Videos

Magenta: Music and Art Generation (TensorFlow Dev Summit 2017)

1 month ago
Using TensorFlow for Music and Art Generation — that’s what Magenta is all about. Join Douglas Eck discusses art and music generation with deep nets and reinforcement learning. He also talks about how artists and musicians fit in to the effort. Be prepared to see and hear inspired ML models. Visit the TensorFlow website for […]

Wide & Deep Learning: Memorization + Generalization with TensorFlow (TensorFlow Dev Summit 2017)

1 month ago
Wide models are great for memorization, deep models are great for generalization — why not combine them to create even better models? In this talk, Heng-Tze Cheng explains Wide and Deep networks and gives examples of how they can be used. Check out our blog post, paper, YouTube video, TensorFlow tutorials: goo.gl/MwVlVa Visit the TensorFlow […]

Case Study: TensorFlow in Medicine – Retinal Imaging (TensorFlow Dev Summit 2017)

1 month ago
Diabetic retinopathy is the fastest growing cause of blindness. Learn from Lily Peng how TensorFlow was trained to analyze retinal fundus images to diagnose this condition. She describes the project steps: from acquiring a dataset, training a deep network, and evaluating of the results. Visit the TensorFlow website for all session recordings: goo.gl/bsYmza Subscribe to […]

Sequence Models and the RNN API (TensorFlow Dev Summit 2017)

1 month ago
In this talk, Eugene Brevdo discusses the creation of flexible and high-performance sequence-to-sequence models. He covers reading and batching sequence data, the RNN API, fully dynamic calculation, fused RNN cells for optimizations for special cases, and dynamic decoding. Visit the TensorFlow website for all session recordings: goo.gl/bsYmza Subscribe to the Google Developers channel at goo.gl/mQyv5L

ML Toolkit (TensorFlow Dev Summit 2017)

1 month ago
TensorFlow is an extremely powerful framework, yet has been missing packaged solutions that work out-of-the-box. In this talk, Ashish Agarwal introduces a toolkit of algorithms that takes a step in that direction. Visit the TensorFlow website for all session recordings: goo.gl/bsYmza Subscribe to the Google Developers channel at goo.gl/mQyv5L

Serving Models in Production with TensorFlow Serving (TensorFlow Dev Summit 2017)

1 month ago
Serving is the process of applying a trained model in your application. In this talk, Noah Fiedel describes TensorFlow Serving, a flexible, high-performance ML serving system designed for production environments. Visit the TensorFlow website for all session recordings: goo.gl/bsYmza Subscribe to the Google Developers channel at goo.gl/mQyv5L

TensorFlow Ecosystem: Integrating TensorFlow with your infrastructure (TensorFlow Dev Summit 2017)

1 month ago
Generating input data, running distributed TensorFlow training, and serving models all involve other infrastructure components. Jonathan Hseu describes integration for each of these steps. Visit the TensorFlow website for all session recordings: goo.gl/bsYmza Subscribe to the Google Developers channel at goo.gl/mQyv5L

Distributed TensorFlow (TensorFlow Dev Summit 2017)

1 month ago
TensorFlow gives you the flexibility to scale up to hundreds of GPUs, train models with a huge number of parameters, and customize every last detail of the training process. In this talk, Derek Murray gives you a bottom-up introduction to Distributed TensorFlow, showing all the tools available for harnessing this power. Further reading: – tensorflow.org/extend/architecture […]

Mobile and Embedded TensorFlow (TensorFlow Dev Summit 2017)

1 month ago
Did you know that TensorFlow models can be deployed in iOS and Android apps, and even run on Raspberry Pi? In this talk Pete Warden will go through everything you need to know to make this happen, and provide some golden technical pro-tips on the way. Visit the TensorFlow website for all session recordings: goo.gl/bsYmza […]

TensorFlow at DeepMind (TensorFlow Dev Summit 2017)

1 month ago
In this talk, Daniel Visentin from the DeepMind Applied team talks about DeepMind and TensorFlow. He explains the importance of choosing a platform, the team’s choice to migrate to TensorFlow, and gives a number of examples of how DeepMind uses TensorFlow. Visit the TensorFlow website for all session recordings: goo.gl/bsYmza Subscribe to the Google Developers […]

XLA: TensorFlow, Compiled! (TensorFlow Dev Summit 2017)

1 month ago
Speed is everything for effective machine learning, and XLA was developed to reduce training and inference time. In this talk, Chris Leary and Todd Wang describe how TensorFlow can make use of XLA, JIT, AOT, and other compilation techniques to minimize execution time and maximize computing resources. Visit the TensorFlow website for all session recordings: […]

Integrating Keras & TensorFlow: The Keras workflow, expanded (TensorFlow Dev Summit 2017)

1 month ago
Keras has the goal to make deep learning accessible to everyone, and it’s one of the fastest growing machine learning frameworks. Join Francois Chollet, the primary author of Keras, as he demonstrates how Keras can be used in TensorFlow through a video QA example. Visit the TensorFlow website for all session recordings: goo.gl/bsYmza Subscribe to […]