Alternatives to ioModel

Open source platform for machine learning. TensorFlow is a machine learning platform that is open-source and available to all. It offers a flexible, comprehensive ecosystem of tools, libraries, and community resources that allows researchers to push the boundaries of machine learning. Developers can easily create and deploy ML-powered applications using its tools. Easy ML model training and development using high-level APIs such as Keras. This allows for quick model iteration and debugging. No matter what language you choose, you can easily train and deploy models in cloud, browser, on-prem, or on-device. It is a simple and flexible architecture that allows you to quickly take new ideas from concept to code to state-of the-art models and publication. TensorFlow makes it easy to build, deploy, and test.

TIMi allows companies to use their corporate data to generate new ideas and make crucial business decisions more quickly and easily than ever before. The heart of TIMi’s Integrated Platform. TIMi's ultimate real time AUTO-ML engine. 3D VR segmentation, visualization. Unlimited self service business Intelligence. TIMi is a faster solution than any other to perform the 2 most critical analytical tasks: data cleaning, feature engineering, creation KPIs, and predictive modeling. TIMi is an ethical solution. There is no lock-in, just excellence. We guarantee you work in complete serenity, without unexpected costs. TIMi's unique software infrastructure allows for maximum flexibility during the exploration phase, and high reliability during the production phase. TIMi allows your analysts to test even the most crazy ideas.

This machine learning monitoring tool allows you to easily monitor and troubleshoot large model volumes. Data scientists can avoid false alarms and dead ends by using an unrivaled explainability accuracy and unique analyses that aren't available anywhere else. This allows them to quickly and effectively address critical problems. So that your business runs at its best, machine learning models are optimized. TruEra's explainability engine is the result of years of dedicated research and development. It is significantly more accurate that current tools. TruEra's enterprise-class AI explainability tech is unrivalled. The core diagnostic engine is built on six years of research by Carnegie Mellon University. It outperforms all competitors. The platform performs sophisticated sensitivity analyses quickly, allowing data scientists, business users, risk and compliance teams to understand how and why a model makes predictions.

Altair is used by data scientists and business analysts to extract actionable insights from their data. Knowledge Studio is a market-leading, easy-to-use machine learning and predictive analytics tool that quickly visualizes data and generates explainable results. It doesn't require a single line code. Knowledge Studio, a recognized leader in analytics, brings transparency and automation into machine learning with features like AutoML and explainable AI. You have complete control over how models are built and configured. Knowledge Studio is designed for collaboration across the business. Complex projects can be completed by data scientists and business analysts in minutes, hours, or even days. Results are easy to understand and explain. Data scientists can quickly create machine learning models using less time than coding or using other tools because of the ease of use and automation of modeling steps.

Comprehensive IP data of high quality for patent analytics. 136 million patents in 100+ countries. Brands and organizations of every size trust us. XLSCOUT combined data with the best-in class artificial intelligence technologies to create the most accurate, comprehensive and intelligent patent & publication database. Using Natural Language Processing (NLP), Machine Learning (ML), and innovation/scientific principles, XLSCOUT gives you more time and reliable insights to confidently make data-driven strategic decisions. Drafting LLM, a cutting edge platform for drafting patent applications, uses Large Language Models (LLMs), & Generative AI to draft top-tier preliminary drafts. Novelty Checker LLM quickly scans patent and non-patent literature to deliver a comprehensive list with ranked prior art references, along with a report on key features.

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.

MyDataModels' best-in-class predictive analytics model TADA allows professionals to use their Small Data to improve their business. It is a simple-to-use tool that is easy to set up. TADA is a predictive modeling tool that delivers fast and useful results. With our 40% faster automated data preparation, you can transform your time from days to just a few hours to create ad-hoc effective models. You can get results from your data without any programming or machine learning skills. Make your time more efficient with easy-to-understand models that are clear and understandable. You can quickly turn your data into insights on any platform and create automated models that are effective. TADA automates the process of creating predictive models. Our web-based pre-processing capabilities allow you to create and run machine learning models from any device or platform.

Patients around the globe suffer from complex diseases and have a wide range of symptoms. They all share one thing: Patients need faster access to safer and more effective treatments. Owkin's mission empowers researchers at hospitals, universities, as well as pharmaceutical companies to understand why drug efficacy differs from patient to patient, improve the drug development process, identify the best drug for the patient to improve treatment outcomes, and provide support to patients. Owkin Loop, the core of Owkin’s research platform, connects medical researchers to high-quality datasets from top academic research centers around world. Owkin Studio, Owkin Connect and Owkin Studio are the two main components of Owkin Software Stack. They power Owkin Loop. Owkin medical research collaborations include oncology, immunology, and cardiovascular diseases.

Self-service machine learning platform that allows you to turn models into APIs with just a few mouse clicks. Sign up for a Deep Infra Account using GitHub, or login using GitHub. Choose from hundreds of popular ML models. Call your model using a simple REST API. Our serverless GPUs allow you to deploy models faster and cheaper than if you were to build the infrastructure yourself. Depending on the model, we have different pricing models. Some of our models have token-based pricing. The majority of models are charged by the time it takes to execute an inference. This pricing model allows you to only pay for the services you use. You can easily scale your business as your needs change. There are no upfront costs or long-term contracts. All models are optimized for low latency and inference performance on A100 GPUs. Our system will automatically scale up the model based on your requirements.

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.

Amazon SageMaker Studio Lab provides a free environment for machine learning (ML), which includes storage up to 15GB and security. Anyone can use it to learn and experiment with ML. You only need a valid email address to get started. You don't have to set up infrastructure, manage access or even sign-up for an AWS account. SageMaker Studio Lab enables model building via GitHub integration. It comes preconfigured and includes the most popular ML tools and frameworks to get you started right away. SageMaker Studio Lab automatically saves all your work, so you don’t have to restart between sessions. It's as simple as closing your computer and returning later. Machine learning development environment free of charge that offers computing, storage, security, and the ability to learn and experiment using ML. Integration with GitHub and preconfigured to work immediately with the most popular ML frameworks, tools, and libraries.

Machine learning can do amazing things, including understanding the world, driving cars, writing code, and making art. It's still very difficult to use. Research is usually published in a PDF format. There are also bits of code on GitHub and weights (if you're fortunate!) on Google Drive. It's difficult to apply that work to a real-world problem unless you're an expert. Machine learning is now accessible to everyone. Machine learning models should be shared by people who create them. People who want to use machine-learning should not need a PhD to share their machine learning models. Great power comes with great responsibility. We believe that this technology can be made safer and more understandable by using better tools and safeguards.

The Descartes Labs Platform was created to address some of the most pressing geospatial analysis questions in the world. The platform allows customers to quickly and efficiently build models and algorithms that transform their businesses. We help AI become a core competency by providing data scientists and their line of business colleagues with the best geospatial and modeling tools in one package. Our massive data archive and their own data can be used by data science teams to create models faster than ever before. Our cloud-based platform allows customers to rapidly and securely scale machine learning, statistical, or computer vision models to inform business decisions using powerful raster-based analytics. Our extensive API documentation, tutorials and guides, as well as demos, provide users with a rich knowledge base that allows them to quickly deploy high-value apps across a variety of industries.

SquareML is an advanced machine learning platform that does not require any coding. It was designed to make predictive modeling and advanced data analytics more accessible to everyone, especially in the healthcare industry. It allows users to harness machine-learning capabilities without extensive coding expertise, regardless of their technical expertise. The platform is specialized in data ingestion, including electronic health records and claims databases. It also includes medical devices and health information exchanges. The platform's key features include a data science lifecycle that requires no coding, generative AI for healthcare, unstructured conversion of data, diverse machine learning algorithms for predicting disease progression and patient outcomes, a library with pre-built models, and seamless integration to various healthcare data sources. SquareML's AI-powered insights are designed to streamline data processes, improve diagnostic accuracy, and improve the outcomes of patient care.

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.

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.

Apache PredictionIO®, an open-source machine-learning server, is built on top a state of the art open-source stack that allows data scientists and developers to create predictive engines for any type of machine learning task. It allows you to quickly create and deploy an engine as web service on production using customizable templates. Once deployed as a web-service, it can respond to dynamic queries immediately, evaluate and tune multiple engine variations systematically, unify data from multiple platforms either in batch or real-time for comprehensive predictive analysis. Machine learning modeling can be speeded up with pre-built evaluation methods and systematic processes. These measures also support machine learning and data processing libraries like Spark MLLib or OpenNLP. You can create your own machine learning models and integrate them seamlessly into your engine. Data infrastructure management simplified. Apache PredictionIO®, a complete machine learning stack, can be installed together with Apache Spark, MLlib and HBase.

The most complex AI, ML, Deep Learning models can be trained. With just a few clicks, you can scale from a single machine up to a whole fleet of VMs. Lambda Cloud makes it easy to scale up or start your Deep Learning project. You can get started quickly, save compute costs, and scale up to hundreds of GPUs. Every VM is pre-installed with the most recent version of Lambda Stack. This includes major deep learning frameworks as well as CUDA®. drivers. You can access the cloud dashboard to instantly access a Jupyter Notebook development environment on each machine. You can connect directly via the Web Terminal or use SSH directly using one of your SSH keys. Lambda can make significant savings by building scaled compute infrastructure to meet the needs of deep learning researchers. Cloud computing allows you to be flexible and save money, even when your workloads increase rapidly.

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.

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.

Scraawl is an integrated suite of data analytics tools that will help you get more out of your data. Scraawl can help you analyze data that is publicly available, such as images and video, text, or all three. Scraawl uses state-of-the art artificial intelligence and machine-learning techniques to provide actionable insights via analytics. Our team is made up of data scientists, data scientists, researchers, and developers who are all dedicated to providing cutting-edge analytics to users. Scraawl SocL® is a web-based, enterprise-level, simple-to-use PAI listening and analysis tool. Scraawl SocL® analyzes, visualizes, and searches online conversations and news data to provide a user with a detailed 360 degree analysis.

JADBio is an automated machine learning platform that uses JADBio's state-of-the art technology without any programming. It solves many open problems in machine-learning with its innovative algorithms. It is easy to use and can perform sophisticated and accurate machine learning analyses, even if you don't know any math, statistics or coding. It was specifically designed for life science data, particularly molecular data. It can handle the unique molecular data issues such as low sample sizes and high numbers of measured quantities, which could reach into the millions. It is essential for life scientists to identify the biomarkers and features that are predictive and important. They also need to know their roles and how they can help them understand the molecular mechanisms. Knowledge discovery is often more important that a predictive model. JADBio focuses on feature selection, and its interpretation.

Hopsworks is an open source Enterprise platform that allows you to develop and operate Machine Learning (ML), pipelines at scale. It is built around the first Feature Store for ML in the industry. You can quickly move from data exploration and model building in Python with Jupyter notebooks. Conda is all you need to run production-quality end-to-end ML pipes. Hopsworks can access data from any datasources you choose. They can be in the cloud, on premise, IoT networks or from your Industry 4.0-solution. You can deploy on-premises using your hardware or your preferred cloud provider. Hopsworks will offer the same user experience in cloud deployments or the most secure air-gapped deployments.

We help developers solve the most pressing problems in the world by unlocking the potential value of sensitive data without increasing risk. We are developing tools for privacy-safe machinelearning and analytics for the distributed future. All types of data are generated and stored in the cloud and on prem. It can be costly to de-identify, move, centrally store, and manage large volumes of data. HIPAA, GDPR and PIPEDA, CCPA, and other regulations limit how data can be combined, especially between jurisdictions. Federated learning and analytics allows only model parameters to leave each private server. Data custodians have full control over their data. Build new product features that harness the collective intelligence from your customers to grow your business and connect with customers.

A new category of AI. Most AI solutions today are designed using a mathematical and statistical lens. We took a different approach. Intelligent Artifacts' team has created a new type of AI based on information theory. It is a true AGI that eliminates the current shortcomings in machine intelligence. Our framework separates the intelligence layer from the data and application layers, allowing it to learn in real time and allowing it to make predictions down to the root cause. A truly integrated platform is required for AGI. Intelligent Artifacts will allow you to model information, not data. Predictions and decisions can be made across multiple domains without the need for rewriting code. Our dynamic platform and specialized AI consultants will provide you with a tailored solution that quickly provides deep insights and better outcomes from your data.

Superb AI offers a new generation of machine learning data platform to AI team members so they can create better AI in a shorter time. The Superb AI Suite, an enterprise SaaS platform, was created to aid ML engineers, product teams and data annotators in creating efficient training data workflows that save time and money. Superb AI can help ML teams save more than 50% on managing training data. Our customers have averaged a 80% reduction in the time it takes for models to be trained. Fully managed workforce, powerful labeling and training data quality control tools, pre-trained models predictions, advanced auto-labeling and filtering your datasets, data source and integration, robust developer tools, ML work flow integrations and many other benefits. Superb AI makes it easier to manage your training data. Superb AI provides enterprise-level features to every layer of an ML organization.

Machine learning can be applied to distributed data to provide faster insights and better results without the long lead times, high concentration risk, or privacy concerns associated with centralizing data. Access to diverse, high-quality data sources is often a limitation of machine learning algorithms' effectiveness. You can gain more insight by unlocking more data and making it transparent about the impact of each dataset model. It takes time to get approvals, centralize data, and build out infrastructure. You can train models faster by using data right where it is while parallelizing and federating the training process. Devron allows you to access data in situ without the need to mask or anonymize. This greatly reduces the overhead of data extraction, transformation, loading, and storage.

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.

Easy management, deployment and monitoring of machine learning models for supercharging MLOps. Available for all organizations on the best AI platform. You can use navio for various machine learning operations across your entire artificial intelligence landscape. Machine learning can be integrated into your business workflow to make a tangible, measurable impact on your business. navio offers various Machine Learning Operations (MLOps), which can be used to support you from the initial model development phase to the production run of your model. Automatically create REST endspoints and keep track the clients or machines that interact with your model. To get the best results, you should focus on exploring and training your models. You can also stop wasting time and resources setting up infrastructure. Let navio manage all aspects of product ionization so you can go live quickly with your machine-learning models.

Cloud AutoML is a set of machine learning products that allows developers with limited machine-learning expertise to create high-quality models tailored to their business needs. It uses Google's state of the art neural architecture and transfer learning search technology. Cloud AutoML uses more than 10 years' of Google Research technology to help machine learning models achieve faster performance, better predictions, and more accurate predictions. Cloud AutoML's graphical user interface makes it easy to build, evaluate, improve, deploy, and test models based upon your data. Only a few clicks away is your custom machine learning model. Google's human-labeling service can assign a team to clean and annotate your labels. This will ensure that your models are trained with high-quality data.

Neural Designer is a data-science and machine learning platform that allows you to build, train, deploy, and maintain neural network models. This tool was created to allow innovative companies and research centres to focus on their applications, not on programming algorithms or programming techniques. Neural Designer does not require you to code or create block diagrams. Instead, the interface guides users through a series of clearly defined steps. Machine Learning can be applied in different industries. These are some examples of machine learning solutions: - In engineering: Performance optimization, quality improvement and fault detection - In banking, insurance: churn prevention and customer targeting. - In healthcare: medical diagnosis, prognosis and activity recognition, microarray analysis and drug design. Neural Designer's strength is its ability to intuitively build predictive models and perform complex operations.

Daria's advanced automated features enable users to quickly and easily create predictive models. This significantly reduces the time and effort required to build them. Eliminate technological and financial barriers to building AI systems from scratch for businesses. Automated machine learning for data professionals can streamline and speed up workflows, reducing the amount of iterative work required. An intuitive GUI for data science beginners gives you hands-on experience with machine learning. Daria offers various data transformation functions that allow you to quickly create multiple feature sets. Daria automatically searches through millions of combinations of algorithms, modeling techniques, and hyperparameters in order to find the best predictive model. Daria's RESTful API allows you to deploy predictive models directly into production.

Arize's machine-learning observability platform automatically detects and diagnoses problems and improves models. Machine learning systems are essential for businesses and customers, but often fail to perform in real life. Arize is an end to-end platform for observing and solving issues in your AI models. Seamlessly enable observation for any model, on any platform, in any environment. SDKs that are lightweight for sending production, validation, or training data. You can link real-time ground truth with predictions, or delay. You can gain confidence in your models' performance once they are deployed. Identify and prevent any performance or prediction drift issues, as well as quality issues, before they become serious. Even the most complex models can be reduced in time to resolution (MTTR). Flexible, easy-to use tools for root cause analysis are available.

Neptune.ai, a platform for machine learning operations, is designed to streamline tracking, organizing and sharing of experiments, and model-building. It provides a comprehensive platform for data scientists and machine-learning engineers to log, visualise, and compare model training run, datasets and hyperparameters in real-time. Neptune.ai integrates seamlessly with popular machine-learning libraries, allowing teams to efficiently manage research and production workflows. Neptune.ai's features, which include collaboration, versioning and reproducibility of experiments, enhance productivity and help ensure that machine-learning projects are transparent and well documented throughout their lifecycle.

With a single command, you can train and serve large AI models in scale. You can simply point to your S3 bucket. We take care of the rest: orchestration, efficiency and node failures. Simple and scalable. MosaicML allows you to train and deploy large AI model on your data in a secure environment. Keep up with the latest techniques, recipes, and foundation models. Our research team has developed and rigorously tested these recipes. In just a few easy steps, you can deploy your private cloud. Your data and models will never leave the firewalls. You can start in one cloud and continue in another without missing a beat. Own the model trained on your data. Model decisions can be better explained by examining them. Filter content and data according to your business needs. Integrate seamlessly with your existing data pipelines and experiment trackers. We are cloud-agnostic and enterprise-proven.

Deeploy allows you to maintain control over your ML models. You can easily deploy your models to our responsible AI platform without compromising transparency, control and compliance. Transparency, explainability and security of AI models are more important today than ever. You can monitor the performance of your models with confidence and accountability if you use a safe, secure environment. Over the years, our experience has shown us the importance of human interaction with machine learning. Only when machine-learning systems are transparent and accountable can experts and consumers provide feedback, overrule their decisions when necessary, and grow their trust. We created Deeploy for this reason.

Create statistically optimized representations for your data to train accurate ML models with limited, sparse and high-dimensional data. Dark Matter accelerates training and improves model performance by learning how to extract complex relationships from your existing data. This is done without extensive feature engineering and resource-intensive deep-learning. Data scientists can spend less time on data to solve hard problems. Dark Matter significantly improved the model precision and f1 score in predicting customer convertion in the online retail sector. When trained on an embedded optimization learned from sparse and high-dimensional data, model performance metrics improved across board. The banking industry improved its predictions of customer churn by training XGBoost with a better representation. No matter what model or domain you are in, you can improve your pipeline.

HPE Ezmeral ML Ops offers pre-packaged tools that enable you to operate machine learning workflows at any stage of the ML lifecycle. This will give you DevOps-like speed, agility, and speed. You can quickly set up environments using your preferred data science tools. This allows you to explore multiple enterprise data sources, and simultaneously experiment with multiple deep learning frameworks or machine learning models to find the best model for the business problems. On-demand, self-service environments that can be used for testing and development as well as production workloads. Highly performant training environments with separation of compute/storage that securely access shared enterprise data sources in cloud-based or on-premises storage.

The Salford Predictive Modeler® (SPM), software suite, is highly accurate and extremely fast for developing predictive, descriptive, or analytical models. Salford Predictive Modeler®, which includes the CART®, TreeNet®, Random Forests® engines, and powerful new automation capabilities and modeling capabilities that are not available elsewhere, is a software suite that includes the MARS®, CART®, TreeNet[r], and TreeNet®. The SPM software suite's data mining technologies span classification, regression, survival analysis, missing value analysis, data binning and clustering/segmentation. SPM algorithms are essential in advanced data science circles. Automation of model building is made easier by the SPM software suite. It automates significant portions of the model exploration, refinement, and refinement process for analysts. We combine all results from different modeling strategies into one package for easy review.

Baidu AI Cloud Machine Learning is an end-toend machine learning platform for enterprises and AI developers. It can perform data preprocessing, model evaluation and training, as well as service deployments. The Baidu AI Cloud AI Development Platform BML is a platform for AI development and deployment. BML allows users to perform data pre-processing and model training, evaluation, service deployment and other tasks. The platform offers a high-performance training environment for clusters, a massive algorithm framework and model cases as well as easy to use prediction service tools. It allows users to concentrate on the algorithm and model, and achieve excellent model and predictions results. The interactive programming environment is fully hosted and allows for data processing and code debugging. The CPU instance allows users to customize the environment and install third-party software libraries.

CentML speeds up Machine Learning workloads by optimising models to use hardware accelerators like GPUs and TPUs more efficiently without affecting model accuracy. Our technology increases training and inference speed, lowers computation costs, increases product margins using AI-powered products, and boosts the productivity of your engineering team. Software is only as good as the team that built it. Our team includes world-class machine learning, system researchers, and engineers. Our technology will ensure that your AI products are optimized for performance and cost-effectiveness.

SAS technologies combine to provide powerful tools for visual information. You can access, manipulate, analyze, and present information in visual formats. SAS Visual Machine Learning allows you to expand your analytics by using machine learning and deep learning capabilities. This makes it easier to visualize and report better. 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.

Artificio, an innovative automation tool created by Artificio Products Inc., is designed to revolutionize the data processing process and eliminate manual data input. This cutting-edge tool uses state-of-the art AI and machine learning models for extracting, segregating, validating, and integrating unstructured data from different sources including texts, images, and PDFs. Artificio enables businesses to unlock digital intelligence's full potential by converting unstructured data into structured data.

Alpa aims automate large-scale distributed training. Alpa was originally developed by people at UC Berkeley's Sky Lab. Alpa's advanced techniques were described in a paper published by OSDI'2022. Google is adding new members to the Alpa community. A language model is a probabilistic distribution of probability over a sequence of words. It uses all the words it has seen to predict the next word. It is useful in a variety AI applications, including the auto-completion of your email or chatbot service. You can find more information on the language model Wikipedia page. GPT-3 is a large language model with 175 billion parameters that uses deep learning to produce text that looks human-like. GPT-3 was described by many researchers and news articles as "one the most important and interesting AI systems ever created." GPT-3 is being used as a backbone for the latest NLP research.

Invert provides a complete solution for collecting, cleaning and contextualizing data. This ensures that every analysis and insight are based on reliable and organized data. Invert collects, standardizes, and models all your bioprocessing data. It has powerful built-in tools for analysis, machine-learning, and modeling. Data that is clean, standardized and pristine is only the beginning. Explore our suite of tools for data management, analysis and modeling. Replace manual workflows with spreadsheets or statistical software. Calculate anything with powerful statistical features. Automatically generate reports using recent runs. Add interactive plots and calculations and share them with collaborators. Streamline the planning, coordination and execution of experiments. Find the data you want and dive deep into any analysis. Find all the tools to manage your data, from integration to analysis and modeling.

Tencent Cloud TI Platform, a machine learning platform for AI engineers, is a one stop shop. It supports AI development at every stage, from data preprocessing, to model building, to model training, to model evaluation, as well as model service. It is preconfigured with diverse algorithms components and supports multiple algorithm frameworks for adapting to different AI use-cases. Tencent Cloud TI Platform offers a machine learning experience in a single-stop shop. It covers a closed-loop workflow, from data preprocessing, to model building, training and evaluation. Tencent Cloud TI Platform allows even AI beginners to have their models automatically constructed, making the entire training process much easier. Tencent Cloud TI Platform’s auto-tuning feature can also improve the efficiency of parameter optimization. Tencent Cloud TI Platform enables CPU/GPU resources that can elastically respond with flexible billing methods to different computing power requirements.

Amazon SageMaker Canvas provides business analysts with a visual interface to help them generate accurate ML predictions. They don't need any ML experience nor to write a single line code. A visual interface that allows users to connect, prepare, analyze and explore data in order to build ML models and generate accurate predictions. Automate the creation of ML models in just a few clicks. By sharing, reviewing, updating, and revising ML models across tools, you can increase collaboration between data scientists and business analysts. Import ML models anywhere and instantly generate predictions in Amazon SageMaker Canvas. Amazon SageMaker Canvas allows you to import data from different sources, select the values you wish to predict, prepare and explore data, then quickly and easily build ML models. The model can then be analyzed and used to make accurate predictions.

PolyAnalyst, a data analysis tool, is used by large companies in many industries (Insurance Manufacturing, Finance, etc.). It uses a visual composer to simplify complex data analysis modeling instead of programming/coding. This is one of its most distinctive features. It can combine structured and poly-structured data for unified analysis (multiple-choice questions and open ended responses), and it can process text data from over 16+ languages. PolyAnalyst provides many features to meet comprehensive data analysis requirements, including the ability to load data, cleanse and prepare data for analysis, deploy machine learning and supervised analytics techniques, and create reports that non-analysts may use to uncover insights.

Wallaroo is the last mile of your machine-learning journey. It helps you integrate ML into your production environment and improve your bottom line. Wallaroo was designed from the ground up to make it easy to deploy and manage ML production-wide, unlike Apache Spark or heavy-weight containers. ML that costs up to 80% less and can scale to more data, more complex models, and more models at a fraction of the cost. Wallaroo was designed to allow data scientists to quickly deploy their ML models against live data. This can be used for testing, staging, and prod environments. Wallaroo supports the most extensive range of machine learning training frameworks. The platform will take care of deployment and inference speed and scale, so you can focus on building and iterating your models.

It's easy to build advanced predictive models with no math or coding in just a few clicks. The Complete Experience We provide everything you need, from cleaning data to building models to forecasting, and everything in between. Trustworthy. Learn the "why" behind AI decisions to drive business with actionable insight. Data Analytics in minutes without having to write code. In one click, you can complete the entire process of building ML algorithms, explaining results and predicting future outcomes. Machine Learning in 3 Steps You can go from raw data to actionable insights without writing a single line code. Upload your data. Ask questions in plain English Find the best model for your data. Share your results. Increase customer productivity We assist companies to use no code Machine Learning to improve their Customer Experience.