Video: Build Intelligence at the Edge - Machine Learning with React Native

The Talk is about building intelligence at the edge with machine learning and React Native. It covers machine learning concepts, building ML models with React, challenges, best practices, and resources.

This talk has been presented at React Day Berlin 2023, check out the latest edition of this React Conference.

Rashmi Nagpal
Rashmi Nagpal
13 min
12 Dec, 2023

Comments

Sign in or register to post your comment.

Check out more articles and videos

We constantly think of articles and videos that might spark Git people interest / skill us up or help building a stellar career

TensorFlow.js 101: ML in the Browser and Beyond
ML conf EU 2020ML conf EU 2020
41 min
TensorFlow.js 101: ML in the Browser and Beyond
TensorFlow.js enables machine learning in the browser and beyond, with features like face mesh, body segmentation, and pose estimation. It offers JavaScript prototyping and transfer learning capabilities, as well as the ability to recognize custom objects using the Image Project feature. TensorFlow.js can be used with Cloud AutoML for training custom vision models and provides performance benefits in both JavaScript and Python development. It offers interactivity, reach, scale, and performance, and encourages community engagement and collaboration between the JavaScript and machine learning communities.
Using MediaPipe to Create Cross Platform Machine Learning Applications with React
React Advanced 2021React Advanced 2021
21 min
Using MediaPipe to Create Cross Platform Machine Learning Applications with React
Top Content
MediaPipe is a cross-platform framework that helps build perception pipelines using machine learning models. It offers ready-to-use solutions for various applications, such as selfie segmentation, face mesh, object detection, hand tracking, and more. MediaPipe can be integrated with React using NPM modules provided by the MediaPipe team. The demonstration showcases the implementation of face mesh and selfie segmentation solutions. MediaPipe enables the creation of amazing applications without needing to understand the underlying computer vision or machine learning processes.
Charlie Gerard's Career Advice: Be intentional about how you spend your time and effort
Charlie Gerard's Career Advice: Be intentional about how you spend your time and effort
Article
Charlie Gerard
Charlie Gerard
When it comes to career, Charlie has one trick: to focus. But that doesn’t mean that you shouldn’t try different things — currently a senior front-end developer at Netlify, she is also a sought-after speaker, mentor, and a machine learning trailblazer of the JavaScript universe. "Experiment with things, but build expertise in a specific area," she advises.
What led you to software engineering?My background is in digital marketing, so I started my career as a project manager in advertising agencies. After a couple of years of doing that, I realized that I wasn't learning and growing as much as I wanted to. I was interested in learning more about building websites, so I quit my job and signed up for an intensive coding boot camp called General Assembly. I absolutely loved it and started my career in tech from there.
What is the most impactful thing you ever did to boost your career?I think it might be public speaking. Going on stage to share knowledge about things I learned while building my side projects gave me the opportunity to meet a lot of people in the industry, learn a ton from watching other people's talks and, for lack of better words, build a personal brand.
What would be your three tips for engineers to level up their career?Practice your communication skills. I can't stress enough how important it is to be able to explain things in a way anyone can understand, but also communicate in a way that's inclusive and creates an environment where team members feel safe and welcome to contribute ideas, ask questions, and give feedback. In addition, build some expertise in a specific area. I'm a huge fan of learning and experimenting with lots of technologies but as you grow in your career, there comes a time where you need to pick an area to focus on to build more profound knowledge. This could be in a specific language like JavaScript or Python or in a practice like accessibility or web performance. It doesn't mean you shouldn't keep in touch with anything else that's going on in the industry, but it means that you focus on an area you want to have more expertise in. If you could be the "go-to" person for something, what would you want it to be? 
And lastly, be intentional about how you spend your time and effort. Saying yes to everything isn't always helpful if it doesn't serve your goals. No matter the job, there are always projects and tasks that will help you reach your goals and some that won't. If you can, try to focus on the tasks that will grow the skills you want to grow or help you get the next job you'd like to have.
What are you working on right now?Recently I've taken a pretty big break from side projects, but the next one I'd like to work on is a prototype of a tool that would allow hands-free coding using gaze detection. 
Do you have some rituals that keep you focused and goal-oriented?Usually, when I come up with a side project idea I'm really excited about, that excitement is enough to keep me motivated. That's why I tend to avoid spending time on things I'm not genuinely interested in. Otherwise, breaking down projects into smaller chunks allows me to fit them better in my schedule. I make sure to take enough breaks, so I maintain a certain level of energy and motivation to finish what I have in mind.
You wrote a book called Practical Machine Learning in JavaScript. What got you so excited about the connection between JavaScript and ML?The release of TensorFlow.js opened up the world of ML to frontend devs, and this is what really got me excited. I had machine learning on my list of things I wanted to learn for a few years, but I didn't start looking into it before because I knew I'd have to learn another language as well, like Python, for example. As soon as I realized it was now available in JS, that removed a big barrier and made it a lot more approachable. Considering that you can use JavaScript to build lots of different applications, including augmented reality, virtual reality, and IoT, and combine them with machine learning as well as some fun web APIs felt super exciting to me.

Where do you see the fields going together in the future, near or far? I'd love to see more AI-powered web applications in the future, especially as machine learning models get smaller and more performant. However, it seems like the adoption of ML in JS is still rather low. Considering the amount of content we post online, there could be great opportunities to build tools that assist you in writing blog posts or that can automatically edit podcasts and videos. There are lots of tasks we do that feel cumbersome that could be made a bit easier with the help of machine learning.
You are a frequent conference speaker. You have your own blog and even a newsletter. What made you start with content creation?I realized that I love learning new things because I love teaching. I think that if I kept what I know to myself, it would be pretty boring. If I'm excited about something, I want to share the knowledge I gained, and I'd like other people to feel the same excitement I feel. That's definitely what motivated me to start creating content.
How has content affected your career?I don't track any metrics on my blog or likes and follows on Twitter, so I don't know what created different opportunities. Creating content to share something you built improves the chances of people stumbling upon it and learning more about you and what you like to do, but this is not something that's guaranteed. I think over time, I accumulated enough projects, blog posts, and conference talks that some conferences now invite me, so I don't always apply anymore. I sometimes get invited on podcasts and asked if I want to create video content and things like that. Having a backlog of content helps people better understand who you are and quickly decide if you're the right person for an opportunity.What pieces of your work are you most proud of?It is probably that I've managed to develop a mindset where I set myself hard challenges on my side project, and I'm not scared to fail and push the boundaries of what I think is possible. I don't prefer a particular project, it's more around the creative thinking I've developed over the years that I believe has become a big strength of mine.***Follow Charlie on Twitter
TensorFlow.JS 101: ML in the Browser and Beyond
JSNation Live 2021JSNation Live 2021
39 min
TensorFlow.JS 101: ML in the Browser and Beyond
JavaScript with TensorFlow.js allows for machine learning in various environments, enabling the creation of applications like augmented reality and sentiment analysis. TensorFlow.js offers pre-trained models for object detection, body segmentation, and face landmark detection. It also allows for 3D rendering and the combination of machine learning with WebGL. The integration of WebRTC and WebXR enables teleportation and enhanced communication. TensorFlow.js supports transfer learning through Teachable Machine and Cloud AutoML, and provides flexibility and performance benefits in the browser and Node.js environments.
Observability with diagnostics_channel and AsyncLocalStorage
Node Congress 2023Node Congress 2023
21 min
Observability with diagnostics_channel and AsyncLocalStorage
Observability with Diagnostics Channel and async local storage allows for high-performance event tracking and propagation of values through calls, callbacks, and promise continuations. Tracing involves five events and separate channels for each event, capturing errors and return values. The span object in async local storage stores data about the current execution and is reported to the tracer when the end is triggered.
An Introduction to Transfer Learning in NLP and HuggingFace
ML conf EU 2020ML conf EU 2020
32 min
An Introduction to Transfer Learning in NLP and HuggingFace
Transfer learning in NLP allows for better performance with minimal data. BERT is commonly used for sequential transfer learning. Models like BERT can be adapted for downstream tasks such as text classification. Handling different types of inputs in NLP involves concatenating or duplicating the model. Hugging Face aims to tackle challenges in NLP through knowledge sharing and open sourcing code and libraries.

Workshops on related topic

Leveraging LLMs to Build Intuitive AI Experiences With JavaScript
JSNation 2024JSNation 2024
108 min
Leveraging LLMs to Build Intuitive AI Experiences With JavaScript
Featured Workshop
Roy Derks
Shivay Lamba
2 authors
Today every developer is using LLMs in different forms and shapes, from ChatGPT to code assistants like GitHub CoPilot. Following this, lots of products have introduced embedded AI capabilities, and in this workshop we will make LLMs understandable for web developers. And we'll get into coding your own AI-driven application. No prior experience in working with LLMs or machine learning is needed. Instead, we'll use web technologies such as JavaScript, React which you already know and love while also learning about some new libraries like OpenAI, Transformers.js
Can LLMs Learn? Let’s Customize an LLM to Chat With Your Own Data
C3 Dev Festival 2024C3 Dev Festival 2024
48 min
Can LLMs Learn? Let’s Customize an LLM to Chat With Your Own Data
WorkshopFree
Andreia Ocanoaia
Andreia Ocanoaia
Feeling the limitations of LLMs? They can be creative, but sometimes lack accuracy or rely on outdated information. In this workshop, we’ll break down the process of building and easily deploying a Retrieval-Augmented Generation system. This approach enables you to leverage the power of LLMs with the added benefit of factual accuracy and up-to-date information.
Let AI Be Your Docs
JSNation 2024JSNation 2024
69 min
Let AI Be Your Docs
Workshop
Jesse Hall
Jesse Hall
Join our dynamic workshop to craft an AI-powered documentation portal. Learn to integrate OpenAI's ChatGPT with Next.js 14, Tailwind CSS, and cutting-edge tech to deliver instant code solutions and summaries. This hands-on session will equip you with the knowledge to revolutionize how users interact with documentation, turning tedious searches into efficient, intelligent discovery.
Key Takeaways:
- Practical experience in creating an AI-driven documentation site.- Understanding the integration of AI into user experiences.- Hands-on skills with the latest web development technologies.- Strategies for deploying and maintaining intelligent documentation resources.
Table of contents:- Introduction to AI in Documentation- Setting Up the Environment- Building the Documentation Structure- Integrating ChatGPT for Interactive Docs
Hands on with TensorFlow.js
ML conf EU 2020ML conf EU 2020
160 min
Hands on with TensorFlow.js
Workshop
Jason Mayes
Jason Mayes
Come check out our workshop which will walk you through 3 common journeys when using TensorFlow.js. We will start with demonstrating how to use one of our pre-made models - super easy to use JS classes to get you working with ML fast. We will then look into how to retrain one of these models in minutes using in browser transfer learning via Teachable Machine and how that can be then used on your own custom website, and finally end with a hello world of writing your own model code from scratch to make a simple linear regression to predict fictional house prices based on their square footage.
The Hitchhiker's Guide to the Machine Learning Engineering Galaxy
ML conf EU 2020ML conf EU 2020
112 min
The Hitchhiker's Guide to the Machine Learning Engineering Galaxy
Workshop
Alyona Galyeva
Alyona Galyeva
Are you a Software Engineer who got tasked to deploy a machine learning or deep learning model for the first time in your life? Are you wondering what steps to take and how AI-powered software is different from traditional software? Then it is the right workshop to attend.
The internet offers thousands of articles and free of charge courses, showing how it is easy to train and deploy a simple AI model. At the same time in reality it is difficult to integrate a real model into the current infrastructure, debug, test, deploy, and monitor it properly. In this workshop, I will guide you through this process sharing tips, tricks, and favorite open source tools that will make your life much easier. So, at the end of the workshop, you will know where to start your deployment journey, what tools to use, and what questions to ask.
Introduction to Machine Learning on the Cloud
ML conf EU 2020ML conf EU 2020
146 min
Introduction to Machine Learning on the Cloud
Workshop
Dmitry Soshnikov
Dmitry Soshnikov
This workshop will be both a gentle introduction to Machine Learning, and a practical exercise of using the cloud to train simple and not-so-simple machine learning models. We will start with using Automatic ML to train the model to predict survival on Titanic, and then move to more complex machine learning tasks such as hyperparameter optimization and scheduling series of experiments on the compute cluster. Finally, I will show how Azure Machine Learning can be used to generate artificial paintings using Generative Adversarial Networks, and how to train language question-answering model on COVID papers to answer COVID-related questions.