Machine Learning as a Pipeline

From Deep Learning Patterns and Practices by Andrew Ferlitsch

Like the best software engineering, modern deep learning uses a pipeline architecture based on reusable patterns.

When Machine Learning Becomes Machine Design: new paradigms and patterns for automated deep learning

Andrew Ferlitsch reveals new paradigms–and patterns–for automated deep learning

Andrew Ferlitsch, from the developer relations team at Google Cloud AI, is so far out on the cutting edge of machine learning and artificial intelligence that he has to invent new terminology to describe what’s happening in Cloud AI with Google Cloud’s enterprise clients. In this interview with editors at Manning Publications, he talks about the current and coming changes in machine learning systems, starting with the concept of model amalgamation. Ferlitsch is currently writing a book, Deep Learning Design Patterns, which collects his ideas along with the most important composable model components.

Read more author interviews here

Call or Pass?

From Five Lines of Code by Christian Clausen

This article delves into when a function should call a method on an object or pass it on as an argument.

Refactor code like a pro

From Five Lines of Code by Christian Clausen

The World of SOA Patterns

You might not even agree with an SOA-based approach, but are perhaps forced into using it based on someone else’s decision. Alternatively, you may think that SOA is the greatest thing since sliced bread. This article from SOA Patterns explains patterns that will help you make the right decisions for the particular challenges and requirements you’ll face in your SOA projects.

The World of SOA Patterns (PDF)

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