From Deep Learning Patterns and Practices by Andrew Ferlitsch
This article covers:
Feeding models training data in a production environment.
Scheduling for continuous retraining.
Using version control and evaluating models before and after deployment.
Deploying models for large scale on-demand and batch requests, in both monolithic and distributed deployments.
From Deep Learning Patterns and Practices by Andrew Ferlitsch
This article covers:
● Feeding models training data in a production environment.
● Scheduling for continuous retraining.
● Using version control and evaluating models before and after deployment.
● Deploying models for large scale on-demand and batch requests, in both monolithic and distributed deployments.
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.
| 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. |
From API Security in Action by Neil Madden
In this article, you’ll implement capability-based access control techniques that enable secure sharing by taking the principle of least authority (POLA) to its logical conclusion and allowing fine-grained control over access to individual resources. Along the way, you’ll see how capabilities prevent a general category of attacks against APIs known as confused deputy attacks.
From JavaScript on Things
By Lyza Danger Gardner
From JavaScript on Things by Lyza Danger Gardner
This article is about using JavaScript for amazing and fun hardware projects.
Chapters selected by Dominique D. Guinard and Vlad M. Trifa.
By Dominique D. Guinard and Vlad M. Trifa authors of Building the Web of Things
In this article, we define the Internet of Things and its limitations and describe how the Web of Things can.
The Limitations of the IoT and how the Web of Things Can Help (PDF)