OpenCV Edge Detection¶
This example does edge detection using OpenCV. This is our canonical starter demo. If you haven’t used Pachyderm before, start here. We’ll get you started running Pachyderm locally in just a few minutes and processing sample log lines.
Word Count (Map/Reduce)¶
Word count is basically the “hello world” of distributed computation. This example is great for benchmarking in distributed deployments on large swaths of text data.
Periodic Ingress from a Database¶
This example pipeline executes a query periodically against a MongoDB database outside of Pachyderm. The results of the query are stored in a corresponding output repository. This repository could be used to drive additional pipeline stages periodically based on the results of the query.
Iris flower classification with R, Python, or Julia¶
The “hello world” of machine learning implemented in Pachyderm. You can deploy this pipeline using R, Python, or Julia commponents, where the pipeline includes the trianing of a SVM, LDA, Decision Tree, or Random Forest model and the subsequent utilization of that model to perform inferences.
Sentiment analysis with Neon¶
This example implements the machine learning template pipeline discussed in this blog post. It trains and utilizes a neural network (implemented in Python using Nervana Neon) to infer the sentiment of movie reviews based on data from IMDB.