Unleash the Power of AI and Machine Learning in Oracle Analytics Cloud
Table of Contents:
- Introduction
- Overview of Oracle Analytics Cloud
- Machine Learning in Oracle Analytics Cloud
- Business Users vs. Developer Style Interfaces
- Integrating Models Created in Python
- Oracle OCI AI Services Integrations
- AI and ML Capabilities in Oracle Analytics Cloud
- Vision Services for Image Classification and Object Detection
- Document Understanding Services for Text Extraction and Classification
- Automl in Oracle Analytics Cloud
- Training and Applying Machine Learning Models
- Pre-trained Models vs. Custom Models
- Integrating the Oracle OCI AI Platform in Analytics Applications
- Conclusion
Introduction
Welcome to this session on Oracle Analytics Cloud, where we will explore the AI and ML capabilities within the platform. In this article, we will provide an overview of Oracle Analytics Cloud and its integration with the Oracle OCI AI platform. We will discuss the different machine learning capabilities available in Oracle Analytics Cloud, including the use of pre-trained models, custom models, and the Automl feature. Additionally, we will explore the vision services for image classification and object detection, as well as the document understanding services for text extraction and classification. By the end of this article, you will have a better understanding of how Oracle Analytics Cloud leverages AI and ML to provide powerful analytics capabilities. Let's dive in!
Overview of Oracle Analytics Cloud
Oracle Analytics Cloud (OAC) is a comprehensive end-to-end platform for all analytical workloads. The platform supports a wide range of data sources, including major databases and legacy sources. With OAC, users have the ability to prepare data directly within the platform without the need for exporting it to external tools. OAC also provides modeling capabilities, allowing users to create their own models or utilize pre-built models for enterprise-wide use. Once the data and models are in place, users can explore the information and gain insights using various analytical tools. The insights can then be shared with colleagues and peers for data-driven decision-making. With features like data stories and mobile device compatibility, OAC offers multiple ways to Consume these insights. The platform also integrates with Oracle OCI AI services, providing even more advanced AI and ML capabilities.
Machine Learning in Oracle Analytics Cloud
In Oracle Analytics Cloud, machine learning is a key component of the platform's capabilities. The platform caters to the needs of both business users and developers, offering a range of interfaces to suit different skill levels. Business users can take advantage of no-code interfaces for easy modeling and analysis, while developers can leverage integration with Python and other programming languages to build more complex models. The platform also integrates with Oracle OCI AI services, such as vision services and document understanding services, to enhance the ML capabilities. This integration allows for the use of pre-built AI models and custom models to address specific business needs. By leveraging the AI and ML capabilities of Oracle Analytics Cloud, users can achieve more advanced analytics-driven insights and make data-driven decisions.
Business Users vs. Developer Style Interfaces
Oracle Analytics Cloud addresses the needs of both business users and developers by providing different interfaces. Business users can utilize no-code interfaces, which are user-friendly and require no programming knowledge. These interfaces allow business users to easily create and explore models, empowering them to gain insights from their data without the need for technical expertise. On the other HAND, developers can make use of developer-style interfaces that support integration with programming languages like Python. This gives developers the flexibility to use their preferred tools and build more advanced models, such as those created in Python. With these interfaces, Oracle Analytics Cloud caters to the diverse skill sets and requirements of its users.
Integrating Models Created in Python
For users who prefer to build models using Python and other programming languages, Oracle Analytics Cloud offers integration capabilities. With this integration, developers can leverage their existing models and easily integrate them into the analytics workflow within the platform. This allows for seamless collaboration between business users and developers, ensuring that everyone has access to the most accurate and up-to-date models. The ability to integrate external models provides users with greater flexibility and allows them to leverage the power of Python for advanced analytics and machine learning tasks.
Oracle OCI AI Services Integrations
Oracle Analytics Cloud also integrates with the Oracle OCI AI services to enhance the AI and ML capabilities of the platform. The OCI AI services provide a range of powerful AI capabilities, including vision services and document understanding services. These services can be used to perform tasks such as image classification, object detection, text extraction, and document classification. By integrating these services into Oracle Analytics Cloud, users can leverage pre-built AI models and APIs to enhance their analytical workflows. This integration enables users to extract valuable insights from their data and make data-driven decisions more effectively.
AI and ML Capabilities in Oracle Analytics Cloud
In Oracle Analytics Cloud, AI and ML capabilities are a fundamental part of the platform. These capabilities empower users to gain deeper insights from their data and make more accurate predictions. The platform provides various AI services, including vision services for image classification and object detection, and document understanding services for text extraction and classification.
Vision Services for Image Classification and Object Detection
Oracle Analytics Cloud leverages vision services to perform tasks such as image classification and object detection. With image classification, users can train models to accurately classify images into different categories. This can be useful in a variety of applications, such as analyzing product images or identifying objects in images.
Object detection is another powerful capability provided by vision services. It enables users to detect and locate specific objects within an image, and even draw bounding boxes around these objects. This can be valuable in applications such as security surveillance, where the identification of objects is crucial.
By utilizing the vision services in Oracle Analytics Cloud, users can enhance their data analysis and gain valuable insights from visual data.
Document Understanding Services for Text Extraction and Classification
Oracle Analytics Cloud also incorporates document understanding services to extract meaning from documents. These services allow users to extract text from documents, classify documents based on their content, and extract key-value pairs from structured documents.
Text extraction enables users to quickly extract Relevant information from documents, such as identifying names, addresses, or other important text-based data. This can be particularly useful in scenarios where large amounts of unstructured data need to be processed.
Document classification is another essential feature that allows users to automatically categorize documents based on their content. This can help streamline processes such as document management and improve the efficiency of data analysis.
With the document understanding services in Oracle Analytics Cloud, users can unlock the insights Hidden within their documents and leverage them for data-driven decision-making.
Automl in Oracle Analytics Cloud
Automl is a powerful feature in Oracle Analytics Cloud that simplifies the process of training and applying machine learning models. With Automl, users can easily create and deploy accurate models without extensive knowledge of machine learning algorithms.
Training a machine learning model typically involves selecting a technique, choosing an algorithm, and tuning the model to achieve the best accuracy. Automl automates this process by exploring multiple algorithms and selecting the most efficient one for the chosen technique. This saves time and effort in model development and eliminates the need for manual experimentation.
Once a model is trained using Automl, it can be applied to new data sets for prediction. Users can conveniently apply the model within data flows, allowing for seamless integration with regular data analysis workflows. This ensures that users can continuously leverage the power of machine learning to gain insights from their data.
Automl also supports the use of pre-trained models and custom models, offering users flexibility in their model creation. Whether utilizing pre-trained models for common tasks or developing custom models for specific business needs, Automl in Oracle Analytics Cloud provides a Simplified and efficient way to leverage machine learning capabilities.
Conclusion
In this article, we explored the AI and ML capabilities within Oracle Analytics Cloud (OAC). We discussed how OAC caters to both business users and developers with its user-friendly interfaces and integration with programming languages like Python. We also showcased the integration of Oracle OCI AI services into OAC, including vision services for image classification and object detection, as well as document understanding services for text extraction and classification. Additionally, we discussed the Automl feature in OAC, which automates the process of training and applying machine learning models. By leveraging these AI and ML capabilities, users can enhance their data analysis, gain valuable insights, and make data-driven decisions more effectively. With Oracle Analytics Cloud, users can harness the power of AI and ML to drive innovation and achieve business success.
Resources:
FAQ:
Q: Can I use Oracle Analytics Cloud with a small budget?
A: Yes, Oracle Analytics Cloud offers cost-effective options, and the basic features can be accessed with a named user professional edition license.
Q: Are the AI and ML capabilities in Oracle Analytics Cloud user-friendly?
A: Yes, Oracle Analytics Cloud provides user-friendly interfaces for business users, as well as integration capabilities for developers.
Q: Can I use pre-trained models in Oracle Analytics Cloud?
A: Yes, Oracle Analytics Cloud supports the use of pre-trained models, which can be easily integrated into the analytics workflow.
Q: Can I integrate Python models into Oracle Analytics Cloud?
A: Yes, Oracle Analytics Cloud allows for the integration of models created in Python and other programming languages.
Q: What are the pricing options for the AI and ML capabilities in Oracle Analytics Cloud?
A: The pricing for the AI and ML capabilities in Oracle Analytics Cloud varies based on usage. The cost estimator tool can provide an estimate based on specific requirements.
