Learn Machine Learning in a way that is accessible to absolute beginners. You will learn the basics of Machine Learning and how to use TensorFlow to implement many different concepts. Google provided a grant to make this course possible.

Artificial intelligence affects more than just computer science. Join this session to hear a collection of short presentations from top machine learning researchers: the TensorFlow engineers working on robotics, and the Magenta team exploring the border between machine learning and art. See all the sessions from Google I/O '18 here https://goo.gl/q1Tr8x

I've been making some TensorFlow examples for my website, fomoro.com, While it's fresh in my head, I wanted to write up an end-to-end description of what it's like to build a machine learning app, and more specifically, how to make your own reverse image search. For this demo, the work is ⅓ data munging/setup, ⅓ model development and ⅓ app development. At a high-level, I use TensorFlow to create an autoencoder, train it on a bunch of images, use the trained model to find related images, and display them with a Flask app. In the last post, I talked model development and training.

I've been making some TensorFlow demos for my website, fomoro.com, While it's fresh in my head, I wanted to write up an end-to-end description of what it's like to build a machine learning app, and more specifically, how to make your own reverse image search. For this demo, the work is ⅓ data munging/setup, ⅓ model development and ⅓ app development. At a high-level, I use TensorFlow to create an autoencoder, train it on a bunch of images, use the trained model to find related images, and display them with a Flask app. In this first post, I'm going to go over my environment and project setup and do a little bit of scaffolding.