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Artificial Intelligence (AI) and Machine Learning (ML) for Developers
Take your project to new heights by letting data tell the story.
OCI AI and Machine Learning Services
Reference architectures
AI and ML services can get complicated. These guides clearly breakdown the moving parts so that you can feel confident in your project.
Hands-on labs
Actively engage with AI and ML with a “learn by doing” approach using these beginner-friendly guides.
AI/ML Videos
Mining Structured and Unstructured Data (37:00)
Fraud and Anomaly Detection using Oracle Advanced Analytics Part 1 Concepts (11:02)
Naked Future: What Happens in a World That Anticipates Your Every Move (49:00)
Open Source Tools
Jupyter
JupyterLab is a web-based interactive development environment for Jupyter notebooks, code, and data.
GraphPipe
GraphPipe is a protocol and collection of software designed to simplify machine learning model deployment and decouple it from framework-specific model implementations.
TensorFlow
TensorFlow is an end-to-end open source platform for machine learning.
Apache SINGA
Apache SINGA is an Apache Top Level Project, focusing on distributed training of deep learning and machine learning models.
Shogun
Shogun is an open-source machine learning library that offers a wide range of efficient and unified machine learning methods.
Apache Mahout
Apache Mahout is a distributed linear algebra framework and mathematically expressive Scala DSL designed to let mathematicians, statisticians, and data scientists quickly implement their own algorithms.
Apache Spark MLlib
MLlib is Apache Spark's scalable machine learning library.
Oryx 2
Oryx 2 is a realization of the lambda architecture built on Apache Spark and Apache Kafka, but with specialization for real-time large scale machine learning.
Accord.NET Framework
The Accord.NET Framework is a .NET machine learning framework combined with audio and image processing libraries completely written in C#.
Building Intelligent Apps
Ready to get started? Here’s a sampling of resources to help you address specific ML/AI development challenges.
- Machine Learning in Oracle Database-Classification of Conference Abstracts based on Text Analysis
- Developing Chatbots with Oracle Mobile Cloud
- Classification-Machine Learning Chatbot with TensorFlow
- Linear Regression-Machine Learning with TensorFlow and Oracle JET UI Explained
- Machine Learning Applied-TensorFlow Chatbot UI with Oracle JET Custom Component
- Promote Standards to Create Great APIs
Machine Learning Fundamentals
Use these resources for a foundation in the basics of ML and AI and their roles in application development.