Neural Structured Learning - Part 1: Framework overview

TensorFlow · Beginner ·🛠️ AI Tools & Apps ·6y ago

Key Takeaways

Introduction to Neural Structured Learning framework using TensorFlow, covering its overview and applications

Original Description

In this video series, we’re going to introduce a new learning framework to our developers called Neural Structured Learning. TensorFlow Senior Software Engineer Da-Cheng Juan kicks off this series with the framework overview. Links: Get started with Neural Structured Learning → https://goo.gle/2sOz6DE Hands-on tutorial → https://goo.gle/37pAD27 Coding TensorFlow → https://goo.gle/Coding-TensorFlow Subscribe to the TensorFlow channel → https://goo.gle/TensorFlow
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1 The TensorFlow YouTube Channel is Here!
The TensorFlow YouTube Channel is Here!
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 2 Answering Your TF Questions #AskTensorFlow
Answering Your TF Questions #AskTensorFlow
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 3 Chatting With the TensorFlow Community (TensorFlow Meets)
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 4 All About TensorFlow Code (Coding TensorFlow)
All About TensorFlow Code (Coding TensorFlow)
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 5 TensorFlow: an ML platform for solving impactful and challenging problems
TensorFlow: an ML platform for solving impactful and challenging problems
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 6 Keynote (TensorFlow Dev Summit 2018)
Keynote (TensorFlow Dev Summit 2018)
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 7 tf.data: Fast, flexible, and easy-to-use input pipelines (TensorFlow Dev Summit 2018)
tf.data: Fast, flexible, and easy-to-use input pipelines (TensorFlow Dev Summit 2018)
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 8 Eager Execution (TensorFlow Dev Summit 2018)
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 9 Machine Learning in JavaScript (TensorFlow Dev Summit 2018)
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 10 Training Performance: A user’s guide to converge faster (TensorFlow Dev Summit 2018)
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 11 The Practitioner's Guide with TF High Level APIs (TensorFlow Dev Summit 2018)
The Practitioner's Guide with TF High Level APIs (TensorFlow Dev Summit 2018)
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 12 Distributed TensorFlow (TensorFlow Dev Summit 2018)
Distributed TensorFlow (TensorFlow Dev Summit 2018)
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 13 Debugging TensorFlow with TensorBoard plugins (TensorFlow Dev Summit 2018)
Debugging TensorFlow with TensorBoard plugins (TensorFlow Dev Summit 2018)
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 14 TensorFlow Lite (TensorFlow Dev Summit 2018)
TensorFlow Lite (TensorFlow Dev Summit 2018)
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 15 Searching Over Ideas (TensorFlow Dev Summit 2018)
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 16 Reconstructing Fusion Plasmas (TensorFlow Dev Summit 2018)
Reconstructing Fusion Plasmas (TensorFlow Dev Summit 2018)
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 17 Nucleus: TensorFlow toolkit for Genomics (TensorFlow Dev Summit 2018)
Nucleus: TensorFlow toolkit for Genomics (TensorFlow Dev Summit 2018)
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 18 Open Source Collaboration (TensorFlow Dev Summit 2018)
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 19 Swift for TensorFlow - TFiwS (TensorFlow Dev Summit 2018)
Swift for TensorFlow - TFiwS (TensorFlow Dev Summit 2018)
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 20 TensorFlow Hub (TensorFlow Dev Summit 2018)
TensorFlow Hub (TensorFlow Dev Summit 2018)
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 21 Applied AI at The Coca-Cola Company (TensorFlow Dev Summit 2018)
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 22 Real-World Robot Learning (TensorFlow Dev Summit 2018)
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 23 TensorFlow Extended (TFX) (TensorFlow Dev Summit 2018)
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 24 Project Magenta (TensorFlow Dev Summit 2018)
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 25 TensorFlow Dev Summit 2018 - Livestream
TensorFlow Dev Summit 2018 - Livestream
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 26 Introducing TensorFlow Lite (Coding TensorFlow)
Introducing TensorFlow Lite (Coding TensorFlow)
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 27 TensorFlow Dev Summit 2018 Highlights
TensorFlow Dev Summit 2018 Highlights
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 28 Jeff Dean, Head of AI at Google discusses the impact of ML (TensorFlow Meets)
Jeff Dean, Head of AI at Google discusses the impact of ML (TensorFlow Meets)
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 29 TensorFlow Mobile vs. TF Lite and More! #AskTensorFlow
TensorFlow Mobile vs. TF Lite and More! #AskTensorFlow
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 30 Using TensorFlow to enable research & production across many fields (TensorFlow Meets)
Using TensorFlow to enable research & production across many fields (TensorFlow Meets)
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 31 Teaching TensorFlow for Deep Learning at Stanford University (TensorFlow Meets)
Teaching TensorFlow for Deep Learning at Stanford University (TensorFlow Meets)
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 32 TensorFlow Lite for Android (Coding TensorFlow)
TensorFlow Lite for Android (Coding TensorFlow)
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 33 Using the tf.data API to build input pipelines (TensorFlow Meets)
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 34 Training Models in the Cloud & the Benefits of AI Toolkits #AskTensorFlow
Training Models in the Cloud & the Benefits of AI Toolkits #AskTensorFlow
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 35 Execute operations immediately with TensorFlow's Eager Execution (TensorFlow Meets)
Execute operations immediately with TensorFlow's Eager Execution (TensorFlow Meets)
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 36 TensorFlow Lite for iOS (Coding TensorFlow)
TensorFlow Lite for iOS (Coding TensorFlow)
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 37 Get started with TensorFlow's High-Level APIs (Google I/O '18)
Get started with TensorFlow's High-Level APIs (Google I/O '18)
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 38 TensorFlow for JavaScript (Google I/O '18)
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 39 TensorFlow in production: TF Extended, TF Hub, and TF Serving (Google I/O '18)
TensorFlow in production: TF Extended, TF Hub, and TF Serving (Google I/O '18)
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 40 Get started with TensorFlow's High-Level APIs in 5 mins | Google I/O 2018
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 41 TensorFlow and deep reinforcement learning, without a PhD (Google I/O '18)
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 42 TensorFlow Lite for mobile developers (Google I/O '18)
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 43 Advances in machine learning and TensorFlow (Google I/O '18)
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 44 Distributed TensorFlow training (Google I/O '18)
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 45 Classification using neural networks & ML regression models #AskTensorFlow
Classification using neural networks & ML regression models #AskTensorFlow
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 46 TensorFlow and Keras in R - Josh Gordon meets with J.J. Allaire (TensorFlow Meets)
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 47 Focus on your experiment with TensorFlow Estimators (TensorFlow Meets)
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 48 How to get started with AI/ML, retraining models, & more! #AskTensorFlow
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 49 TensorFlow - the deep learning solution for mobile platforms (TensorFlow Meets)
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 50 MiniGo: TensorFlow Meets Andrew Jackson (TensorFlow Meets)
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 51 The growth of TensorFlow with added support for JS & Swift (TensorFlow Meets)
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 52 At the intersection of TensorFlow & nuclear physics (TensorFlow Meets)
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 53 NVidia TensorRT: high-performance deep learning inference accelerator (TensorFlow Meets)
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 54 Try TensorFlow.js in your browser (Coding TensorFlow)
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 55 TensorFlow Hub: reusing machine learning modules (TensorFlow Meets)
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 56 How to use TensorFlow in PyCharm (TensorFlow Tip of the Week)
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 57 Training models faster with TensorFlow Hub (TensorFlow Meets)
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 58 Prepare your dataset for machine learning (Coding TensorFlow)
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 59 Using ML to predict insulin use for Type 1 Diabetes (TensorFlow Meets)
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 60 TFX: an end-to-end machine learning platform for TensorFlow (TensorFlow Meets)
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This video introduces the Neural Structured Learning framework, a new learning framework for developers, and provides an overview of its applications and uses in machine learning and deep learning. Viewers can learn how to get started with Neural Structured Learning and explore its potential in building neural network models. The framework is particularly useful for structured learning tasks, where relationships between data points are important.

Key Takeaways
  1. Get started with Neural Structured Learning
  2. Explore the framework overview
  3. Try the hands-on tutorial
  4. Learn how to use TensorFlow for neural structured learning
  5. Implement neural networks with TensorFlow
💡 Neural Structured Learning is a new framework that enables developers to build neural network models that can learn from structured data, such as graphs or tables, and can be used for a variety of machine learning tasks.

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