Tag: machine learning

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Artificial Intelligence Education Innovation Reading

Latest Read: AI and Machine Learning for Coders

AI and Machine Learning for Coders: A Programmer’s Guide to Artificial Intelligence by Laurence Moroney.

AI and Machine Learning for Coders: A Programmer’s Guide to Artificial Intelligence by Laurence Moroney

Laurence holds a BSc in Physics and Computer Science from Cardiff University, Postgraduate Diploma in Microelectronics Systems Design from Birmingham City University and a Graduate Certificate in Artificial Intelligence from Stanford University.

He was Global AI Advocacy Lead at Google for 10 years and Senior Developer Evangelist at Microsoft for 7 years. In fact, today he is Senior Fellow at The AI Fund, and Artificial Intelligence Advisor and Fellow at RealAvatar. Laurence has also taught millions of students through online platforms such as Coursera, Udacity, and edX.

This book is certainly an amazing guide designed for programmers looking to transition into AI and machine learning with a focus on computer vision, natural language processing (NLP), and sequence modeling with code samples and projects.

To no surprise Laurence is driving this on TensorFlow, Google’s tool for for building models on multiple platforms including Raspberry Pi for deployments on web, mobile (Android and iOS), cloud, and embedded systems.

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Artificial Intelligence Education Reading

Latest Read: AI and Machine Learning for On-Device Development

AI and Machine Learning for On-Device Development: A Programmer’s Guide by Laurence Moroney.

AI and Machine Learning for On-Device Development: A Programmer's Guide by Laurence Moroney

Laurence holds a Bachelor of Science in Physics and Computer Science from Cardiff University, PgD, Microelectronics Systems Design from Birmingham City University and Graduate Certificate in Artificial Intelligence from Stanford University.

Today he is Chief AI Scientist at VisionWorks Studios. He previously was an AI Advocate at Google for 10 years and served as a Senior Developer Evangelist at Microsoft. He wrote this book in 2021 and previously published AI and Machine Learning for Coders in 2020.

While OpenAI’s ChatGPT kick started the LLM surge, AI will simply be a component installed upon our mobile devices. The OpenAI/Microsoft partnership is certainly enterprise focused, Google Gemini and Apple will drive their Android and iOS devices to simply adopt AI as part of their mobile ecosystem. Phones will simply remain the go to device.

So, there was a lot of buzz regarding new AI devices including Humane’s AI Pin or the Rabbit R1. Their rush to market to capitalize on the AI hype cycle leads to critical mistakes.

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Artificial Intelligence Education Reading

Latest Read: Grokking Machine Learning

Grokking Machine Learning by Luis Serrano. He holds a Masters in Mathematics from the University of Waterloo and PhD in Mathematics from the University of Michigan.

Grokking Machine Learning by Luis Serrano

Luis worked as a postdoctoral researcher at the Laboratoire de Combinatoire et d’Informatique Mathématique at the University of Quebec at Montreal.

Today Luis is a research scientist in quantum artificial intelligence at Zapata Computing. He previously worked as a Machine Learning Engineer at Google, Lead Artificial Intelligence Educator at Apple, and Head of Content in Artificial Intelligence and Data Science at Udacity.

The opening chapters provide a good overview to Machine Learning before addressing linear regression. As with previous Grokking series books (below) readers will certainly be learning about supervised algorithms that classifying data.

However Luis is also addressing a much needed understanding of established methods to simplify data clean up in order to make reporting actionable. Likewise, an understanding the basics of Python will make this book’s examples easily understood. To his credit, Luis’ feels that anyone with high school algebra will be able to understand his book.

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Artificial Intelligence Education Reading

Latest Read: Not with a Bug, But with a Sticker

Not with a Bug, But with a Sticker: Attacks on Machine Learning Systems and What to Do about Them by Ram Shankar Siva Kumar and Hyrum Anderson.

Not with a Bug, But with a Sticker: Attacks on Machine Learning Systems and What to Do about Them by Ram Shankar Siva Kumar and Hyrum Anderson

Ram Shankar holds a Masters degree in Electrical and Computer Engineering from Carnegie Mellon University. For over 10 years he has worked as a Data Cowboy at Microsoft in the Azure Security data science team.

Hyrum holds a PhD in Electrical Engineering from the University of Washington. He is a former Principal architect at Microsoft and co-found er of CAMLIS. Today Hyrum is CTO of Robust Intelligence.

Ram Shanker and Hyrum introduce adversarial machine learning, the dedicated field launching cyber attacks upon AI. While this is a most timely book to release, it should have been published twenty years ago so the impact could be well understood.

Perhaps it will clash with Wall Street and Silicon Valley desire to overcome slumping known PC sales and be the spark to drive billions in revenue for a new class of technology companies while reinforcing the market cap of established companies. So, let the voice of Ram Shanker and Hyrum, who attack AI machines for a living provide deep insights. In fact, most of us do not consider the civil liberty implications of attacking AI systems.

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Artificial Intelligence Education Innovation Reading

Latest Read: Everyday Chaos

Everyday Chaos: Technology, Complexity, and How We’re Thriving in a New World of Possibility by David Weinberger.

Everyday Chaos: Technology, Complexity, and How We’re Thriving in a New World of Possibility by David Weinberger

David holds a PhD in Philosophy from the University of Toronto. He is widely published including Wired, Scientific American, Harvard Business Review, The Atlantic, and The Chronicle of Higher Education.

He is Co-Director of Harvard Library’s Innovation Lab; Writer-in-residence at a Google AI lab; Senior researcher at Harvard’s Berkman Klein Center for Internet & Society; Fellow at Harvard’s Shorenstein Center on Media, Politics and Public Policy; and a Franklin Fellow at the US State Department.

David previously authored The Cluetrain Manifesto, Everything is Miscellaneous, and Too Big to Know. Having read these books, David’s writing both inspirational and spot on regarding how internet technologies are shifting the global world. My only regret is not reading this book the day it hit newsstands. And based upon his previous works, will not make that mistake moving forward.

Everyday Chaos is focusing on artificial intelligence, big data, modern science, and a very dynamic internet. Rolling into a somewhat staggering force, these technologies are certainly revealing how complex the world is today. Perhaps the most important message, we now find ourselves facing a digital transformation more unpredictable even by those who created the technologies.

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