Charlie Gerard

Learn how to build a simple gesture recognition system using JavaScript, Arduino and Machine learning.

Most of our interactions with technology aren’t really intuitive. We’ve had to adapt to it by learning to type, swipe, execute specific voice commands, etc… but what if we could train technology to adapt to us?

Programming for hardware in JavaScript has already been made accessible with frameworks like Johnny- five, but, combining it with machine learning, we have the opportunity to create new and smarter interactions.

In this presentation, I will talk about how to build a simple gesture recognition system using JavaScript, Arduino and Machine learning.

2020

JSConf Hawaiʻi

Strike a Pose: Gesture Recognition in JS with Machine Learning

Acoustic activity recognition can create new interactions and better smart systems. See how you can experiment with JS, Machine Learning, and Tensorflow.js.

Even though we don’t really think about it, sound is a very rich source of information.

Leveraging the properties of sound with machine learning, we can gain insights about an environment or an activity performed.

Acoustic activity recognition has the potential to create new interactions and better smart systems, and in this talk, Charlie explores how to experiment with this technology in JavaScript, using the Web audio API and Tensorflow.js.

2019

dotJS

Exploring the hidden potential of sound data

What if you could interact with interfaces and devices using your clothes? When we think about wearable garments, we usually think of the technology as an output. We might think of LED dresses or designer-made outfits that react to the environment but what if instead, we used this technology as an input, as a way to interact with other things.

I have been prototyping wearable interfaces in JavaScript to use clothes as an input device and, in this talk, I will walk through the process of making interactive clothing using conductive textile, show what it can do and talk about the possibilities and limits of such technology.

JSConf Budapest

Weaving the web - Programming textile-based interactions

Most of our interactions with technology aren’t really intuitive. We’ve had to adapt to it by learning to type, swipe, execute specific voice commands, etc… but what if we could train technology to adapt to us?

Programming for hardware in JavaScript has already been made accessible with frameworks like Johnny-five, but, combining it with machine learning, we have the opportunity to create new and smarter interactions.

In this presentation, I will talk about how to build a simple gesture recognition system using JavaScript, Arduino and Machine learning.

JSConf US

Strike a Pose - Gesture recognition in JavaScript with ML & Arduino

Machine learning can have some pretty complicated concepts to grasp if you’re not a data scientist. However, recent developments in tooling make it more and more accessible for developers and people with little or no experience.

One of these advancements is the ability to now train and run machine learning algorithms and models in the browser, opening this world to front-end developers to learn and experiment.

In this presentation, we will talk about the different applications, possibilities, tools and resources, as well as show a few examples and demos, so you can get started building your own experiments using machine learning in JavaScript.

JSConf Asia

Machine Learning for Front-End Developers

Machine learning can have some pretty complicated concepts to grasp if you’re not a data scientist. However, recent developments in tooling make it more and more accessible for developers and people with little or no experience. One of these advancements is the ability to now train and run machine learning algorithms and models in the browser, opening this world to front-end developers to learn and experiment. 

In this presentation, we will talk about the different applications, possibilities, tools and resources, as well as show a few examples and demos, so you can get started building your own experiments using machine learning in JavaScript.

2019 Lithuania

You Gotta Love Frontend

Practical Machine Learning for Front End Developers

You can now train and run machine learning algorithms and models in the browser, opening this world to front-end developers to learn and experiment.

Machine learning can have some pretty complicated concepts to grasp if you’re not a data scientist. However, recent developments in tooling make it more and more accessible for developers and people with little or no experience.

One of these advancements is the ability to now train and run machine learning algorithms and models in the browser, opening this world to front-end developers to learn and experiment.