Panelists Suz Hinton and Nick Nisi discuss TensorFlow.js and Machine Learning in JavaScript with special guest Paige Bailey, TensorFlow mom and developer Advocate for Google AI.

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Featuring:

• Paige Bailey – Twitter, GitHub, Website
• Suz Hinton – Mastodon, Twitter, GitHub
• Nick Nisi – Mastodon, Twitter, GitHub, Website

Show Notes:

• TensorFlow.js
• Google AI ml5.js - Friendly Machine Learning for the Web
• Machine Learning Glossary
• TensorFlow tutorials
• Tero Parviainen on CodePen
• tfjs-layers - High-level machine learning model API
• tfjs-models - Pre-trained TensorFlow.js models
• slicing-metrics-browser.gif">tfma-slicing-metrics-browser.gif 📷
• TensorFlow Model Analysis (TFMA) - a library for evaluating TensorFlow models
• code.github.io/what-if-tool/">What-If Tool - Building effective machine learning systems means asking a lot of questions. It’s not enough to train a model and walk away. Instead, good practitioners act as detectives, probing to understand their model better.
• EthicalMachineLearning.ipynb
• TensorBoard: Visualizing Learning
• TensorBoard: Graph Visualization
• People + AI Research (PAIR) - Human-centered research and design to make AI partnerships productive, enjoyable, and fair.
• Distill - Clear explanations of machine learning
• Book: Technically Wrong: Sexist Apps, Biased Algorithms, and Other Threats of Toxic Tech
• Book: Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy
• A new course to teach people about fairness in machine learning
• List of cognitive biases
• CleverHans - a Python library to benchmark machine learning systems’ vulnerability to adversarial examples
• CleverHans paper
• Breaking linear classifiers on ImageNet
• CV Dazzle - explores how fashion can be used as camouflage from face-detection technology, the first step in automated face recognition

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