Your search did not match any results.
We suggest you try the following to help find what you're looking for:
AI and ML services can get complicated. These guides clearly breakdown the moving parts so that you can feel confident in your project.
Actively engage with AI and ML with a “learn by doing” approach using these beginner-friendly guides.
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)
JupyterLab is a web-based interactive development environment for Jupyter notebooks, code, and data.
GraphPipe is a protocol and collection of software designed to simplify machine learning model deployment and decouple it from framework-specific model implementations.
TensorFlow is an end-to-end open source platform for machine learning.
Apache SINGA is an Apache Top Level Project, focusing on distributed training of deep learning and machine learning models.
Shogun is an open-source machine learning library that offers a wide range of efficient and unified machine learning methods.
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.
MLlib is Apache Spark's scalable machine learning library.
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.
The Accord.NET Framework is a .NET machine learning framework combined with audio and image processing libraries completely written in C#.
Ready to get started? Here’s a sampling of resources to help you address specific ML/AI development challenges.