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

These guides clearly break down 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.

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#.

AI/ML Videos

Building Intelligent Apps

Ready to get started? Here’s a sampling of resources to help you address specific ML/AI development challenges.

Machine Learning Fundamentals

Use these resources for a foundation in the basics of ML and AI and their roles in application development.