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In a 24-criteria evaluation of notebook-based predictive analytics and machine learning (PAML) solutions providers, Oracle was recognized as a leader (Q3 2018).
Oracle Cloud Infrastructure Data Science enables data science teams to easily organize their work and access data and computing resources. Building, training, deployment, and model management are all powered via Oracle Cloud for easy access. The platform makes data science teams more productive, resulting in faster deployment and ultimately a more robust organization powered by machine learning.
Oracle Cloud Infrastructure Data Science enables data scientists to easily build, train, deploy, and manage machine learning models on Oracle Cloud. Teams of data scientists can easily organize their work and access data and computing resources in a collaborative environment. The platform makes data science teams more productive, decreasing time to value, and ultimately creating a more robust business, powered by machine learning.
Oracle Cloud Infrastructure Data Science is a collaboration 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, train, save, and deploy models, while utilizing the rich Python ecosystem as well as Oracle’s proprietary Python libraries.
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.
See how NHS Business Services Authority is using Oracle's products to improve patient care.
See how DX Marketing improved customer efficiency and internal processes with Oracle's products.
Accenture on leveraging AI with clients thanks to Oracle's products.
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...