Your weekly celebration of JavaScript and the web. This show records LIVE on Thursdays at 1pm US/Eastern time. Panelists include Jerod Santo, Feross Aboukhadijeh, Kevin Ball, Amelia Wattenberger, Nick Nisi, Divya Sasidharan, Mikeal Rogers, Chris Hiller, and Amal Hussein. Topics discussed include the web platform (Chrome, Safari, Edge, Firefox, Brave, etc), front-end frameworks (React, Ember, Angular, Vue, etc), Node.js, web animation, SVG, robotics, IoT, and much more. If JavaScript and/or the web touch your life, this show’s for you. Some people search for JSParty and can’t find the show, so now the string JSParty is in our description too.
TensorFlow.js and Machine Learning in JavaScript
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 – Twitter, GitHub, Website
- Nick Nisi – Twitter, GitHub, Website
Notes and Links
- 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
- tfma-slicing-metrics-browser.gif 📷
- TensorFlow Model Analysis (TFMA) - a library for evaluating TensorFlow models
- 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
