Dyad X Machina is a research partnership that combines affective neuroscience and deep learning. In this episode, Laurence meets with the co-founder,  Haohan Wang, who explains Dyad’s mission as bringing emotion into machine learning.

Watch to learn more about the intersection of deep learning and affective computing and Haohan’s four P’s of learning.

Machine learning models, especially deep learning ones, can be complex.

In this video from QCon.ai 2018, Chi Zeng walks us through how to debug, monitor, and examine the decisions of a TensorFlow-based model using the TensorBoard suite of visualizations.

Chi Zeng works on the TensorBoard suite of visualizations within Google Brain.

Here’s an interesting interview with Josh Dillon, who works on Tensorflow.

In this video, he discusses working on the Distribution API, which is based on probabilistic programming. Watch this video to find out what exactly probabilistic programming is, where the use of Distributions and Bijectors comes into play, & how you can get started. Subscribe to our channel to stay up to date with Google Developers.

This week James Montemagno is joined by Jim Bennett, a Cloud Developer Advocate at Microsoft, who shows us how to use AI inside a mobile app to identify his daughters’ toys.

In the video below, he walks through using the Azure custom vision service to generate a model to identify different toys, then shows how you can use these models from inside your app, both remotely by calling an Azure service, or locally by running the model on your device using CoreML and Tensorflow.

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