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The Iguazio Data Science & MLOps Platform provides a complete data science workflow in a single ready-to-use platform that includes all the required building blocks for creating data science applications
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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...
Algorithm - Fulfilled on Amazon SageMaker
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...
Model Package - Fulfilled on Amazon SageMaker
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.
Model Package - Fulfilled on Amazon SageMaker
This trial version of Kaskada's time-based feature engine unleashes instant iteration on what feature definitions are and when training examples are observed -- with data-dependent, entity-specific computations. At a high-level Kaskada is a feature engine that allows you to connect directly to...
Linux/Unix, Amazon Linux Amazon Linux 2 Kernel 5.10 AMI 2.0.20220606.1 - 64-bit Amazon Machine Image (AMI)
Customer Genomics is our inhouse built platform for powering customer decisioning with intelligence @speed and scale. It executes next best experience recommendations at every stage of a customer’s relationship journey with client businesses.Over the last 6-7 years we have solved personalization...
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.
Model Package - Fulfilled on Amazon SageMaker
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...
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...
Model Package - Fulfilled on Amazon SageMaker
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