TensorFlow
TensorFlow is a fast, flexible, and scalable open-source machine learning library for research and production.
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Welcome to IJCAI-19
Welcome to IJCAI 2019, the 28th International Joint Conference on Artificial Intelligence. This will be the second time that IJCAI is held in China: the first time was 2013 in Beijing, the capital of…
Auto-classification of NAVER Shopping Product Categories using TensorFlow
A guest post by the NAVER engineering team.
tensorflow/tfx
TFX is an end-to-end platform for deploying production ML pipelines - tensorflow/tfx
TensorFlow 2.0 upgrade, Python support, & more! (#AskTensorFlow)
In a special live episode from the TensorFlow Dev Summit, Paige (@DynamicWebPaige) and Laurence (@lmoroney) answer your #AskTensorFlow questions. Learn about...
TensorFlow Extended: Machine Learning Pipelines and Model Understanding (Google I/O'19)
This talk will focus on creating a production machine learning pipeline using TFX. Using TFX developers can implement machine learning pipelines capable of p...
Online Program
*Robert Crowe, Google Keywords: machine learning, deep learning, artificial intelligence, open source, data science, TensorFlow, TFX, Apache Beam, ML pipelines, ML Ops, Dev Ops Putting machine…
Tutorials - International Conference on Software Engineering 2019 in Montreal, Canada
The International Conference on Software Engineering (ICSE), sponsored by IEEE CS and ACM, is the premier software-engineering conference, where researchers, practitioners, and educators come together…
TensorFlow Model Optimization Toolkit — Pruning API
Since we introduced the Model Optimization Toolkit — a suite of techniques that developers, both novice and advanced, can use to optimize…
TensorFlow Extended: An End-to-End Machine Learning Platform for TensorFlow
As machine learning evolves from experimentation to serving production workloads, so does the need to effectively manage the end-to-end training and production workflow including model management,…
Introducing Google Coral: Building On-Device AI
This session will introduce you to Google Coral, a new platform for on-device AI application development and showcase it's machine learning acceleration power with TensorFlow demos. Coral offers the…
Machine Learning Fairness: Lessons Learned
ML fairness is a critical consideration in machine learning development. This session will present a few lessons Google has learned through our products and research and how developers can apply these…
Machine Learning Zero to Hero
This is a talk for people who know code, but who don’t necessarily know machine learning. Learn the ‘new’ paradigm of machine learning, and how models are an alternative implementation for some logic…
TF-Agents: A Flexible Reinforcement Learning Library for TensorFlow
TF-Agents is a clean, modular, and well-tested open-source library for Deep Reinforcement Learning with TensorFlow. This session will cover recent advancements in Deep RL, and show how TF-Agents can…
Cutting Edge TensorFlow: New Techniques
There's lots of great new things available in TensorFlow since last year's IO. This session will take you through 4 of the hottest from Hyperparameter Tuning with Keras Tuner to Probabilistic…
Federated Learning: Machine Learning on Decentralized Data
Meet federated learning: a technology for training and evaluating machine learning models across a fleet of devices (e.g. Android phones), orchestrated by a central server, without sensitive training…
Swift for TensorFlow
Swift for TensorFlow is a platform for the next generation of machine learning that leverages innovations like first-class differentiable programming to seamlessly integrate deep neural networks with…
AI for Mobile and IoT Devices: TensorFlow Lite
Imagine building an app that identifies products in real time with your camera or one that responds to voice commands instantly. In this session, you'll learn how to build AI into any device using…
TensorFlow Extended: Machine Learning Pipelines and Model Understanding
This talk will focus on creating a production machine learning pipeline using TFX. Using TFX developers can implement machine learning pipelines capable of processing large datasets for both modeling…
Machine Learning Magic for Your JavaScript Application
TensorFlow.js is a library for training and deploying machine learning models in the browser and in Node.js and offers unique opportunities for JavaScript developers. In this talk, you will learn…
Getting Started with TensorFlow 2.0
TensorFlow 2.0 is here! Understand new user-friendly APIs for beginners and experts through code examples to help you create different flavors of neural networks (Dense, Convolutional, and Recurrent)…
Schedule - Google I/O 2019
Google I/O 2019 returns to the Shoreline Amphitheatre May 7-9. Join us for a hands-on experience with Google’s latest product and platform innovations.
High-Level APIs in TensorFlow 2.0 (TensorFlow Meets)
TensorFlow’s high-level APIs help are there to help you through each stage of your model-building process. On this episode of TensorFlow Meets, Laurence (@lm...
Using GPUs in TensorFlow, TensorBoard in notebooks, finding new datasets, & more!…
In a special live episode from the TensorFlow Dev Summit, Paige (@DynamicWebPaige) and Laurence (@lmoroney) answer your #AskTensorFlow questions. Learn about...