Alternatives to Wolfram Data Science Platform

One source of truth for R packages and Python packages RStudio is the preferred professional data science solution for every group. A Python and R integrated development environment with syntax-highlighting editor, console, and code execution. It also includes tools for workspace management, history, plotting, and plotting. You can publish and distribute data products throughout your organization. One-button deployment of Shiny applications and R Markdown reports, Jupyter Notebooks, etc. To increase reproducibility and reduce the time spent installing and troubleshooting R packages, you can control, organize, and manage your use of them. RStudio is committed to sustainable investment in open-source and free software for data science. RStudio has been certified as a B Corporation. This means that our open-source mission has been codified in our charter. Our professional software products are enterprise-ready and provide a modular platform that allows teams to adopt open-source data sciences at scale.

Composable is an enterprise-grade DataOps platform designed for business users who want to build data-driven products and create data intelligence solutions. It can be used to design data-driven products that leverage disparate data sources, live streams, and event data, regardless of their format or structure. Composable offers a user-friendly, intuitive dataflow visual editor, built-in services that facilitate data engineering, as well as a composable architecture which allows abstraction and integration of any analytical or software approach. It is the best integrated development environment for discovering, managing, transforming, and analysing enterprise data.

Wolfram Alpha introduced a new paradigm of knowledge and answers. Instead of searching the internet, Wolfram Alpha uses a vast array of data, algorithms, and methods to perform dynamic computations. Wolfram Alpha makes expert-level capabilities and knowledge available to a wide range of people, spanning all professions and educational levels. We accept free-form input and serve as a knowledge generator that generates powerful and clear results. Wolfram Alpha is possible today because of a unique set of circumstances, and the singular vision of Stephen Wolfram. The web is a powerful delivery system that allows Wolfram Alpha to be available to a wide audience. This is the first time ever in history that computers have been powerful enough for Wolfram Alpha. This technology was not enough to make Wolfram Alpha possible.

One is the world's first fully cloud-desktop hybrid, integrated computation platform, the ideal entry point to using the full capabilities of the Wolfram technology stack. One is the culmination of 30 years' experience in one easy-to-use, get-started-now product from the world's leading computation company. Wolfram technology can handle any type of computational task, from simple web forms to complex data analytics. The Wolfram Language is the foundation of everything we do. The Wolfram Language was designed for new generations of programmers. It has a wealth of built-in knowledge and algorithms, all accessible automatically through its elegant, unified symbolic language. Scalable for small to large programs, with immediate deployment locally or in the cloud.

Our platform is the only one that offers an end-to–end platform for AI-powered innovation. It can handle everything from data cleansing and structuring to creating and deploying advanced data-science models to infusing advanced analytics algorithms, to infusing Recommendation AI, to deducing outcomes with simple-to-deduce visualization dashboards as well as Explainable AI to track how the outcomes were calculated. Our platform provides a seamless, holistic data science experience. FutureAnalytica offers key features such as a robust Data Lakehouse and an AI Studio. There is also a comprehensive AI Marketplace. You can also get support from a world-class team of data-science experts (on a case-by-case basis). FutureAnalytica will help you save time, effort, and money on your data-science and AI journey. Start discussions with the leadership and then a quick technology assessment within 1-3 days. In 10-18 days, you can create ready-to-integrate AI solutions with FA's fully-automated data science & AI platform.

AIXON is a data-science platform that unites and enriches customer data to help you better understand your audience and run AI models to predict their future actions. To get a complete view of your users, enrich their profiles with external and internal insights. AI brains can quickly find the best pattern to implement your marketing strategies. With insights from AI brains, you can quickly and easily take action via all channels. AIXON provides a 360-degree view to your audience by combining data from multiple sources, such as apps, websites, and CRM. This data can be combined with the users' digital footprints from Appier's cross-screen database to enrich your audience profiles. You can either use existing AI models or create your own to quickly generate powerful predictions. You can create segments based upon user interests or personas. You can also find lookalikes and compare audiences. The platform allows you to predict future actions such as conversions.

BDB is a modern data analysis and BI platform that can dig deep into your data to uncover actionable insights. It can be deployed on-premise or in the cloud. Our unique microservices-based architecture includes elements such as Data Preparation and Predictive, Pipeline, Dashboard designer, and Pipeline. This allows us to offer customized solutions and scalable analysis to different industries. BDB's NLP-based search allows users to access the data power on desktop, tablet, and mobile. BDB is equipped with many data connectors that allow it to connect to a variety of data sources, apps, third-party API's, IoT and social media. It works in real-time. It allows you to connect to RDBMS and Big data, FTP/ SFTP Server flat files, web services, and FTP/ SFTP Server. You can manage unstructured, semi-structured, and structured data. Get started on your journey to advanced analysis today.

Doolytic is a leader in big data discovery, the convergence data discovery, advanced analytics and big data. Doolytic is bringing together BI experts to revolutionize self-service exploration of large data. This will unleash the data scientist in everyone. doolytic is an enterprise solution for native big data discovery. doolytic is built on open-source, scalable technologies that are best-of-breed. Lightening performance on billions and petabytes. Structured, unstructured, and real-time data from all sources. Advanced query capabilities for experts, Integration with R to enable advanced and predictive applications. With Elastic's flexibility, you can search, analyze, and visualize data in real-time from any format or source. You can harness the power of Hadoop data lakes without any latency or concurrency issues. doolytic solves common BI issues and enables big data discovery without clumsy or inefficient workarounds.

The traditional system of bespoke review of data is not keeping pace with the increasing volume and speed of data. Cornerstone AI has created a self-learning AI platform that automatically creates smarter data rules to organize and clean up your data. This will allow you to access better analytical datasets quicker. Your team is spending too much time and effort cleaning and preparing clinical data. Our platform supports clinical trial, EHR, registry and digital health. Our platform scans every table and data point to determine structure and validity. This allows us to organize your tables and correct any errors. A quick data quality report that highlights the most problematic features in your data. Automated or UI based correction of these errors, API access for connecting directly to your data pipeline, as well as an audit trail for all. We don't keep, aggregate, nor resell your data. Your data is yours, and it is used only for you.

All work can be synced, searched and managed across your data science team. Zepl's powerful search allows you to discover and reuse models, code, and other data. Zepl's enterprise collaboration platform allows you to query data from Snowflake or Athena and then build your models in Python. For enhanced interactions with your data, use dynamic forms and pivoting. Zepl creates new containers every time you open your notebook. This ensures that you have the same image each time your models are run. You can invite your team members to join you in a shared space, and they will be able to work together in real-time. Or they can simply leave comments on a notebook. You can share your work with fine-grained access controls. You can allow others to read, edit, run, and share your work. This will facilitate collaboration and distribution. All notebooks can be saved and versioned automatically. An easy-to-use interface allows you to name, manage, roll back, and roll back all versions. You can also export seamlessly into Github.

Two complementary tools, one enterprise-grade platform. Open source KNIME Analytics Platform to create data science. Commercial KNIME Server to produce data science. KNIME Analytics Platform is an open-source software that creates data science. KNIME is intuitive, open, and constantly integrating new developments. It makes data science and designing data science workflows as easy as possible. KNIME Server Enterprise Software is used to facilitate team-based collaboration, automation, and management of data science workflows, as well as the deployment and management of analytical applications and services. Non-experts have access to KNIME WebPortal and REST APIs. Extensions for KNIME Analytics Platform allow you to do more with your data. Some are created and maintained by KNIME, while others are contributed by the community or our trusted partners. Integrations are also available with many open-source projects.

Drag and drop from the many built-in and expandable model libraries allows you to build multidomain, industrial-strength models of your entire system. The Wolfram Language provides a powerful environment for quickly understanding, analyzing and iterating on system designs. Creating insight, innovation, and results. Real-world machines, systems, and networks are not limited to one physical domain. Models can include any combination of interconnected components from any number domains, mimicking real-world topology. Exploration is quick and easy. All values can be accessed from any component of your model with a click. Zoom in on a specific area of interest to see the built-in plot styles. Access the full model equations, and simulation results of your models to perform your own symbolic and numeric computations. Your model analysis will benefit from the full power and flexibility of Wolfram Language.

ZinkML is an open-source data science platform that does not require any coding. It was designed to help organizations leverage data more effectively. Its visual and intuitive interface eliminates the need for extensive programming expertise, making data sciences accessible to a wider range of users. ZinkML streamlines data science from data ingestion, model building, deployment and monitoring. Users can drag and drop components to create complex pipelines, explore the data visually, or build predictive models, all without writing a line of code. The platform offers automated model selection, feature engineering and hyperparameter optimization, which accelerates the model development process. ZinkML also offers robust collaboration features that allow teams to work seamlessly together on data science projects. By democratizing the data science, we empower businesses to get maximum value out of their data and make better decisions.

The Domino Enterprise MLOps 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. By automating time-consuming and tedious DevOps tasks, data scientists can focus on the tasks at hand. 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 has a powerful reproducibility engine, search and knowledge management, and integrated project management. Teams can easily find, reuse, reproduce, and build on any data science work to amplify innovation.

Combine Data Science, Business Intelligence and Data Management Capabilities into One Integrated, Self-Serve Platform. Analance is an end-to-end platform with robust and salable features that combines Data Science and Advanced Analytics, Business Intelligence and Data Management into a single integrated platform. It provides core analytical processing power to ensure that data insights are easily accessible to all, performance remains consistent over time, and business objectives can be met within a single platform. Analance focuses on making quality data into accurate predictions. It provides both citizen data scientists and data scientists with pre-built algorithms as well as an environment for custom programming. Company - Overview Ducen IT provides advanced analytics, business intelligence, and data management to Fortune 1000 companies through its unique data science platform Analance.

Machine learning can be accelerated from research to production using a consistent experience that is built for your traditional platform. Cloudera Data Science Workbench, (CDSW), offers a self-service experience that data scientists will love. It allows you to access Python, R, Scala, and more directly from your web browser. You can download and test the latest frameworks and libraries in project environments that look exactly like your laptop. Cloudera Data Science Workbench allows you to connect to CDH and HDP as well as to the systems that your data science teams depend on for analysis. Cloudera Data Science Workbench allows data scientists to manage their own analytics pipelines. It includes built-in monitoring, scheduling, email alerting, and monitoring. Rapidly create and prototype machine learning projects, and then easily deploy them to production.

An end-to-end solution gives you all the tools your data science team needs to scale your machine learning development, from research to production. cnvrg.io, the world's leading data science platform for MLOps (model management) is a leader in creating cutting-edge machine-learning development solutions that allow you to build high-impact models in half the time. In a collaborative and clear machine learning management environment, bridge science and engineering teams. Use interactive workspaces, dashboards and model repositories to communicate and reproduce results. You should be less concerned about technical complexity and more focused on creating high-impact ML models. The Cnvrg.io container based infrastructure simplifies engineering heavy tasks such as tracking, monitoring and configuration, compute resource management, server infrastructure, feature extraction, model deployment, and serving infrastructure.

Accelerate scientific discovery, empower your R&D team and use harmonized data in cloud to accelerate your R&D. The Tetra R&D Data Cloud is the only cloud-native data platform for global pharmaceutical companies. It combines the power of the largest Life Sciences integrations network and deep domain knowledge to provide a future-proof solution to harness the power of your most important asset, R&D data. The cloud covers the entire life-cycle of your R&D data: from acquisition, harmonization, engineering, downstream analysis, and native support for state–of-the–art data science tools. Pre-built integrations allow for easy connection to instruments, informatics and analytics applications, ELN/LIMSs, CRO/CDMOs, and other vendors. Data acquisition, management, harmonization, integration/engineering and data science enablement in one single platform.

Data science platform that increases productivity and has unparalleled capabilities. Create and evaluate machine learning (ML), models of higher quality. Easy deployment of ML models can help increase business flexibility and enable enterprise-trusted data work faster. Cloud-based platforms can be used to uncover new business insights. Iterative processes are necessary to build a machine-learning model. This ebook will explain how machine learning models are constructed and break down the process. Use notebooks to build and test machine learning algorithms. AutoML will show you the results of data science. It is easier and faster to create high-quality models. Automated machine-learning capabilities quickly analyze the data and recommend the best data features and algorithms. Automated machine learning also tunes the model and explains its results.

Decision intelligence aims to empower employees with the ability to make faster, more informed decisions that will allow them to take corrective steps, capitalize on opportunities, and drive innovation. The data and analytics platform that is purpose-built to help enterprises make better, faster decisions. A new type of engine drives it. Streamlining the entire analysis workflow. One platform for all data, any person, and any analytics needs. This is the future for intelligent decisions. This new platform combines data preparation, data science, and business analytics into one integrated platform. Streamline all aspects of decision-making. Everything from discovery to publishing to modeling is interconnected (and easy-to-use). It can be run at hyper-scale to support any data-driven decision. Advanced data science is available for all business needs, from the C-Suite to frontline.

A fully-featured machine learning platform empowers enterprises to conduct real data science at scale and speed. You can spend less time managing infrastructure and tools so that you can concentrate on building machine learning applications to propel your business forward. Anaconda Enterprise removes the hassle from ML operations and puts open-source innovation at the fingertips. It provides the foundation for serious machine learning and data science production without locking you into any specific models, templates, workflows, or models. AE allows data scientists and software developers to work together to create, test, debug and deploy models using their preferred languages. AE gives developers and data scientists access to both notebooks as well as IDEs, allowing them to work more efficiently together. They can also choose between preconfigured projects and example projects. AE projects can be easily moved from one environment to the next by being automatically packaged.

A data science platform for life scientists. Transform your microbiome research into useful applications Get new, safe and effective products on the market faster. Combine the right combination of data science and collaboration tools to make rapid progress in cancer therapy. Effective digital technology solutions can improve crop productivity and accelerate research. Import both small and large data. You can either use our templates or create your own schema. Our format inference algorithm synthesizes the parsing functions and allows you to override if necessary, without any coding. For bulk imports, you can use our interactive import screens and CLI. Your data is more than just bits. Solvuu automatically calculates summary statistics and generates rich interactive visualizations. You can explore and gain insight into your data instantly; you can even slice and dice it as needed.

Bitfount provides a platform for distributed data sciences. We enable deep data collaborations that do not require data sharing. Distributed data science connects algorithms to data and not the other way around. In minutes, you can set up a federated privacy protecting analytics and machine learning network. This will allow your team to focus on innovation and insights instead of bureaucracy. Although your data team is equipped with the skills to solve your most difficult problems and innovating, they are hindered by data access barriers. Are you having trouble accessing your data? Are compliance processes taking too much time? Bitfount offers a better way for data experts to be unleashed. Connect siloed or multi-cloud data sources while protecting privacy and commercial sensitivity. No expensive, time-consuming data lift-and-shift. Useage-based access control to ensure that teams only do the analysis you need, with the data you want. Transfer access control management to the teams that have the data.

Cloud-based Data Science Platform that delivers intelligently curated, cleansed and ready to consume data. Before they can begin to add value, firms face significant challenges and resource constraints. Data is ingested and then cleaned, stored, accessed and only then analyzed. The value comes from the analysis. Our solution allows our clients to focus on their core business activities and not on the expensive and resource-intensive data lifecycle. We'll take care of it. Cloud-native platform that enables real-time streaming analytics. INQDATA can deliver historical and real-time information without the need for complex infrastructure.

Datalore is a platform for collaborative data science and analytics that aims to improve the entire analytics workflow and make working with data more enjoyable for both data scientists as well as data-savvy business teams. Datalore is a collaborative platform that focuses on data teams workflow. It offers technical-savvy business users the opportunity to work with data teams using no-code and low-code, as well as the power of Jupyter Notebooks. Datalore allows business users to perform analytic self-service. They can work with data using SQL or no-code cells, create reports, and dive deep into data. It allows core data teams to focus on simpler tasks. Datalore allows data scientists and analysts to share their results with ML Engineers. You can share your code with ML Engineers on powerful CPUs and GPUs, and you can collaborate with your colleagues in real time.

Spend less time prepping your data and more time analysing it. You can create better-looking and more accurate reports by centralizing all data gathering, analytics, and data science into one interface that is accessible to everyone within the organization. No matter where your data is located, import it all. Rational BI provides all the tools you need to create scheduled reports from Excel files, cross-reference data between Excel files and databases, or transform your data into SQL queryable database tables. Find the hidden signals in your data and make it accessible immediately to your competitors. Business intelligence can help you increase your analytics capabilities and make it easier to find the most up-to-date data. It also makes it easy for data scientists and casual users to analyze it.

With open-source Metaflow, you can design and develop data-intensive projects. You can scale them up and deploy them on the fully managed Outerbounds platform. All your data science and ML projects can be managed from one platform. Access data securely from existing data warehouses. A cluster that is optimized for cost and scale can be used to compute. 24/7 managed orchestration of production workflows. Results can be used to power any application. Your engineers will give your data scientists superpowers. Outerbounds Platform enables data scientists to quickly develop, experiment at scale, then deploy to production with confidence. All within the boundaries of your engineers' policies and processes, all running on your cloud account, fully supported by us. Security is part of our DNA, not at its perimeter. Through multiple layers of security, the platform adapts to your policies. Centralized authentication, a strict permission limit, and granular task execution role.

Easily extract, transform, manage & process CAD data, FE data, CFD and test results. Create automatic data pipelines to support machine learning, deep learning, and ROM. Data science barriers can be removed without coding. Key Ward's platform, the first engineering no-code end-to-end solution, redefines how engineers work with their data. Our software allows engineers to handle multi-source data with ease, extract direct value using our built-in advanced analytical tools, and build custom machine and deep learning model with just a few clicks. Automatically centralize, update and extract your multi-source data, then sort, clean and prepare it for analysis, machine and/or deep learning. Use our advanced analytics tools to correlate, identify patterns, and find dependencies in your experimental & simulator data.

Predictive modeling with Machine Learning and Explainable Ai. FICO®, Analytics Workbench™, is a comprehensive suite of state-of the-art analytic authoring software that empowers companies to make better business decisions throughout the customer lifecycle. Data scientists can use it to build superior decisioning abilities using a variety of predictive data modeling tools, including the most recent machine learning (ML), and explainable AI (xAI) methods. FICO's innovative intellectual property enables us to combine the best of open-source data science and machine learning to provide world-class analytical capabilities to find, combine, and operationalize data predictive signals. Analytics Workbench is built upon the FICO®, leading platform that allows for new predictive models and strategies to easily be put into production.

HyperCube is the platform that data scientists use to quickly discover hidden insights, no matter what your business needs. Use your business data to make an impact. Unlock understanding, uncover untapped opportunities, make predictions, and avoid risk before they happen. HyperCube turns huge amounts of data into actionable insights. HyperCube is for you, whether you are a beginner or an expert in machine learning. It is the data science Swiss Army knife. It combines proprietary and open-source code to deliver a wide variety of data analysis features right out of the box. Or, it can be customized for your business. We are constantly improving our technology to deliver the best possible results. Choose from apps, DaaS (data-as-a service) or vertical market solutions.

Data analysts, engineers, scientists, and other scientists can be brought together. Automate self-service analytics and machine learning operations. Get results today, build for tomorrow. Dataiku DSS is a collaborative data science platform that allows data scientists, engineers, and data analysts to create, prototype, build, then deliver their data products more efficiently. Use notebooks (Python, R, Spark, Scala, Hive, etc.) You can also use a drag-and-drop visual interface or Python, R, Spark, Scala, Hive notebooks at every step of the predictive dataflow prototyping procedure - from wrangling to analysis and modeling. Visually profile the data at each stage of the analysis. Interactively explore your data and chart it using 25+ built in charts. Use 80+ built-in functions to prepare, enrich, blend, clean, and clean your data. Make use of Machine Learning technologies such as Scikit-Learn (MLlib), TensorFlow and Keras. In a visual UI. You can build and optimize models in Python or R, and integrate any external library of ML through code APIs.

Snowflake®, a cloud data platform and enterprise-grade architecture, allows you to securely store and use your data in the cloud. Drag-and-drop visual workflow design and built-in ETL to connect, clean and transform data from 250+ sources. You can generate actionable insights and insights from your data using the latest Search and AI-driven technology. Our AI/ML environments can be used to build, tune, and deploy models for predictive analytics or forecasting. Our AI/ML environments are available to help you take your data to new heights. The PurpleCube Data Science module allows you to create, train, tune, and deploy AI models for forecasting and predictive analysis. PurpleCube Analytics allows you to create BI visualizations, search your data with natural language and use AI-driven insights and smart recommendations to provide answers to questions that you didn't know to ask.

You can build, run, and manage AI models and optimize decisions across any cloud. IBM Watson Studio allows you to deploy AI anywhere with IBM Cloud Pak®, the IBM data and AI platform. Open, flexible, multicloud architecture allows you to unite teams, simplify the AI lifecycle management, and accelerate time-to-value. ModelOps pipelines automate the AI lifecycle. AutoAI accelerates data science development. AutoAI allows you to create and programmatically build models. One-click integration allows you to deploy and run models. Promoting AI governance through fair and explicable AI. Optimizing decisions can improve business results. Open source frameworks such as PyTorch and TensorFlow can be used, as well as scikit-learn. You can combine the development tools, including popular IDEs and Jupyter notebooks. JupterLab and CLIs. This includes languages like Python, R, and Scala. IBM Watson Studio automates the management of the AI lifecycle to help you build and scale AI with trust.

Einblick is the fastest and most collaborative method to analyze data, make predictions, and then deploy data apps. Our canvases dramatically change the data science workflows. They make it easier to clean, manipulate, and explore data in a new interface. Our platform is the only one that allows you to collaborate with your entire team in real-time. Let's make decision-making a team activity. Don't waste your time tuning models manually. AutoML's goal is to help you make clear predictions and identify key drivers quickly. Einblick combines common analytics functionality into simple-to-use operators that allow you to abstract repetitive tasks and get answers faster. Connect your data source to Snowflake, S3 buckets, or CSV files and you'll be able to get answers in minutes. You can create a list of customers that have been churned or are currently churned, and share everything you know about them. Find out the key factors that caused churn and how at-risk each customer is.

Visplore makes the analysis of large, dirty time series data intuitive and extremely efficient. For process experts, R&D engineers, quality managers, industry consultants, and everyone who has spent a lot of time on the tedious preparation of complex measurement data. Knowing your data is the fundament of unlocking its value. Visplore offers ready-to-use tools to understand correlations, patterns, trends and much more, faster than ever. Cleansing and annotating make the difference between valuable and useless data. In Visplore, you deal with dirty data like outliers, anomalies and process changes as easily as using a drawing program. Integrations with Python, R, Matlab and many other sources makes workflow integration straightforward. And all of that at a performance that is still fun even with millions of data records, and allows for unexpectedly creative analyses.

Streamlit. The fastest way to create and share data apps. In minutes, turn data scripts into sharable Web apps All in Python. All this for free. No need for front-end experience. Streamlit combines three simple concepts. Use Python scripting. Our API is simple and allows you to create an app in just a few lines of code. You can then see the app update automatically as you save your source file. You can also use interaction. Declaring a variable is the same thing as adding a widget. You don't need to create a backend, define routes or handle HTTP requests. You can deploy your app instantly. Streamlit's platform for sharing allows you to easily share, manage and collaborate on your apps. A framework that allows you to create powerful apps. Face-GAN explorer. App that generates faces matching selected attributes using Shaobo Guan’s TL-GAN project, TensorFlow and NVIDIA’s PG-GAN. Real time object detection. A browser that displays images from the Udacity self driving-car dataset.

Darwin is an automated machine-learning product that allows your data science and business analysis teams to quickly move from data to meaningful results. Darwin assists organizations in scaling the adoption of data science across their teams and the implementation machine learning applications across operations to become data-driven enterprises.

DotData allows your business to concentrate on the results of your AI/ML applications and not the hassles of the data science process. Automate full-cycle AI & ML pipeline deployment in minutes. Continuous deployment allows you to update your data in real-time. Feature engineering automation reduces the time it takes to complete data science projects. Data science automation automates the discovery of unknowns in your business. Data science automation is a labor-intensive and cumbersome process that uses data science to create and deploy machine learning and AI models. Automate repetitive and time-consuming tasks that are the banes of data science work. This will reduce the development times for AI from months to days.

Runlve is at the forefront of the AI revolution. We provide data science, MLOps and data & models management to empower our community and customers with AI capabilities that will propel their projects forward.

We provide the computational paradigm. The Wolfram Language gives you access to computing power at an unprecedented level. It does this by leveraging built-in computational intelligence that is based on a variety of algorithms and real-world information, which has been carefully accumulated over three decades. The Wolfram Language can scale for small and large programs, and it can be deployed on-premises or in the cloud. The Wolfram Language is based on clear principles and a unified symbolic framework. It is now the most productive programming language in the world and the first real computational communication language for humans or AI.

The RAPIDS software library, which is built on CUDAX AI, allows you to run end-to-end data science pipelines and analytics entirely on GPUs. It uses NVIDIA®, CUDA®, primitives for low level compute optimization. However, it exposes GPU parallelism through Python interfaces and high-bandwidth memories speed through user-friendly Python interfaces. RAPIDS also focuses its attention on data preparation tasks that are common for data science and analytics. This includes a familiar DataFrame API, which integrates with a variety machine learning algorithms for pipeline accelerations without having to pay serialization fees. RAPIDS supports multi-node, multiple-GPU deployments. This allows for greatly accelerated processing and training with larger datasets. You can accelerate your Python data science toolchain by making minimal code changes and learning no new tools. Machine learning models can be improved by being more accurate and deploying them faster.

Data scientists are able to build, improve, or operate end-to–end workflows independently. This allows them to deliver data science projects that are successful. Metaflow can be used with your favorite data science libraries such as SciKit Learn or Tensorflow. You can write your models in idiomatic Python codes with little to no learning. Metaflow also supports R language. Metaflow allows you to design your workflow, scale it, and then deploy it to production. It automatically tracks and versions all your data and experiments. It allows you to easily inspect the results in notebooks. Metaflow comes pre-installed with the tutorials so it's easy to get started. Metaflow allows you to make duplicates of all tutorials in your current directory by using the command line interface.

Kedro provides the foundation for clean, data-driven code. It applies concepts from software engineering to machine-learning projects. Kedro projects provide scaffolding for complex machine-learning and data pipelines. Spend less time on "plumbing", and instead focus on solving new problems. Kedro standardizes the way data science code is written and ensures that teams can collaborate easily to solve problems. You can make a seamless transition between development and production by using exploratory code. This code can be converted into reproducible, maintainable and modular experiments. A series of lightweight connectors are used to save and upload data across a variety of file formats and file systems.

All enterprise's AI/ML efforts can have a consistent and positive impact. Data scientists deserve a solution that makes their experiments reproducible, each asset discoverable, and simplifies knowledge transfer. Managers deserve a dedicated data science solution. To automate reporting, secure knowledge, and simplify reviews and other processes. Vectice's mission is to revolutionize how data science teams collaborate and work together. All organizations should see consistent and positive AI/ML impacts. Vectice is the first automated knowledge system that is data science-aware, actionable, and compatible with the tools used by data scientists. Vectice automatically captures all assets created by AI/ML teams, such as data, code, notebooks and models, or runs. It then automatically generates documentation, from business requirements to production deployments.

Easy extract, transform, load (ETL), data for data science or analytics. Code-free data flows can be created into data lakes or data marts. Oracle's extensive portfolio of integration solutions. The intuitive user interface allows you to set up integration parameters and automate data mapping from sources and targets. To shape your data, you can use one of the many out-of-the box operators such as a join or aggregate. You can centrally manage your processes and use parameters to override certain configuration values at runtime. Users can view and interact with their data to validate their processes. You can increase productivity and fine-tune data flow on the fly without waiting for executions to complete. Reduce maintenance complexity and avoid broken integration flows as data schemas change.

With a fully automated cloud infrastructure, experts can explore data and write stable codes at the same time. Zerve’s data science environment gives data scientists and ML teams a unified workspace to explore, collaborate and build data science & AI project like never before. Zerve provides true language interoperability. Users can use Python, R SQL or Markdown in the same canvas and connect these code blocks. Zerve offers unlimited parallelization, allowing for code blocks and containers to run in parallel at any stage of development. Analysis artifacts can be automatically serialized, stored and preserved. This allows you to change a step without having to rerun previous steps. Selecting compute resources and memory in a fine-grained manner for complex data transformation.

IBM SPSS Modeler, a leading visual data-science and machine-learning (ML) solution, is designed to help enterprises accelerate their time to value through the automation of operational tasks by data scientists. It is used by organizations around the world for data preparation, discovery, predictive analytics and model management and deployment. ML is also used to monetize data assets. IBM SPSS Modeler transforms data in the best possible format for accurate predictive modeling. You can now analyze data in just a few clicks, identify fixes, screen fields out and derive new characteristics. IBM SPSS Modeler uses its powerful graphics engine to help you bring your insights to life. The smart chart recommender will select the best chart from dozens of options to share your insights.

We create, manage, and operate predictive software services that are based on machine learning and data science. Software service for large ecommerce businesses and retail chains that uses machine learning to optimize stock distribution between warehouses and retail stores. A personalized product recommendation tool for ecommerce websites that uses real-time Bayes nets in order to show relevant products to e-shop customers. Software service that automatically predicts product price movements in order to increase profit. It uses statistical price and demand elastic models. API to calculate optimal paths for batch picking optimization in a retailer’s warehouse. This API is built using shortest path graph algorithms.

Analytically driven decision flows can be created, embedded and managed at scale in batch or real-time. SAS Data Science Programming allows data scientists who prefer to work only in programmatic mode to access SAS analytical capabilities at every stage of the analytics lifecycle, including data discovery and deployment. Visualize and discover relationships in your data. You can create and share interactive dashboards and reports, and use self service analytics to quickly assess possible outcomes to make data-driven, smarter decisions. This solution runs in SAS®, Viya®. It allows you to explore data and create or adjust predictive analytical models. Analysts, statisticians, data scientists, and analysts can work together to refine and refine models for each group or segment, allowing them to make informed decisions. A comprehensive visual interface allows you to solve complex analytical problems. It handles all aspects of the analytics lifecycle.

Accelerate and simplify IoT data extraction, create AI for the shop floor, and visualize KPIs. Manage decentralized, compact data pods. Each data pod is completely autonomous and includes infrastructure for powerful analytics. Flexible storage capacity allows you to create multiple pods with different sizes. In a seamless data journey, you can collect, analyze, visualize, and visualize data. You can collect raw data from multiple sources, such as IoT routers or the web. Instantly generate reports and create custom infographics from your browser. Combine the power of VS Code, Observable and TablePlus to create interactive data science workbooks. You can see the current and past processes in real time and automate package loads up to reporting.