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Feature Engineering (23 results) showing 1 - 20
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ByIguazio | Ver MLRun Kit 0.1.11
The Iguazio AI Platform provides a complete AI workflow in a single ready-to-use platform that includes all the required building blocks for building, deploying, operationalizing, scaling and de-risking ML and GenAI applications in live business environments. If you need access to our Enterprise of... | |
ByMarlabs Inc | Ver V1.0
mAdvisor is an AutoML platform that translates data from enterprise systems into meaningful insights & predictions in the form of narratives without any manual intervention. AutoML gives users the power of cognitive technologies like machine learning, machine reasoning, deep learning, natural... | |
ByQRI SpeedWise Waterflood Management (SWM) is a revolutionary cloud-native SaaS solution for asset teams looking to optimize waterflood operations. SWM combines the fundamentals of subsurface flow physics with advanced data-driven techniques to quickly build waterflood models based on available... | |
ByQRI Discover the power of SpeedWise® Reservoir Opportunity (SRO), an AI-powered, cloud-native platform that is revolutionizing complex geological and engineering workflows. Through advanced computational algorithms and data mining techniques, SRO can automatically create a ranked list of field... | |
ByMphasis | Ver 1.1 Quantum Feature Selecton is hyrbid quantum computing approach to optimize feature selection in artificial intelligence/machine learning (AI/ML) model training and prediction. This solution approaches feature selection as an optimization problem and selects the most critical variables and eliminates... | |
ByOrganon Analytics | Ver autonon_afe_1.0.1 Automated Feature Extraction (AFE) enables the creation of automated and supervised extraction of an optimal set of predictive features from transactional datasets without human effort. It helps to transform temporal and relational datasets into feature matrices for modeling. The user just needs to... | |
BySlalom In today’s technology-forward environment, companies of all types face a variety of obstacles in delivering relevant, significant, and valuable products. Customers and employees expect seamless experiences at every touchpoint, and the complexities of meeting changing demands are higher than ever... | |
ByMphasis | Ver 1.8 The solution runs machine learning related feature selection operations on the input data. This will simplify the task of feature selection for a data scientist where the user will have to specify few selected parameters to generate the correct output instead of writing specific code for each... | |
ByMphasis | Ver 2.1 The solution will provide machine learning related feature engineering as output for the user provided data. The feature engineering operations to execute on the data can be specified by user in a separate config file. This will simplify the task of feature engineering for a data scientist where in... | |
ByMphasis | Ver 3.0 Categorical Missing Data Imputation is a robust deep learning based solution. This solution fills in missing values for categorical attributes by identifying data patterns in the input dataset. It helps reduce the data quality issues due to incomplete / non-available data. | |
ByMphasis | Ver 3.7 Missing Data Imputation is a robust neural network based solution. This solution fills in missing values for numerical attributes by identifying data patterns in the input dataset. It helps reduce the data quality issues due to incomplete/non-available data. | |
Byi4cast LLC | Ver 0.1.0
The Dynamic Factor Variance-Covariance Model (DFVCM) makes multi-step forecasts of multivariate volatilities of a large number time-series (e.g. those of numerous investable assets in many markets) by applying dynamic factor model (DFM). The multi-step forecasts of multivariate volatilities are com... | |
ByChalk The data platform for machine learning. Tired of Spark? So are we. Just-in-time data + Hot-reload + Rust compute Chalk is a data platform that powers machine learning and generative AI. Chalk's best-in-class developer experience enables data teams to declare features and their dependencies with idi... | |
ByChalk The data platform for machine learning. Tired of Spark? So are we. Just-in-time data + Hot-reload + Rust compute Chalk is a data platform that powers machine learning and generative AI. Chalk's best-in-class developer experience enables data teams to declare features and their dependencies with idi... | |
BydotData dotData Cloud is a fully-managed service offering a comprehensive suite of dotData products with full support, infrastructure, and management. Businesses can leverage dotData’s proprietary AI to automatically analyze diverse, multi-table datasets—structured and unstructured, including numeric,... | |
ByLentra Cadenz Profiles is an AI-driven Customer Intelligence Platform that streamlines historical and current customer records for financial institutions. Seamlessly integrating with multiple channels, it provides unified Single Customer View (SCV) by combining behavioral intelligence data with factual... | |
AgilePod Flexible Engineering Services are designed to adapt to your project's needs, providing rapid deployment and skilled engineering teams to ensure successful and timely cloud project delivery on AWS. | |
Workbench makes AWS both easier to use and more powerful. It handles all the details around updating and managing a complex set of AWS Services. With a simple-to-use Python API and a beautiful set of web interfaces, Workbench makes creating AWS ML pipelines a snap. It also dramatically improves... | |
ByTurboML TurboML is a machine learning platform that's reinvented for real-time. What does that mean? All the steps in the ML lifecycle, from data ingestion, to feature engineering, to ML modelling to post deployment steps like monitoring, are all designed so that in addition to batch data, they can also... | |
PROJECT BACKGROUND Machine learning plays an increasingly important role in unlocking the ability to extract actionable insights from complex datasets across a broad range of fields. The collection of ever-increasing amounts of data brings new challenges in data management, preparation, model train... |