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What is Oracle Data Science?
A productivity-boosting data science platform presents exceptional features that streamline the crafting and evaluation of advanced machine learning (ML) models. By quickly utilizing data that businesses trust, organizations can enjoy enhanced flexibility and achieve their data-centric objectives through more straightforward ML model deployment. Cloud-based solutions empower companies to efficiently discover valuable insights that can shape their strategies. The process of building a machine learning model is inherently cyclical, and this ebook thoroughly explains each phase of its development. Users can interact with notebooks to create or assess a variety of machine learning algorithms, allowing for a hands-on learning experience. Engaging with AutoML not only leads to remarkable results in data science but also enables the swift generation of high-quality models with minimal effort. Additionally, automated machine learning techniques efficiently scrutinize datasets, suggesting the most effective features and algorithms while optimizing models and clarifying their outcomes. This holistic approach guarantees that organizations can fully exploit their data, fostering innovation and facilitating well-informed decision-making. Ultimately, adopting such advanced tools can significantly transform how businesses leverage data, setting them on a path toward lasting success.
What is Azure Data Science Virtual Machines?
Data Science Virtual Machines (DSVMs) are customized images of Azure Virtual Machines that are pre-loaded with a diverse set of crucial tools designed for tasks involving data analytics, machine learning, and artificial intelligence training. They provide a consistent environment for teams, enhancing collaboration and sharing while taking full advantage of Azure's robust management capabilities. With a rapid setup time, these VMs offer a completely cloud-based desktop environment oriented towards data science applications, enabling swift and seamless initiation of both in-person classes and online training sessions. Users can engage in analytics operations across all Azure hardware configurations, which allows for both vertical and horizontal scaling to meet varying demands. The pricing model is flexible, as you are only charged for the resources that you actually use, making it a budget-friendly option. Moreover, GPU clusters are readily available, pre-configured with deep learning tools to accelerate project development. The VMs also come equipped with examples, templates, and sample notebooks validated by Microsoft, showcasing a spectrum of functionalities that include neural networks using popular frameworks such as PyTorch and TensorFlow, along with data manipulation using R, Python, Julia, and SQL Server. In addition, these resources cater to a broad range of applications, empowering users to embark on sophisticated data science endeavors with minimal setup time and effort involved. This tailored approach significantly reduces barriers for newcomers while promoting innovation and experimentation in the field of data science.
Integrations Supported
Anaconda
Apache Spark
Azure Blob Storage
Azure Machine Learning
Azure Marketplace
Jupyter Notebook
MLflow
Microsoft 365
Microsoft Azure
Microsoft Cognitive Toolkit
Integrations Supported
Anaconda
Apache Spark
Azure Blob Storage
Azure Machine Learning
Azure Marketplace
Jupyter Notebook
MLflow
Microsoft 365
Microsoft Azure
Microsoft Cognitive Toolkit
API Availability
Has API
API Availability
Has API
Pricing Information
Pricing not provided.
Free Trial Offered?
Free Version
Pricing Information
$0.005
Free Trial Offered?
Free Version
Supported Platforms
SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux
Supported Platforms
SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux
Customer Service / Support
Standard Support
24 Hour Support
Web-Based Support
Customer Service / Support
Standard Support
24 Hour Support
Web-Based Support
Training Options
Documentation Hub
Webinars
Online Training
On-Site Training
Training Options
Documentation Hub
Webinars
Online Training
On-Site Training
Company Facts
Organization Name
Oracle
Date Founded
1977
Company Location
United States
Company Website
www.oracle.com/data-science/
Company Facts
Organization Name
Microsoft
Date Founded
1975
Company Location
United States
Company Website
azure.microsoft.com/en-us/services/virtual-machines/data-science-virtual-machines/
Categories and Features
Data Science
Access Control
Advanced Modeling
Audit Logs
Data Discovery
Data Ingestion
Data Preparation
Data Visualization
Model Deployment
Reports
Machine Learning
Deep Learning
ML Algorithm Library
Model Training
Natural Language Processing (NLP)
Predictive Modeling
Statistical / Mathematical Tools
Templates
Visualization
Categories and Features
Data Science
Access Control
Advanced Modeling
Audit Logs
Data Discovery
Data Ingestion
Data Preparation
Data Visualization
Model Deployment
Reports