Google TensorFlow

posted Feb 19, 2016, 12:56 PM by Chris G   [ updated Oct 21, 2017, 7:51 AM ]

Google releases Deep Learning framework TensorFlow as open-source

Machine learning powers many Google product features, from speech recognition in the Google app to Smart Reply in Inbox to search in Google Photos. While decades of experience have enabled the software industry to establish best practices for building and supporting products, doing so for services based upon machine learning introduces new and interesting challenges.

Today, we announce the release of TensorFlow Serving, designed to address some of these challenges. TensorFlow Serving is a high performance, open source serving system for machine learning models, designed for production environments and optimized for TensorFlow.

TensorFlow Serving is ideal for running multiple models, at large scale, that change over time based on real-world data

Teach Yourself Deep Learning with TensorFlow and Udacity

The course consists of four lectures which provide a tour of the main building blocks that are used to solve problems ranging from image recognition to text analysis. The first lecture focuses on the basics that will be familiar to those already versed in machine learning: setting up your data and experimental protocol, and training simple classification models. The second lecture builds on these fundamentals to explore how these simple models can be made deeper, and more powerful, and explores all the scalability problems that come with that, in particular regularization and hyperparameter tuning. The third lecture is all about convolutional networks and image recognition. The fourth and final lecture explore models for text and sequences in general, with embeddings and recurrent neural networks. By the end of the course, you will have implemented and trained this variety of models on your own machine and will be ready to transfer that knowledge to solve your own problems!