift and build your models in Python. Use pivoting and dynamic forms for enhanced interactions with your data using heatmap, radar, and Sankey charts. Zepl creates a new container every time you run your notebook, providing you with the same image each time you run your models. Invite team members to join a shared space and work together in real time or simply leave their comments on a notebook. Use fine-grained access controls to share your work. Allow others have read, edit, and run access as well as enable collaboration and distribution. All notebooks are auto-saved and versioned. You can name, manage and roll back all versions through an easy-to-use interface, and export seamlessly into Github. -
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Neural Designer
Artelnics
Neural Designer is a powerful software tool for developing and deploying machine learning models. It provides a user-friendly interface that allows users to build, train, and evaluate neural networks without requiring extensive programming knowledge. With a wide range of features and algorithms, Neural Designer simplifies the entire machine learning workflow, from data preprocessing to model optimization. In addition, it supports various data types, including numerical, categorical, and text, making it versatile for domains. Additionally, Neural Designer offers automatic model selection and hyperparameter optimization, enabling users to find the best model for their data with minimal effort. Finally, its intuitive visualizations and comprehensive reports facilitate interpreting and understanding the model's performance.Starting Price: $2495/year (per user) -
43
NVIDIA Merlin
NVIDIA
NVIDIA Merlin empowers data scientists, machine learning engineers, and researchers to build high-performing recommenders at scale. Merlin includes libraries, methods, and tools that streamline the building of recommenders by addressing common preprocessing, feature engineering, training, inference, and deploying to production challenges. Merlin components and capabilities are optimized to support the retrieval, filtering, scoring, and ordering of hundreds of terabytes of data, all accessible through easy-to-use APIs. With Merlin, better predictions, increased click-through rates, and faster deployment to production are within reach. NVIDIA Merlin, as part of NVIDIA AI, advances our commitment to supporting innovative practitioners doing their best work. As an end-to-end solution, NVIDIA Merlin components are designed to be interoperable within existing recommender workflows that utilize data science, and machine learning (ML). -
44
TruEra
TruEra
A machine learning monitoring solution that helps you easily oversee and troubleshoot high model volumes. With explainability accuracy that’s unparalleled and unique analyses that are not available anywhere else, data scientists avoid false alarms and dead ends, addressing critical problems quickly and effectively. Your machine learning models stay optimized, so that your business is optimized. TruEra’s solution is based on an explainability engine that, due to years of dedicated research and development, is significantly more accurate than current tools. TruEra’s enterprise-class AI explainability technology is without peer. The core diagnostic engine is based on six years of research at Carnegie Mellon University and dramatically outperforms competitors. The platform quickly performs sophisticated sensitivity analysis that enables data scientists, business users, and risk and compliance teams to understand exactly how and why a model makes predictions. -
45
Oracle Big Data Service
Oracle
Oracle Big Data Service makes it easy for customers to deploy Hadoop clusters of all sizes, with VM shapes ranging from 1 OCPU to a dedicated bare metal environment. Customers choose between high-performance NVmE storage or cost-effective block storage, and can grow or shrink their clusters. Quickly create Hadoop-based data lakes to extend or complement customer data warehouses, and ensure that all data is both accessible and managed cost-effectively. Query, visualize and transform data so data scientists can build machine learning models using the included notebook with its R, Python and SQL support. Move customer-managed Hadoop clusters to a fully-managed cloud-based service, reducing management costs and improving resource utilization.Starting Price: $0.1344 per hour -
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Oracle Autonomous Database
Oracle
Oracle Autonomous Database is a fully automated cloud database that uses machine learning to automate database tuning, security, backups, updates, and other routine management tasks traditionally performed by DBAs. It supports a wide range of data types and models, including SQL, JSON documents, graph, geospatial, text, and vectors, enabling developers to build applications for any workload without integrating multiple specialty databases. Built-in AI and machine learning capabilities allow for natural language queries, automated data insights, and the development of AI-powered applications. It offers self-service tools for data loading, transformation, analysis, and governance, reducing the need for IT intervention. It provides flexible deployment options, including serverless and dedicated infrastructure on Oracle Cloud Infrastructure (OCI), as well as on-premises with Exadata Cloud@Customer.Starting Price: $123.86 per month -
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neptune.ai
neptune.ai
Neptune.ai is a machine learning operations (MLOps) platform designed to streamline the tracking, organizing, and sharing of experiments and model-building processes. It provides a comprehensive environment for data scientists and machine learning engineers to log, visualize, and compare model training runs, datasets, hyperparameters, and metrics in real-time. Neptune.ai integrates easily with popular machine learning libraries, enabling teams to efficiently manage both research and production workflows. With features that support collaboration, versioning, and experiment reproducibility, Neptune.ai enhances productivity and helps ensure that machine learning projects are transparent and well-documented across their lifecycle.Starting Price: $49 per month -
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dbForge Studio for Oracle
Devart
dbForge Studio for Oracle is a powerful integrated development environment (IDE) which helps Oracle SQL developers to increase PL/SQL coding speed, provides versatile data editing tools for managing in-database and external data. This Oracle IDE allows synchronizing data between different Oracle servers and automating schema change management process during development. dbForge Oracle GUI features powerful functionality wrapped into a smooth management Oracle GUI consistent with Microsoft Visual Studio. Key features: * AI Assistant Integration * PL/SQL Coding Assistant * Database Project * Oracle Database Management * Data Generator * Documenter * Object Manager * Oracle PL/SQL Debugger * Query Builder * Query Profiler * Schema Import/Export * Database Administration * Database Designer * Import/Export Data * Report and Analysis * Find Object You can always find the latest version of the product on the official Devart website.Starting Price: $149.95 -
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Build, run and manage AI models, and optimize decisions at scale across any cloud. IBM Watson Studio empowers you to operationalize AI anywhere as part of IBM Cloud Pak® for Data, the IBM data and AI platform. Unite teams, simplify AI lifecycle management and accelerate time to value with an open, flexible multicloud architecture. Automate AI lifecycles with ModelOps pipelines. Speed data science development with AutoAI. Prepare and build models visually and programmatically. Deploy and run models through one-click integration. Promote AI governance with fair, explainable AI. Drive better business outcomes by optimizing decisions. Use open source frameworks like PyTorch, TensorFlow and scikit-learn. Bring together the development tools including popular IDEs, Jupyter notebooks, JupterLab and CLIs — or languages such as Python, R and Scala. IBM Watson Studio helps you build and scale AI with trust and transparency by automating AI lifecycle management.
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Analance
Ducen
Combining Data Science, Business Intelligence, and Data Management Capabilities in One Integrated, Self-Serve Platform. Analance is a robust, salable end-to-end platform that combines Data Science, Advanced Analytics, Business Intelligence, and Data Management into one integrated self-serve platform. It is built to deliver core analytical processing power to ensure data insights are accessible to everyone, performance remains consistent as the system grows, and business objectives are continuously met within a single platform. Analance is focused on turning quality data into accurate predictions allowing both data scientists and citizen data scientists with point and click pre-built algorithms and an environment for custom coding. Company – Overview Ducen IT helps Business and IT users of Fortune 1000 companies with advanced analytics, business intelligence and data management through its unique end-to-end data science platform called Analance.
