Alternatives to Peak

Fully managed ML tools allow you to build, deploy and scale machine-learning (ML) models quickly, for any use case. Vertex AI Workbench is natively integrated with BigQuery Dataproc and Spark. You can use BigQuery to create and execute machine-learning models in BigQuery by using standard SQL queries and spreadsheets or you can export datasets directly from BigQuery into Vertex AI Workbench to run your models there. Vertex Data Labeling can be used to create highly accurate labels for data collection.

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.

Scios platform unifies your market, expertise, and data It combines data and expertise with the dynamics of consumer decisions, delivering collaborative analytics and decision intelligence. Scios harmonizes data sources and research by integrating consumer, macroeconomic, and competitive data into a digital model of the market. You can use the Scios platform to integrate data about sales, marketing and more for yourself and your competitors. - Run an Attribution Analysis to understand the relative importance for many different factors - Run What If scenarios and Goal Optimizations for the best possible path forward - Perform an optimization analysis to determine the optimal budget allocation for your sales target.

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.

Manage, control, secure, and manage the apps, data, and IT that run your business from edge to cloud. HPE Ezmeral accelerates digital transformation initiatives by shifting resources and time from IT operations to innovation. Modernize your apps. Simplify your operations. You can harness data to transform insights into impact. Kubernetes can be deployed at scale in your data center or on the edge. It integrates persistent data storage to allow app modernization on baremetal or VMs. This will accelerate time-to-value. Operationalizing the entire process to build data pipelines will allow you to harness data faster and gain insights. DevOps agility is key to machine learning's lifecycle. This will enable you to deliver a unified data network. Automation and advanced artificial intelligence can increase efficiency and agility in IT Ops. Provide security and control to reduce risk and lower costs. The HPE Ezmeral Container Platform is an enterprise-grade platform that deploys Kubernetes at large scale for a wide variety of uses.

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.

Integrate analytics into real time interactions and event-based capabilities. SAS Visual Data Science Decisioning offers robust data management, visualization, advanced analysis, and model management. It supports decision making by creating, embedding, and governing analytically driven decision flows at scale in batch or real-time. It also provides analytics and stream-based decisions to help you uncover insights. A comprehensive visual interface allows you to solve complex analytical problems. It handles all aspects of the analytics lifecycle. SAS Visual Data Mining and Machine Learning runs in SAS®, Viya®. It combines data wrangling and exploration with feature engineering and modern statistical, data mining and machine learning techniques in one, scalable, in-memory processing environment. This web application is a development tool that you can access via your browser.

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.

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.

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.

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.

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.

To identify the best actions, you need to build and solve complex optimization models. IBM®, ILOG®, CPLEX®, Optimization Studio uses decision optimization technology. It optimizes your business decisions, creates and deploys optimization models quickly, and creates real-world applications that can significantly increase business outcomes. How does it work? How? It combines a fully-featured integrated development environment that supports Optimization Programming Language, (OPL), and the high-performance CPLEX/CP Optimizer solvers. It's data science for your decisions. IBM Decision Optimization is also available in Cloud Pak for Data. This allows you to combine optimization and machine-learning within a unified environment, IBM Watson® Studio that enables AI infused optimization modeling capabilities.

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.

NVIDIA Merlin enables data scientists, machine-learning engineers, and researchers, to build high-performance recommenders at scale. Merlin includes libraries, methods and tools to streamline the building and deployment of recommenders. These include addressing common challenges in preprocessing, feature engineering and training. Merlin components and capabilities have been optimized to support retrieval, scoring, filtering and ordering of hundreds terabytes data. All of this is accessible via easy-to-use interfaces. Merlin can help you make better predictions, increase click-through rates and deploy faster to production. NVIDIA Merlin is part of NVIDIA AI and advances our commitment to support innovative practitioners doing their best. NVIDIA Merlin is designed as an end-toend solution that can be integrated into existing recommender workflows utilizing data science and machine learning.

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.

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.

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.

Brilent is a data-science tech company that develops a SaaS solution for talent seekers to quickly and effectively find the right talent to hire. This intelligent technology is simple, which is the best part. There are no tricks. It uses the components that recruiters find most relevant. The core elements of the Brilent engine include three simple elements: job requirements, candidate profile, and our unique repository market data. The fun part is next. Our system collects all relevant data from job requirements and candidate profiles. We use hundreds of variables from the market data and familiar elements in recruiting to make predictions about whether a candidate will be a good match for a job. This is a lot of data crunching done in seconds. Recruiters can then rank candidates according to their specifications.

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.

Saturn Cloud is a data science and machine learning platform flexible enough for any team supporting Python, R, and more. Scale, collaborate, and utilize built-in management capabilities to aid you when you run your code.

The largest global team of Fast Data and Functional Programming engineers focused on developing high-performance, customized solutions. Through rapid prototyping and proof-of-concept, we move from "thought to thing". CI/CD can help you create an ecosystem that will deliver at scale. To develop a shared vision, it is important to understand the stakeholder needs and the strategic intent. MVP should be deployed to launch the product in a most efficient and expedient manner. Continuous improvements and enhancements are made to meet new requirements. Without the ability to use the most recent tools and technology, it would be impossible to build great products or provide unmatched engineering services. We help you capitalize on opportunities, respond effectively to competitive threats, scale successful investments, and reduce organizational friction in your company's processes, structures, and culture. Knoldus assists clients in identifying and capturing the highest value and meaningful insights from their data.

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.

Dash & Dash Enterprise allow you to build and deploy analytic web applications using Python, R, or Julia. No JavaScript or DevOps are required. The world's most successful companies offer AI, ML and Python analytics at a fraction of the cost of full-stack development. Dash is the way they do it. Apps and dashboards that run advanced analytics such as NLP, forecasting and computer vision can be delivered. You can work in Python, R, or Julia. Reduce costs by migrating legacy per-seat license software to Dash Enterprise's unlimited end-user pricing model. You can deploy and update Dash apps faster without an IT or DevOps staff. You can create pixel-perfect web apps and dashboards without having to write any CSS. Kubernetes makes it easy to scale. High availability support for mission-critical Python apps

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.

TrueFoundry provides data scientists and ML engineers with the fastest framework to support the post-model pipeline. With the best DevOps practices, we enable instant monitored endpoints to models in just 15 minutes! You can save, version, and monitor ML models and artifacts. With one command, you can create an endpoint for your ML Model. WebApps can be created without any frontend knowledge or exposure to other users as per your choice. Social swag! Our mission is to make machine learning fast and scalable, which will bring positive value! TrueFoundry is enabling this transformation by automating parts of the ML pipeline that are automated and empowering ML Developers with the ability to test and launch models quickly and with as much autonomy possible. Our inspiration comes from the products that Platform teams have created in top tech companies such as Facebook, Google, Netflix, and others. These products allow all teams to move faster and deploy and iterate independently.

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.

The Iguazio MLOps Platform turns AI projects into real-world business results. You can accelerate and scale the development, deployment, and management of your AI apps with end-to–end automation of deep and machine learning pipelines. A fully integrated platform allows you to seamlessly deploy machine and deep learning models to high-powered business applications, reducing time to market and achieving real-time enterprise performance. Continuously and seamlessly deploy new model into business environments, monitor models during production, detect and mitigate drift, save time and money on operationalizing machine-learning, and save time. Automate and accelerate data science workflows so concepts flow smoothly from development through deployment to impact. Monitor Models, Detect Drift, and Auto-Trigger Training. You can deploy with ease to an Operational Pipeline.

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.

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.

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.

Unutilized data is the biggest obstacle to scaling AI-powered decision making. IBM Cloud Pak®, for Data is a unified platform that provides a data fabric to connect, access and move siloed data across multiple clouds or on premises. Automate policy enforcement and discovery to simplify access to data. A modern cloud data warehouse integrates to accelerate insights. All data can be protected with privacy and usage policy enforcement. To gain faster insights, use a modern, high-performance cloud storage data warehouse. Data scientists, analysts, and developers can use a single platform to create, deploy, and manage trusted AI models in any cloud.

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.

Learn how users interact with your product and identify opportunities to help you make product decisions. Mode allows one Stitch analyst to perform the work of a full-time data team with speed, flexibility, collaboration. Create dashboards for annual revenue and then use chart visualizations quickly to identify anomalies. Share analysis with teams to create polished reports that are investor-ready. Connect your entire tech stack with Mode to identify upstream issues and improve performance. With webhooks and APIs, you can speed up team workflows. Learn how users interact with your product and identify areas for improvement. Use marketing and product data to identify weak points in your funnel, improve landing page performance, and prevent churn from happening.

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.

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.

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.

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.

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.

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.

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.

Machine learning can be shared across your organization by collaborating, democratizing, and operationalizing it. Data science is a team sport. Data scientists, citizen data scientists and data engineers, as well as business users and developers, need flexible tools that facilitate collaboration, automation and reuse of analytic workflows. Algorithms are just one part of advanced analytic technology. Companies must increase their focus on the management, deployment, and monitoring analytic models in order to deliver predictive insights. Smart businesses depend on platforms that can support the entire lifecycle of analytics and provide enterprise security and governance. TIBCO®, Data Science software allows organizations to innovate and solve complex problems more quickly, ensuring that predictive findings are quickly turned into optimal outcomes. Flexible authoring and deployment capabilities allow organizations to expand their data science deployments throughout the organization with TIBCO Data Science.

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.

PROPHET is an yield optimization platform which uses your data and data science to help make better decisions, optimize prices, and increase revenue. We at Furious know how hard you've worked because we've done it ourselves - we have more than 100 years' experience in media and manufacturing. We founded Furious and PROPHET, because we knew that there was a faster, easier way to generate revenue and profits. PROPHET does exactly that. PROPHET uses data, data science, and technology to help you PRICE your inventory better and work smarter, not harder. The days of creating endless spreadsheets and repeating the same manual process are over.

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.

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).

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.

The only platform that can handle all aspects of data pipeline. Gathr was built from the ground up to support a cloud-first world. It is the only platform that can handle all your data integration needs - ingestion and ETL, ELT and CDC, streaming analytics and data preparation, machine-learning, advanced analytics, and more. Gathr makes it easy for anyone to build and deploy pipelines, regardless of their skill level. Ingestion pipelines can be created in minutes and not weeks. You can access data from any source and deliver it to any destination. A wizard-based approach allows you to quickly build applications. A templatized CDC app allows you to replicate data in real time. Native integration for all sources. All the capabilities you need to succeed today or tomorrow. You can choose between pay-per-use, free, or customized according to your needs.

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.

IBM Streams analyzes a wide range of streaming data, including unstructured text, video and audio, and geospatial and sensor data. This helps organizations to spot opportunities and risks, and make decisions in real-time.