Alternatives to Posit

IBM® SPSS® Statistics software is used by a variety of customers to solve industry-specific business issues to drive quality decision-making. The IBM® SPSS® software platform offers advanced statistical analysis, a vast library of machine learning algorithms, text analysis, open-source extensibility, integration with big data and seamless deployment into applications. Its ease of use, flexibility and scalability make SPSS accessible to users of all skill levels. What’s more, it’s suitable for projects of all sizes and levels of complexity, and can help you find new opportunities, improve efficiency and minimize risk.

K.Explorer is an AI system that creates better software faster, cheaper, and more efficiently. A coding assistant that increases developer productivity. An AI pair programmer that suggests code completions and complete function bodies as you type. You can also search the engine for help. It is an AI-powered Code Assistant that has been trained on millions of lines of code from private corporations, as well as billions of lines of open-source code for general purposes. Natural Language allows programmers to receive guidance and tell a text story about what code they are writing.

Domo puts data to work for everyone so they can multiply their impact on the business. Underpinned by a secure data foundation, our cloud-native data experience platform makes data visible and actionable with user-friendly dashboards and apps. Domo helps companies optimize critical business processes at scale and in record time to spark bold curiosity that powers exponential business results.

DSVMs are Azure Virtual Machine Images that have been pre-configured, configured, and tested with many popular tools that are used for data analytics and machine learning. A consistent setup across the team promotes collaboration, Azure scale, management, Near-Zero Setup and full cloud-based desktop to support data science. For one to three classroom scenarios or online courses, it is easy and quick to set up. Analytics can be run on all Azure hardware configurations, with both vertical and horizontal scaling. Only pay for what you use and when you use it. Pre-configured Deep Learning tools are readily available in GPU clusters. To make it easy to get started with the various tools and capabilities, such as Neural Networks (PYTorch and Tensorflow), templates and examples are available on the VMs. ), Data Wrangling (R, Python, Julia and SQL Server).

Our namesake product, Minitab Statistical Software, leads the way in data analysis with the power to visualize, analyze and harness your data to gain insights and solve your toughest challenges. Access trusted, proven and modern analytics combined with dynamic visualizations to empower you and your decisions. The latest version of Minitab Statistical Software includes access to Minitab on the cloud so you can analyze from anywhere, and Graph Builder, our new interactive tool to instantly create multiple graph options at once. Minitab offers modules for Predictive Analytics and Healthcare to boost your analytics even further. Available in 8 languages: English, Chinese, French, German, Japanese, Korean, Spanish, and Portuguese. For 50 years, Minitab has helped thousands of companies and institutions spot trends, solve problems, and discover valuable insights in their data through our comprehensive, best-in-class suite of data analysis and process improvement tools.

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.

Open-source web application, the Jupyter Notebook, allows you to create and share documents with live code, equations, and visualizations. Data cleaning and transformation, numerical modeling, statistical modeling and data visualization are just a few of the many uses.

SAS Visual Statistics allows multiple users to interactively explore data and then create and refine predictive models. Your statisticians and data scientists can use the most appropriate analytical modeling techniques to analyze your observations at a fine level. What will you get? The result? You can quickly build and refine models to target specific segments or groups, and run multiple scenarios simultaneously. To get better results, you can ask more "what-if" questions. You can also use an automatically generated score code to put your results into practice. Multiple users can interact with data visually. They can add, change, or remove outliers. You can instantly see how changes affect the predictive power of your model and make adjustments quickly. Data science teams have the freedom to work in the language they prefer, so they can make the most of their talents. SAS Visual Statistics combines all analytical assets.

MatDeck is a universal technical software that can be used for mathematics, science, engineering, chemistry, programming, databases, and many other purposes. Our software includes a complete Python IDE, thousands of mathematical functions, a drag-and-drop GUI Designer, and many visualization tools. All this is embedded in a cutting-edge, live document that provides a professional computing environment at a low cost.

Automated best practices will increase your open source security posture. This workflow combines security and development teams into one seamless process. The cloud-native security platform reduces risks and protects revenue without slowing down developers. The dependency firewall blocks malicious open source before it reaches developers and infrastructure. This protects data, assets and company reputation. Our policy engine analyzes threat signals, such as known vulnerabilities, license information and customer-defined rules. It is vital to have an understanding of the open-source components used in applications in order to avoid exploitable vulnerabilities. Dashboard reporting and Software Composition Analysis (SCA), provide stakeholders with a comprehensive overview of the current situation. Find out when new open-source licences are added to the codebase. Automated tracking of license compliance issues and restriction of unlicensed packages.

Machine Learning and Predictive Analytics Platform. Advanced artificial intelligence is a pre-built platform for machine learning and big-data analytics that can enhance data-driven decision making. OpenText Magellan makes predictive analytics easy to use and provides flexible data visualizations that maximize business intelligence. Artificial intelligence software reduces the need to manually process large amounts of data. It presents valuable business insights in a manner that is easily accessible and relevant to the organization's most important objectives. Organizations can enhance business processes by using a curated combination of capabilities such as predictive modeling, data discovery tools and data mining techniques. IoT data analytics is another way to use data to improve decision-making based on real business intelligence.

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.

The Lightning-Smart PHPIDE. PhpStorm fully understands your code. PhpStorm works well with Symfony and Laravel, Drupal. WordPress, Zend Framework. Magento, Joomla!. CakePHP. Yii. And other frameworks. The editor 'gets' your code, and can help you understand its structure. It supports all PHP language features for both modern and legacy projects. It offers the best code completion, refactorings and on-the-fly error detection. You can make the most of cutting-edge front-end technologies such as HTML 5, CSS, Sass, Less, Stylus, CoffeeScript, TypeScript, Emmet, JavaScript, Emmet, JavaScript, and JavaScript. There are refactorings, debugging, unit testing, and refactorings available. Live Edit allows you to see the changes in your browser right away. Many routine tasks can be performed right from the IDE thanks to the Version Control Systems integration. This includes remote deployment, databases/SQL and command-line tools such as Docker, Composer and REST Client.

With a single keystroke, switch between editor and command modes. Use the arrow keys to navigate between cells. All the Jupyter shortcuts are available. Fully interactive outputs are available right under the cell. Editing code cells is easy with smart code completion, quick error checking and quick fixes, and easy navigation. You can connect to remote JupyterHub or JupyterLab servers from the IDE. Interactively run Python scripts and arbitrary expressions in a Python Console. You can see the outputs and the state variables in real time. Split Python scripts into code cells using the #%% separator, and run them individually in a Jupyter notebook. Interactive controls allow you to browse DataFrames or visualizations in real time. All popular Python scientific libraries, including Plotly and Altair, ipywidgets and others, are supported.

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.

IBM Analytics for Apache Spark allows data scientists to ask more difficult questions and deliver business value quicker with a flexible, integrated Spark service. It's a simple-to-use, managed service that is always on and doesn't require any long-term commitment. You can start exploring immediately. You can access the power of Apache Spark without locking yourself in, thanks to IBM's open-source commitment as well as decades of enterprise experience. With Notebooks as a connector, coding and analytics are faster and easier with managed Spark services. This allows you to spend more time on innovation and delivery. You can access the power of machine learning libraries through managed Apache Spark services without having to manage a Sparkcluster by yourself.

Coder offers self-hosted cloud development environments, provisioned as code and ready for developers from day one. Favored by enterprises, Coder is open source and can be deployed air-gapped on-premise or in your cloud, ensuring powerful infrastructure access without sacrificing governance. By shifting local development and source code to a centralized infrastructure, Coder allows developers to access their remote environments via their preferred desktop or web-based IDE. This approach enhances developer experience, productivity, and security. With Coder’s ephemeral development environments, provisioned as code from pre-defined templates, developers can instantly create new workspaces. This streamlines the process, eliminating the need to deal with local dependency versioning issues or lengthy security approvals. Coder enables developers to onboard or switch projects in a matter of minutes.

Quadratic allows your team to collaborate on data analysis and deliver faster results. You're already familiar with spreadsheets, but this is the first time you have had so much power. Quadratic is fluent in Formulas, Python and SQL (JavaScript & SQL coming soon). Use the language that you and your team are already familiar with. Single-line formulas can be difficult to read. Quadratic allows you to expand your recipes as many times as you want. Quadratic comes with Python library support. Bring the latest open source tools to your spreadsheet. The last line of the code is returned to your spreadsheet. By default, raw values, 1/2D arrays and Pandas DataFrames can be used. Quadratic updates its cells automatically when data is pulled or fetched from an external API. Zoom out to see the big picture and zoom in for the details. Arrange your data and navigate it the way you see it in your mind, not as a tool would have it.

Project Jupyter is an open-source project that develops open-standards software and services for interactive computing in dozens of programming languages. JupyterLab provides a web-based interactive environment for Jupyter notebooks and code. JupyterLab's user interface is flexible. You can configure and arrange it to support a variety of workflows in data science and scientific computing. JupyterLab can be extended and modified to add new components or integrate with existing ones. Open-source web application, Jupyter Notebook, allows you to create and share documents with live code, equations and visualizations. Data cleaning and transformation, numerical modeling, statistical modeling and data visualization are just a few of the many uses. Jupyter supports more than 40 programming languages, including Python and R, Julia, Scala, and Scala.

Stata is a comprehensive, integrated software package that can handle all aspects of data science: data manipulation, visualization and statistics, as well as automated reporting. Stata is quick and accurate. The extensive graphical interface makes it easy to use, but is also fully programable. Stata's menus, dialogs and buttons give you the best of both worlds. All Stata's data management, statistical, and graphical features are easy to access by dragging and dropping or point-and-click. To quickly execute commands, you can use Stata's intuitive command syntax. You can log all actions and results, regardless of whether you use the menus or dialogs. This will ensure reproducibility and integrity in your analysis. Stata also offers complete command-line programming and programming capabilities, including a full matrix language. All the commands that Stata ships with are available to you, whether you want to create new Stata commands or script your analysis.

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.

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.

You can build and run powerful AI and engineering apps in just 5 minutes after downloading Flojoy Studio. No coding skills are required. Engineers use Flojoy Studio for streaming measurements from robotics and microcontrollers to Flojoy Cloud. Once in Flojoy Cloud this research data can then be analyzed, archived and downloaded by team members. Flojoy is a de facto resource for open source instrument control in Python. Flojoy's mission is to provide first-class Python support for every major motion platform, including robotic arms, steppermotors, servos and linear actuators.

MATLAB®, a combination of a desktop environment for iterative analysis, design processes, and a programming language that expresses matrix or array mathematics directly, is MATLAB®. It also includes the Live Editor, which allows you to create scripts that combine output, code, and formatted text in an executable notebook. MATLAB toolboxes have been professionally developed, tested and documented. MATLAB apps allow you to see how different algorithms interact with your data. You can repeat the process until you get the results you desire. Then, MATLAB will automatically generate a program to replicate or automate your work. With minor code changes, you can scale your analyses to run on GPUs, clusters, and clouds. You don't need to rewrite any code or learn big-data programming and other out-of-memory methods. Convert MATLAB algorithms automatically to C/C++ and HDL to run on your embedded processor/FPGA/ASIC. Simulink works with MATLAB to support Model-Based Design.

Appsilon offers innovative data analytics, machine-learning, and managed services for Fortune 500 companies, NGOs and non-profit organizations. We offer the most advanced R Shiny applications in the world, and have the unique ability to quickly develop and scale enterprise Shiny dashboards. Our machine learning frameworks enable us to deliver prototypes for Computer Vision, NLP and fraud detection in as little as one working week. We are determined to make a positive difference in the world. Our AI For Good Initiative allows us to contribute our expertise to projects that help preserve human life and conserve animal populations around the world. Our team has been working to reduce poaching in Africa using computer vision, provide satellite imagery analysis to assess damage after natural catastrophes, and develop tools to aid with COVID-19 risk assessments. Appsilon is also an innovator in open-source.

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.

Alteryx AI Platform will help you enter a new age of analytics. Empower your organization through automated data preparation, AI powered analytics, and accessible machine learning - all with embedded governance. Welcome to a future of data-driven decision making for every user, team and step. Empower your team with an intuitive, easy-to-use user experience that allows everyone to create analytical solutions that improve productivity and efficiency. Create an analytics culture using an end-toend cloud analytics platform. Data can be transformed into insights through self-service data preparation, machine learning and AI generated insights. Security standards and certifications are the best way to reduce risk and ensure that your data is protected. Open API standards allow you to connect with your data and applications.

Access, explore, and prepare data while discovering new patterns and trends. SAS Visual Data Science allows you to create and share interactive visualizations and reports using a single interface. It uses machine learning, text analysis, and econometrics to improve forecasting and optimization. Additionally, it registers SAS and open source models within projects and as standalone models. Visualize your data and find relevant relationships. You can create and share interactive dashboards and reports, and use self service analytics to quickly assess possible outcomes for better, data-driven 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.

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.

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.

SAS®, Viya®, data science offerings offer a comprehensive, scalable analytical environment that is quick and easy to use, allowing you to meet diverse business requirements. Automatically generated insights allow you to identify the most commonly used variables across all models, the most significant variables selected across models, and assess results for all models. Natural language generation capabilities allow you to create project summaries in plain language. This makes it easy to interpret reports. Analytics team members can add project notes and comments to the insights report to facilitate communication between team members. SAS allows you to embed open source code into an analysis and call open-source algorithms seamlessly within its environment. This allows for collaboration within your organization as users can program in the language they prefer. SAS Deep Learning with Python (DLPy) is also available on GitHub.

SonarCloud automatically analyzes and decorates pull request branches to maximize your throughput. To prevent undefined behavior from affecting end-users, catch tricky bugs. Security Hotspots will help you identify and fix vulnerabilities that could compromise your app. It takes just a few mouse clicks to get your code up and running. Instant access to the most recent features and enhancements. Project dashboards keep stakeholders and teams informed about code quality and releasability. Show your communities that you care about awesome by displaying project badges. Your entire stack should be concerned about code quality and security. We cover 24 languages, including C++, Java, Python, and many other. Transparency is a good thing and the trend is growing. Join the fun! Open-source projects are completely free!

Helix Swarm is a web-based and free code review tool for Helix Core. Helix Swarm helps you keep your projects moving at a rapid pace while adhering to your organizational processes. It allows teams to work together for more efficient code reviews. This code review tool allows contributors to share files, comment, suggest tasks and vote up or down. Helix Swarm simplifies peer code review. This will allow you to ensure that the right code is reviewed by the right people, on time. This will make your code reviews more efficient and improve the quality of your next release.

High quality code must be sent. Code can be reviewed, discussed, changed, shared knowledge, and identified defects in SVN, Git and Mercurial, CVS and Perforce. Formal, workflow-based, and quick code reviews can be created. You can assign reviewers from your entire team. Any code review can be turned into a threaded discussion. You can comment on specific source lines, files or entire changesets. Unified views of your code activity allow you to focus on the important things. You can improve code quality by knowing which parts of your codebase have not received sufficient review. A quick overview of review status and who might be preventing reviews. You can access a complete audit trail that includes all code review details down to the history for a particular review. You can customize your Jira Software workflow so that you know when to stop if there is an open review. Upgrade your workflow with Jira Software and Bitbucket Server. Bamboo, Bitbucket Server and hundreds of other developer tools are available.

Develop healthier code. Improve code quality and workflow. Codecov offers a comprehensive suite of tools that allow you to group, merge and archive coverage reports, as well as compare them. Open source. Plans starting at $10/user per month. Ruby, Python and C++ as well as Javascript are all available. All CI products and workflows can be integrated easily. No setup is required. Automatic report merging for all CI languages and languages into one report. You can get custom statuses for any group of coverage metrics. You can review coverage reports by folder, project, and type (unit tests or integration tests). You can comment the detailed report directly in your pull request. Codecov is SOC 2 Type II Certified. This means that Codecov has been audited by a third party and attested to our security practices.

It allows communities to come together, regardless of their choice in tools, by making it easy for them to share code, bug report, translations, and ideas between projects. Launchpad allows you to share bug reports, statuses and comments across projects. You can also share bug data with other trackers like Bugzilla or Trac. You can also find everything you need in a bug tracker, including web, email, and API interfaces, links between bugs, fixes, team-based delegation, and more. Once they are ready, they can upload the branch to Launchpad and submit it for merging into your trunk. Code review is available via web and email. This allows you to share your thoughts and approve or deny the merge. Launchpad makes it easy to translate. Translators have a simple web interface that offers suggestions from a library with more than 16,000,000 strings.

The first comprehensive security solution to protect code within an enterprise. Software is more valuable than ever. Software is also more open, collaborative, and complex than ever before. This makes it a threat for corporate security. BluBracket allows companies to see where source code poses security risks and allows them to fully secure their code without affecting developer workflows or productivity. You can't protect what you don't see. Today's collaborative coding tools are causing code proliferation that companies don't have visibility into. BluBracket allows companies to view a BluPrint of the code environments within their organization. This allows them to see exactly where their code is located and who has access. You can also classify the most important codes with just one click, so you can show an audit trail or compliance report.

Project IDX is a new experimental initiative that aims to bring your entire multiplatform, full-stack app development workflow into the cloud. Project IDX begins with a web workspace that will feel familiar to coders but new. We're only at the beginning of our journey. We would love to hear your feedback as we work on improving application development. Project IDX will get you up and running quickly, with the security and scalability that Google Cloud offers. Open your browser and develop an application in seconds, not weeks, on any device. Project IDX allows you to build an app that is compatible with multiple platforms. It offers templates for popular frameworks such as Angular.js, Next.js React, Svelte and Flutter. Python and Go will be supported soon. You can import your existing apps from GitHub. Support is available for most tech stacks.

Code editing. Redefined Free. Open source. It runs everywhere. IntelliSense provides smart completions that go beyond syntax highlighting and autocomplete. It uses variable types, function definitions and imported modules to provide intelligent completions. You can debug code directly from the editor. You can attach or launch your apps, and debug with breakpoints, call stacks and an interactive console. It's never been easier to work with Git or other SCM providers. The editor allows you to review diffs and stage files, as well as make commits. Pull and push from any hosted SCM service. Want even more features? To add languages, themes, debuggers and connect to other services, install extensions. Extensions are separate processes that don't slow down your editor. Learn more about extensions. Microsoft Azure allows you to deploy and host your React (Angular), Vue, Node (and many more!) applications. Sites can store and query relational or document-based data and scale with serverless computing.

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.

esDynamic allows you to maximize your security testing journey. From setting up your bench, to analyzing the results of your data processing, esDynamic will save you time and effort. Discover the comprehensive and flexible Python-based platform that is perfect for every phase of security analysis. You can easily customize your research space by adding new equipment, integrating different tools, and changing data. esDynamic also offers a large collection of materials that cover complex topics, which would normally require extensive research and a team of experts. This gives you instant access to expertise. Say goodbye to fragmented data and scattered knowledge. Welcome to a cohesive workspace that allows your team to easily share data and insights. This will foster collaboration and accelerate discoveries. Share your JupyterLab Notebooks with your team to centralize and solidify all your efforts.

Deepnote is building the best data science notebook for teams. Connect your data, explore and analyze it within the notebook with real-time collaboration and versioning. Share links to your projects with other analysts and data scientists on your team, or present your polished, published notebooks to end users and stakeholders. All of this is done through a powerful, browser-based UI that runs in the cloud.

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.

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.

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.

Dask is free and open-source. It was developed in collaboration with other community projects such as NumPy and pandas. Dask uses existing Python data structures and APIs to make it easy for users to switch between NumPy/pandas and scikit-learn-powered versions. Dask's schedulers can scale to thousands of node clusters, and its algorithms have been tested at some of the most powerful supercomputers around the world. You don't necessarily need a large cluster to get started. Dask ships schedulers that can be used on personal computers. Many people use Dask to scale computations on their laptops, using multiple cores and their disk for extra storage. Dask exposes lower level APIs that allow you to build custom systems for your own applications. This allows open-source leaders to parallelize their own packages, and business leaders to scale custom business logic.

Machine learning uncovers hidden patterns in enterprise data and generates new value for businesses. Oracle Machine Learning makes it easier to create and deploy machine learning models for data scientists by using AutoML technology and reducing data movement. It also simplifies deployment. Apache Zeppelin notebook technology, which is open-source-based, can increase developer productivity and decrease their learning curve. Notebooks are compatible with SQL, PL/SQL and Python. Users can also use markdown interpreters for Oracle Autonomous Database to create models in their preferred language. No-code user interface that supports AutoML on Autonomous Database. This will increase data scientist productivity as well as non-expert users' access to powerful in-database algorithms to classify and regression. Data scientists can deploy integrated models using the Oracle Machine Learning AutoML User Interface.

Metacoder makes data processing faster and more efficient. Metacoder provides data analysts with the flexibility and tools they need to make data analysis easier. Metacoder automates data preparation steps like cleaning, reducing the time it takes to inspect your data before you can get up and running. It is a good company when compared to other companies. Metacoder is cheaper than similar companies and our management is actively developing based upon our valued customers' feedback. Metacoder is primarily used to support predictive analytics professionals in their work. We offer interfaces for database integrations, data cleaning, preprocessing, modeling, and display/interpretation of results. We make it easy to manage the machine learning pipeline and help organizations share their work. Soon, we will offer code-free solutions for image, audio and video as well as biomedical data.

Beautiful dashboards and reports are available in BI tools that allow users to examine patterns in historical data. Past data can provide insights. It cannot be prescriptive. Model-Driven decision making is the only way to get a better understanding of what could happen in unusual situations and how to make it happen. Analytica is an innovative visual software environment that allows you to build, explore, and share quantitative decision models that produce prescriptive results. Transcend cumbersome spreadsheets. Analytica's flexibility, power, flexibility, and clarity are a revelation. Analytica makes it easy to create transparent models in fractions of the time required for procedural languages such as R or Python. Analytica provides insights, not just numbers. Agile modeling can be used to create models that support business decision-making. Probabilistic simulations are efficient and accurate in estimating risk and uncertainty. Smart sensitivity analysis reveals what is important and why.

Real-time business decisions that are ubiquitous without the need for expensive and specialized resources. UBIX is at the forefront of generative AI, reinforcement learning and business-led automation. Our patented SaaS platform contextualizes data from within and outside the enterprise and presents it in minutes, rather than days, ensuring AI innovation transformation. Improve daily decisions that have an impact on productivity, waste, compliance and profitability. The right data is delivered to the right business leaders at the right time and in the correct format. In just a few days and 5 simple steps, you can AI-enable any enterprise. Data scientists can be freed up to innovate instead of generating reports and improve business intelligence initiatives. Artificial intelligence is not just for large organizations or technical teams. It's available to all organizations. UBIX makes advanced analytics and artificial intelligence available to everyone.