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As an AI Lead at Google for over 10 years, I have been driving the corporate-wide…

Articles by Laurence

Covid Vaccines and Big Tech

By Laurence Moroney

Mar 26, 2021

Using Google Sign-In with your server

By Laurence Moroney

Jan 15, 2016

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Harvard Data Science Review November 1, 2022

Broadening access to both computational and educational resources is critical to diffusing machine learning (ML) innovation. However, today, most ML resources and experts are siloed in a few countries and organizations. In this article, we describe our pedagogical approach to increasing access to applied ML through a massive open online course (MOOC) on Tiny Machine Learning (TinyML). We suggest that TinyML, applied ML on resource-constrained embedded devices, is an attractive means to widen…
Broadening access to both computational and educational resources is critical to diffusing machine learning (ML) innovation. However, today, most ML resources and experts are siloed in a few countries and organizations. In this article, we describe our pedagogical approach to increasing access to applied ML through a massive open online course (MOOC) on Tiny Machine Learning (TinyML). We suggest that TinyML, applied ML on resource-constrained embedded devices, is an attractive means to widen access because TinyML leverages low-cost and globally accessible hardware and encourages the development of complete, self-contained applications, from data collection to deployment. To this end, a collaboration between academia and industry produced a four part MOOC that provides application-oriented instruction on how to develop solutions using TinyML. The series is openly available on the edX MOOC platform, has no prerequisites beyond basic programming, and is designed for global learners from a variety of backgrounds. It introduces real-world applications, ML algorithms, data-set engineering, and the ethical considerations of these technologies through hands-on programming and deployment of TinyML applications in both the cloud and on their own microcontrollers. To facilitate continued learning, community building, and collaboration beyond the courses, we launched a standalone website, a forum, a chat, and an optional course-project competition. We also open-sourced the course materials, hoping they will inspire the next generation of ML practitioners and educators and further broaden access to cutting-edge ML technologies.
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O'Reilly October 1, 2021

If you're looking to make a career move from programmer to AI specialist, this is the ideal place to start. Based on Laurence Moroney's extremely successful AI courses, this introductory book provides a hands-on, code-first approach to help you build confidence while you learn key topics.
You'll understand how to implement the most common scenarios in machine learning, such as computer vision, natural language processing (NLP), and sequence modeling for web, mobile, cloud, and embedded…
If you're looking to make a career move from programmer to AI specialist, this is the ideal place to start. Based on Laurence Moroney's extremely successful AI courses, this introductory book provides a hands-on, code-first approach to help you build confidence while you learn key topics.
You'll understand how to implement the most common scenarios in machine learning, such as computer vision, natural language processing (NLP), and sequence modeling for web, mobile, cloud, and embedded runtimes. Most books on machine learning begin with a daunting amount of advanced math. This guide is built on practical lessons that let you work directly with the code.
You'll learn:
How to build models with TensorFlow using skills that employers desire
The basics of machine learning by working with code samples
How to implement computer vision, including feature detection in images
How to use NLP to tokenize and sequence words and sentences
Methods for embedding models in Android and iOS
How to serve models over the web and in the cloud with TensorFlow Serving
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Patent March 10, 2021

n one example embodiment, a computer-implemented method for determining traffic conditions includes obtaining traffic sample data associated with a first direction of traffic on a first road segment, the traffic sample data including data indicative of a plurality of movement speeds associated with a plurality of objects. The method includes determining a plurality of average traffic speeds for the first direction of traffic on the first road segment based at least in part on the plurality of…
n one example embodiment, a computer-implemented method for determining traffic conditions includes obtaining traffic sample data associated with a first direction of traffic on a first road segment, the traffic sample data including data indicative of a plurality of movement speeds associated with a plurality of objects. The method includes determining a plurality of average traffic speeds for the first direction of traffic on the first road segment based at least in part on the plurality of movement speeds. The method includes associating each of the plurality of average traffic speeds with at least one of a plurality of traffic types. The method includes determining map data based at least in part on the plurality of traffic types and associated average traffic speeds. The method includes transmitting to a client device in response to a request, map data corresponding to at least one of the plurality of traffic types.
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APress October 1, 2017

Plan how to build a better app, grow it into a business, and earn money from your hard work using Firebase. In this book, Laurence Moroney, Staff Developer Advocate at Google, takes you through each of the 15 Firebase technologies, showing you how to use them with concrete examples. You’ll see how to build cross-platform apps with the three pillars of the Firebase platform: technologies to help you develop apps with a real-time database, remote configuration, cloud messaging, and more; grow…
Plan how to build a better app, grow it into a business, and earn money from your hard work using Firebase. In this book, Laurence Moroney, Staff Developer Advocate at Google, takes you through each of the 15 Firebase technologies, showing you how to use them with concrete examples. You’ll see how to build cross-platform apps with the three pillars of the Firebase platform: technologies to help you develop apps with a real-time database, remote configuration, cloud messaging, and more; grow your apps with user sharing, search integration, analytics, and more; and earn from your apps with in-app advertising.
After reading The Definitive Guide to Firebase, you'll come away empowered to make the most of this technology that helps you build better cross-platform mobile apps using either native Android or JavaScript-based web apps and effectively deploy them in a cloud environment.
What You'll Learn
Use the real-time database for a codeless middleware that gives online and offline data for syncing across your users’ devices
Master Firebase Cloud Messaging, a technology that delivers to connected devices in less than 500ms
Grow your app organically with technologies such App Indexing, App Invites, and Dynamic Links
Understand problems when they arise with crash reporting
Fix user problems without direct access to users’ devices
Tie it all together with analytics that give you great intelligence about how users interact with your app
Who This Book Is For
Experienced Android, mobile app developers new to Firebase. This book is also for experienced web developers looking to build and deploy web apps for smartphones and tablets, too, who may be new or less experienced with mobile programming.
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