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Oracle announced the availability of Cloud Data Science Platform. Entering into the cloud computing industry Oracle is meant to face extremely high competition form the players like AWS, Azure, GCP, and IBM Cloud.
This will be a comprehensive collection of services that comprises of a data catalogue, machine learning Cloudera Hadoop and Apache Spark distributions on Oracle Cloud Infrastructure (OCI). Oracle further added that the key differentiating factor for this thing is the feature of team collaboration and stringent integration with the variety of data sources available in OCI.
Oracle Cloud Data Science Platform has a Jupyter notebooks supporting cloud for building and deploying machine learning models. Which will allow developers and data scientists in creating a notebook session on a Virtual Cloud Network (VCN) with appropriate permissions where they can access data from Autonomous Data Warehouse (ADW). In fact, data scientists can use other similar libraries like Pandas to fetch data from the ADW for performing exploratory data analysis and visualization. Allowing user to extract predictive data keeping the data warehouse into the loop which can be used even for the historical data.
Oracle Autonomous Database has firmly integrated the machine learning algorithms for Python and AutoML. When Oracle Cloud Infrastructure Data Science is fully integrated with the Autonomous Database that can allow data scientists to develop models using both open source and scalable in-database algorithms.
Oracle also has added AutoML capabilities to the data science platforms. This automates algorithm selection and tuning which automates the process of running tests against multiple algorithms and hyperparameter configurations. This automated feature simplifies various other features like engineering by automatically identifying key predictive features from bigger datasets. Organizations, thus, can choose the best model depending upon a comprehensive model evaluation process that uses multiple evaluation metrics.
Oracle has emphasized on the explainability of the models where the Oracle Cloud Infrastructure Data Science is providing an automated explanation of relative weighting and importance of those factors that can help in generating predictions. Oracle has further claimed that its platform offers the industry"s first commercial implementation of model-agnostic explanation. Like a data scientist dealing with fraud, detection model can explain factors that drive fraud pushing the businesses & organizations to change their process to safeguard.
Adding upon the features of Oracle Cloud Data Science Platform it further is backed by the GPUs, Oracle Big Data Service based on full Cloudera Hadoop implementation. It is a data catalogue allowing users to discover, explore organize enrich and trace the data assets on their cloud.
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