Alternatives to Paradise

NovaFori We are a cutting-edge technology firm based in London, Malaga. With a decade of experience in business analysis, market design, development, and data science, we can offer you the best. Our technology supports B2B clients in Europe, North America, and Asia. We have processed more than $11 billion in GMV through our platforms since our inception. The Platform Our data science-powered auction and trading platform is used in multiple industries including procurement, financial services, and logistics. The technology platform is modular, flexible, scalable, and modular. It was designed with the B2C user in mind and complex product attributes for the B2B market. Data Science Machine learning algorithms are used to analyse data and predict future trends, optimise market performance, and leverage data.

Speechmatics is the most accurate and inclusive speech-to-text API ever released. Speechmatics is the world’s leading expert in Speech Technology, combining the latest breakthroughs in AI and ML to unlock the business value in human speech. Businesses use Speechmatics worldwide to accurately understand and transcribe human-level speech into text regardless of demographic, age, gender, accent, dialect, or location in real-time and on recorded media. Combining these transcripts with the latest AI-driven speech capabilities, businesses build products that utilize summarization, topic detection, sentiment analysis, translation, and more. How is Speechmatics different? * The most accurate speech recognition on the market * 55 languages with vast accent and dialect coverage * Cloud-based or on-premises deployment options for data security * Real-time transcription with low latency and high accuracy * Real-time translation with 69 language pairs * Speech Understanding features such as Summaries, Sentiment, Topic Detection, Chapters, Audio Events * Fast and secure transcriptions for pre-recorded audio * Automatic translation and language identification * A culture of R&D in deep learning and speech recognition

Your deep learning workload can be accelerated. AI model training and inference can speed up your time to value. Deep learning is becoming more popular as enterprises adopt it to gain and scale insight through speech recognition and natural language processing. Deep learning can read text, images and video at scale and generate patterns for recommendation engines. It can also model financial risk and detect anomalies. Due to the sheer number of layers and volumes of data required to train neural networks, it has been necessary to use high computational power. Businesses are finding it difficult to demonstrate results from deep learning experiments that were implemented in silos.

The training data platform for AI teams. A machine learning model can only be as good as the training data it uses. Labelbox is an integrated platform that allows you to create and manage high quality training data in one place. It also supports your production pipeline with powerful APIs. A powerful image labeling tool for segmentation, object detection, and image classification. You need precise and intuitive image segmentation tools when every pixel is important. You can customize the tools to suit your particular use case, including custom attributes and more. The performant video labeling editor is for cutting-edge computer visual. Label directly on the video at 30 FPS, with frame level. Labelbox also provides per-frame analytics that allow you to create faster models. It's never been easier to create training data for natural language intelligence. You can quickly and easily label text strings, conversations, paragraphs, or documents with fast and customizable classification.

A platform that offers a variety of machine learning algorithms to meet data mining and analysis needs. Machine Learning Platform for AI offers end-to-end machine-learning services, including data processing and feature engineering, model prediction, model training, model evaluation, and model prediction. Machine learning platform for AI integrates all these services to make AI easier than ever. Machine Learning Platform for AI offers a visual web interface that allows you to create experiments by dragging components onto the canvas. Machine learning modeling is a step-by-step process that improves efficiency and reduces costs when creating experiments. Machine Learning Platform for AI offers more than 100 algorithm components. These include text analysis, finance, classification, clustering and time series.

Scikit-learn offers simple and efficient tools to analyze predictive data. Scikit-learn, an open source machine learning toolkit for Python, is designed to provide efficient and simple tools for data modeling and analysis. Scikit-learn is a robust, open source machine learning library for the Python programming language, built on popular scientific libraries such as NumPy SciPy and Matplotlib. It offers a range of supervised learning algorithms and unsupervised learning methods, making it a valuable toolkit for researchers, data scientists and machine learning engineers. The library is organized in a consistent, flexible framework where different components can be combined to meet specific needs. This modularity allows users to easily build complex pipelines, automate tedious tasks, and integrate Scikit-learn in larger machine-learning workflows. The library's focus on interoperability also ensures that it integrates seamlessly with other Python libraries to facilitate smooth data processing.

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.

Open source machine learning and data visualization. With a wide range of tools, you can create data analysis workflows visually. Simple data analysis can be done with data visualization. Explore statistical distributions, box and scatter plots. Or dive deeper with decision trees and hierarchical clustering, heatmaps and MDS. Smart attribute ranking and selections can make multidimensional data more sensible in 2D. Interactive data exploration allows for qualitative analysis in a quick and efficient manner. The graphic user interface allows you focus on exploratory data analysis and not coding. Smart defaults make prototyping a data analysis workflow very easy. Connect widgets to the canvas, place them on the screen, and then load your data. We like to show data mining rather than just explain it. Orange excels at this.

Weka is a collection containing machine learning algorithms for data mining tasks. It includes tools for data preparation, classification and regression, clustering, clustering, association rule mining, visualization, and visualization. The Weka is a flightless bird that lives only on New Zealand's islands. It has an inquisitive nature and is not able to fly. The bird's name is pronounced as follows: Weka is open-source software that is licensed under the GNU General Public License. Weka is open source software. We have created several online courses that can be used to teach machine learning and data mining. You can find the videos on Youtube. The invention and application methods of machine learning (ML) is an exciting development in computer science. These allow a computer program analyze large amounts of data and determine the most relevant information. This information can then be used to automatically predict or help people make faster decisions.

MLBox is a powerful Automated machine learning python Library. It provides the following features fast reading and distributed data preprocessing/cleaning/formatting, highly robust feature selection and leak detection, accurate hyper-parameter optimization in high-dimensional space, state-of-the art predictive models for classification and regression (Deep Learning, Stacking, LightGBM), and prediction with models interpretation. MLBox's main package includes 3 sub-packages, namely preprocessing and prediction. Each of them is aimed at reading data and preprocessing it, testing or optimising learners of different levels and predicting the target using a test dataset.

Apache Mahout is an incredibly powerful, scalable and versatile machine-learning library that was designed for distributed data processing. It provides a set of algorithms that can be used for a variety of tasks, such as classification, clustering and recommendation. Mahout is built on top of Apache Hadoop and uses MapReduce and Spark for data processing. Apache Mahout(TM), a distributed linear-algebra framework, is a mathematically expressive Scala DSL that allows mathematicians to quickly implement their algorithms. Apache Spark is recommended as the default distributed back-end, but can be extended to work with other distributed backends. Matrix computations play a key role in many scientific and engineering applications such as machine learning, data analysis, and computer vision. Apache Mahout is designed for large-scale data processing, leveraging Hadoop and Spark.

Multi-survey structural interpretation and visualization is fast and easy. Multiple users can collaborate in one shared environment. Integrated analysis of multi-scale geophysical, seismic and geological data allows for reliable prediction of facies from well data. Comprehensive, integrated solution for seismic interpretation that includes industry-leading facies classifications and volume visualization workflows. Visual integration and interpretation at all scales, from regional to prospect. You can easily share data and projects with other members of your team without duplication. Interactivity and consistency among views speed up the interpretation process. This makes full use of high-speed graphics and large memory, as well as the fast connectivity of modern workstations. The user interface is intuitive and easy to use.

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.

Every physical object is unique. Our technology can identify any solid object, regardless of its appearance, from visually identical objects. There is no need to serialize, bar codes, RFID, or other methods. It can be used to identify and authenticate objects at low cost, with statistically perfect results. This branch of machine vision is called FeaturePrint™. Every person has unique fingerprints. Each physical object has unique surface characteristics that make it different from all other objects. Once an object has been registered, its FeaturePrint can be securely stored in the cloud. The object's identity can be verified using a ubiquitous device such as a smartphone at any time. Our patent technology uses advanced machine vision, neural network, and deep learning to identify each object based on its unique properties. It is independent of RFID, bar codes, or other proxies. The object itself is capable of identifying the object.

Amazon EC2 Trn2 instances powered by AWS Trainium2 are designed for high-performance deep-learning training of generative AI model, including large language models, diffusion models, and diffusion models. They can save up to 50% on the cost of training compared to comparable Amazon EC2 Instances. Trn2 instances can support up to 16 Trainium2 accelerations, delivering up to 3 petaflops FP16/BF16 computing power and 512GB of high bandwidth memory. Trn2 instances support up to 1600 Gbps second-generation Elastic Fabric Adapter network bandwidth. NeuronLink is a high-speed nonblocking interconnect that facilitates efficient data and models parallelism. They are deployed as EC2 UltraClusters and can scale up to 30,000 Trainium2 processors interconnected by a nonblocking, petabit-scale, network, delivering six exaflops in compute performance. The AWS neuron SDK integrates with popular machine-learning frameworks such as PyTorch or TensorFlow.

A powerful labeling platform for all stages and types of ML development. We leverage a suite of industry-leading computer vision algorithms to automatically detect and classify the content of your images and videos. Creating detailed segmentation information is a time-consuming process. Machine assistance speeds up task completion by as much as 70%, saving you both time and money. We leverage ML to propose labels that accelerate human labeling. This includes computer vision models to automatically detect, localize, and classify entities in your images and videos before handing off the task to our workforce. Automatic labelling reduces workforce costs and allows annotators to spend their time on the more complicated steps of the annotation process. Our video annotation tool is built to handle 4K resolution and long-running videos natively and provides innovative features like interpolation, object proposal, and entity resolution.

Amazon SageMaker JumpStart can help you speed up your machine learning (ML). SageMaker JumpStart gives you access to pre-trained foundation models, pre-trained algorithms, and built-in algorithms to help you with tasks like article summarization or image generation. You can also access prebuilt solutions to common problems. You can also share ML artifacts within your organization, including notebooks and ML models, to speed up ML model building. SageMaker JumpStart offers hundreds of pre-trained models from model hubs such as TensorFlow Hub and PyTorch Hub. SageMaker Python SDK allows you to access the built-in algorithms. The built-in algorithms can be used to perform common ML tasks such as data classifications (images, text, tabular), and sentiment analysis.

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.

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.

Nyckel makes it easy to auto-label images and text using AI. We say ‘easy’ because trying to do classification through complicated AI tools is hard. And confusing. Especially if you don't know machine learning. That’s why Nyckel built a platform that makes image and text classification easy. In just a few minutes, you can train an AI model to identify attributes of any image or text. Our goal is to help anyone spin up an image or text classification model in just minutes, regardless of technical knowledge.

AI can help you create amazing experiences. It can be difficult to design and deliver the perfect customer experience. Adobe Sensei makes it easy with AI and machine learning. It helps you create effortlessly, make informed choices, and target marketing to achieve better results. See our new video to learn more about Adobe Sensei.

Torch is a scientific computing platform that supports machine learning algorithms and has wide support for them. It is simple to use and efficient thanks to a fast scripting language, LuaJIT and an underlying C/CUDA implementation. Torch's goal is to allow you maximum flexibility and speed when building your scientific algorithms, while keeping it simple. Torch includes a large number of community-driven packages for machine learning, signal processing and parallel processing. It also builds on the Lua community. The core of Torch is the popular optimization and neural network libraries. These libraries are easy to use while allowing for maximum flexibility when implementing complex neural networks topologies. You can create arbitrary graphs of neuro networks and parallelize them over CPUs or GPUs in an efficient way.

The machine learning platform that unifies data and orchestrates intelligent behavior among revenue-generating teams. It also delivers out-of the-box attribution and actionable analytics. QFlow.ai processes the gigabytes worth of data that Salesforce.com's activity table stores. To help you win more deals and generate more opportunities, we normalize, trend, or analyze your sales efforts. QFlow.ai uses data engineering for outbound activity reporting. It focuses on one crucial factor: whether they were productive. It also automatically displays critical metrics such as average days between first activity and opp creation, and average days between opp création to close. To understand trends in sales activity and productivity over time, Sales Effort data can either be filtered by a team or an individual.

Machine Learning made simple for everyone The leading Machine Learning platform will take your business to the next level. Get data-driven decisions now! No more cumbersome or expensive solutions. Machine Learning that works. BigML offers a variety of Machine Learning algorithms that are robustly engineered and can be applied across your company to solve real-world problems. You can avoid dependencies on multiple libraries that will increase complexity, maintenance costs, or technical debt in your projects. BigML allows unlimited predictive applications in all industries, including aerospace, automotive and energy, entertainment, financial, financial services, food and healthcare, IoT pharmaceutical, transportation, telecommunications and many more. Supervised Learning: Classification and regression (trees and ensembles, logistic regressions and deepnets), as well as time series forecasting.

Build and deploy deep-learning models for custom use scenarios. Our automated machine-learning process allows customers create powerful AI solutions based on our best-in class models and tailored to their specific challenges. Digital platforms can quickly create custom models that fit their guidelines and requirements. Build large language models to support specialized use cases, such as bots for customer and technical service. Create image classification models for better understanding image libraries, including search, organization and more.

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.

Connect your data to the Engine by uploading a file, or connecting to a database. You can then analyze your data with visualizations or prepare it for machine learning modeling using the data wrangling recipes. Build machine learning models using algorithms such as clustering, classification, or regression. All without writing any code. Discover insights into your data using the feature importance tools, prediction explanations, and what-ifs. Our connectors allow you to make predictions and integrate them into your existing systems.

SparkCognition, an industrial AI company, has created a natural language processing solution that automates the workflows of unstructured data within companies so that humans can concentrate on high-value business decisions. DeepNLP uses machine learning to automate the retrieval, classification, and analysis of information. DeepNLP integrates with existing workflows to allow organizations to respond more quickly to changes in their businesses and get quick answers to specific queries.

AttributeStudio provides multi-attribute seismic interpretation as well as reservoir property prediction software. Integrated software system for seismic data interpretation and integration. It is easy to use. Geoscientists designed the system. Data I/O supports all industrial standard data formats. Comprehensive: Includes both basic interpretation workflows as well as advanced modules to predict reservoir properties using the most recent machine learning algorithms. Recent innovations. Regular updates include the latest innovations in seismic interpretation, visualization, or machine learning. Robust. AttributeStudio was built on a solid, 20-year-old software architecture. Affordable. Only license the modules you use in your work. Licenses for corporate teams are available at a discounted rate. Multiple attributes are required for fault surface tracking. Interactive attribute classification using cross plots in 2D and 3.

SHARK is an open-source C++ machine-learning library that is fast, modular, and feature-rich. It offers methods for linear and unlinear optimization, kernel-based algorithms, neural networks, as well as other machine learning techniques. It is a powerful toolbox that can be used in real-world applications and research. Shark relies on Boost, CMake. It is compatible with Windows and Solaris, MacOS X and Linux. Shark is licensed under the permissive GNU Lesser General Public License. Shark offers a great compromise between flexibility and ease of use and computational efficiency. Shark provides many algorithms from different domains of machine learning and computational intelligence that can be combined and extended easily. Shark contains many powerful algorithms that, to our best knowledge, are not available in any other library.

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.

Folio3 has a dedicated team of Data Scientists and Consultants who have completed end-to-end projects in machine learning, natural language processing and computer vision. Companies can now use highly customized solutions with advanced Machine Learning capabilities thanks to Artificial Intelligence and Machine Learning algorithms. Computer vision technology has revolutionized the way companies use visual content. It has also made it easier to analyze visual data and introduced new functions that are image-based. Folio3's predictive analytics solutions produce fast and effective results that allow you to identify anomalies and opportunities in your business processes.

AWS Trainium, the second-generation machine-learning (ML) accelerator, is specifically designed by AWS for deep learning training with 100B+ parameter model. Each Amazon Elastic Comput Cloud (EC2) Trn1 example deploys up to sixteen AWS Trainium accelerations to deliver a low-cost, high-performance solution for deep-learning (DL) in the cloud. The use of deep-learning is increasing, but many development teams have fixed budgets that limit the scope and frequency at which they can train to improve their models and apps. Trainium based EC2 Trn1 instance solves this challenge by delivering a faster time to train and offering up to 50% savings on cost-to-train compared to comparable Amazon EC2 instances.

A platform for machine learning and deep learning applications that is reproducible and scaleable. Learn more about the products and features that make up today's most innovative platform to manage data science workflows. Polyaxon offers an interactive workspace that includes notebooks, tensorboards and visualizations. You can collaborate with your team and share and compare results. Reproducible results are possible with the built-in version control system for code and experiments. Polyaxon can be deployed on-premises, in the cloud, or in hybrid environments. This includes single laptops, container management platforms, and Kubernetes. You can spin up or down, add nodes, increase storage, and add more GPUs.

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.

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.

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.

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.

Abacus.AI is the first global end-to-end autonomous AI platform. It enables real-time deep-learning at scale for common enterprise use cases. Our innovative neural architecture search methods allow you to create custom deep learning models and then deploy them on our end-to-end DLOps platform. Our AI engine will increase user engagement by at least 30% through personalized recommendations. Our recommendations are tailored to each user's preferences, which leads to more interaction and conversions. Don't waste your time dealing with data issues. We will automatically set up your data pipelines and retrain the models. To generate recommendations, we use generative modeling. This means that even if you have very little information about a user/item, you won't have a cold start.

Data scientists need innovative and efficient turn-key solutions. For quantum engineers, powerful circuit building blocks. Turn-key implementations of algorithms for data scientists, financial analysts, engineers. Explore problems in binary optimization and machine learning on simulators and real hardware. You don't need to have any prior experience in quantum computing. To load classical data into quantum states, use NISQ data loader devices. Circuit building blocks are available for linear algebra with distance estimation or matrix multiplication circuits. You can create your own algorithms using our circuit building blocks. You can get a significant performance boost with D-Wave hardware. Also, the latest gate-based improvements will help you. Quantum data loaders and algorithms offer guaranteed speed-ups in clustering, classification, regression.

Neuton.AI, an automated solution, empowering users to build accurate predictive models and make smart predictions with: Zero code solution Zero need for technical skills Zero need for data science knowledge

AIxBlock is an end-to-end blockchain-based platform for AI that harnesses unused computing resources of BTC miners, as well as all global consumer GPUs. Our platform's training method is a hybrid machine learning approach that allows simultaneous training on multiple nodes. We use the DeepSpeed-TED method, a three-dimensional hybrid parallel algorithm which integrates data, tensor and expert parallelism. This allows for the training of Mixture of Experts models (MoE) on base models that are 4 to 8x larger than the current state of the art. The platform will identify and add compatible computing resources from the computing marketplace to the existing cluster of training nodes, and distribute the ML model for unlimited computations. This process unfolds dynamically and automatically, culminating in decentralized supercomputers which facilitate AI success.

Blue Machine Learning (BlueML), solutions allows you to quickly and easily analyze your open text comments. You can instantly see what is most important to your employees and students, and get more actionable insights that will help you make better decisions. Most comment analysis tools are based on customer experience machine-learning models and use a generic approach. When you look at the student or employee journey, you'll see that there are specific components around learning and experience. BlueML allows you to leverage three specialized models that can accurately analyze and analyze comments from each section of the student and employee journeys. This will allow you to categorize context-specifically. Get a complete view of the sentiments expressed by students and employees (very negative, very negative, neutral, positive or very positive), as well as their context-specific categorization. Learn about the emotions students and employees have expressed in comments.

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.

Elastic Fabric Adapter is a network-interface for Amazon EC2 instances. It allows customers to run applications that require high levels of internode communication at scale. Its custom-built OS bypass hardware interface improves the performance of interinstance communications which is crucial for scaling these applications. EFA allows High-Performance Computing applications (HPC) using the Message Passing Interface, (MPI), and Machine Learning applications (ML) using NVIDIA's Collective Communications Library, (NCCL), to scale up to thousands of CPUs and GPUs. You get the performance of HPC clusters on-premises, with the elasticity and flexibility on-demand of AWS. EFA is a free networking feature available on all supported EC2 instances. Plus, EFA works with the most common interfaces, libraries, and APIs for inter-node communication.

Machine learning models can be deployed at scale with greater accuracy. With more models in production, R&D can be turned into ROI. Seldon reduces time to value so models can get to work quicker. Scale with confidence and minimize risks through transparent model performance and interpretable results. Seldon Deploy cuts down on time to production by providing production-grade inference servers that are optimized for the popular ML framework and custom language wrappers to suit your use cases. Seldon Core Enterprise offers enterprise-level support and access to trusted, global-tested MLOps software. Seldon Core Enterprise is designed for organizations that require: - Coverage for any number of ML models, plus unlimited users Additional assurances for models involved in staging and production - You can be confident that their ML model deployments will be supported and protected.

Amazon EC2 UltraClusters allow you to scale up to thousands of GPUs and machine learning accelerators such as AWS trainium, providing access to supercomputing performance on demand. They enable supercomputing to be accessible for ML, generative AI and high-performance computing through a simple, pay-as you-go model, without any setup or maintenance fees. UltraClusters are made up of thousands of accelerated EC2 instance co-located within a specific AWS Availability Zone and interconnected with Elastic Fabric Adapter networking to create a petabit scale non-blocking network. This architecture provides high-performance networking, and access to Amazon FSx, a fully-managed shared storage built on a parallel high-performance file system. It allows rapid processing of large datasets at sub-millisecond latency. EC2 UltraClusters offer scale-out capabilities to reduce training times for distributed ML workloads and tightly coupled HPC workloads.

A neuro-bio inspired generic deep-learning algorithm was developed that is as simple as an intelligence test. It automatically detects patterns and predicts them, allowing you to easily create intelligent apps. Our software is simple to use due to its REST API which allows you to create intelligent apps in any environment. This allows you to connect e.g. You can connect e.g., JavaScript applications, spreadsheets, or your online broker. Our service is available for testing and development purposes. Our community edition is open-source licensed under SSPL. Vanillatech ML Workstation can be used on any local computer. For a customized offer, please contact us if you need any modifications or support.

From materials data to better product faster! Accelerates R&D, scales up, and optimizes manufacturing quality control and supply chain decisions. Use ML guidance to predict outcomes and discover new materials. Get faster and better results. You can build a model as you go. To design cost-effective and robust production lines, test the limits of your model. Models can be used to predict future failures using information from the materials and parameters of the production line. Materials Zone is a platform that aggregates data from independent entities, material providers, factories, and manufacturing facilities and allows them to communicate through a secure platform. Machine learning (ML) algorithms can be applied to your experimental data to discover new materials, create'recipes' that allow you to synthesize materials, analyze unique measurements, and retrieve insights.

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.