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Oracle Cloud Infrastructure Data Science is an enterprise grade data science service where teams of data scientists can collaborate to build, train, and deploy machine learning models.
Cloud-based machine learning can quickly discover new business insights. Find out how with the new free ebook, Getting Started With Machine Learning in the Cloud.
The interdisciplinary field of data science comes with many challenges across a spectrum of users. Oracle's data science family is built to make data science easier for every user—from data scientists to business users to IT departments. With Oracle, streamlined processes make it easier for users to access data, collaborate with teams to build models, and realize the full value of their data.
Oracle Cloud Infrastructure Data Science is a collaborative platform for data scientists to build and manage ML models. Leveraging open source technology, it provides a scalable cloud-based platform for data scientists to explore data and train, save, and deploy models, while utilizing the rich Python ecosystem as well as Oracle’s proprietary Python libraries.
Oracle Analytics Cloud delivers cutting-edge visualization, augmented analysis, and natural language processing through an easy-to-use interface. Powered by AI and machine learning, Oracle Analytics Cloud makes it possible for any level of user to generate deep insights and create forward-thinking reports.
Oracle Database’s Machine Learning capabilities bring the latest automation and self-learning tools to the database space. The result is an experience that's both powerful and user-friendly. Using Oracle's tools, it's easier than ever to manage data and support application development on a secure and scalable infrastructure.
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Paysafe identifies fraud and minimizes risk with Oracle's graph analytics and database solutions. It now has the tools for fast queries, improved customer experience, and a way to detect fraudulent transactions in just minutes instead of days.
Exelon IT Principal Architect Kumar Thakur discusses how this Fortune 100 utilities company plans to reach millions of its customers using Oracle's AI-driven chatbots.
K-means clustering is a type of unsupervised learning, which is used when you have unlabeled data (i.e., data without defined categories or groups). The goal of this algorithm is to find groups in the data, with the number of groups represented by the variable K. The algorithm works iteratively to...
This tutorial will provide a step-by-step guide for fitting an ARIMA model using R. ARIMA models are a popular and flexible class of forecasting model that utilize historical information to make predictions. This type of model is a basic forecasting technique that can be used as a foundation for...
Moving from machine learning to time-series forecasting is a radical change—at least it was for me. As a data scientist, I worked for almost a year developing machine learning models. It was a challenging, yet enriching, experience that gave me a better understanding of...