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AI and Machine Learning for Coders: A Programmer's Guide to Artificial Intelligence
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
390 pages, Paperback
First published April 1, 2021
175 people are currently reading
437 people want to read
About the author
Laurence Moroney
48 books30 followersLaurence Moroney is the author of more books than he’s prepared to admit. After several best selling programming books, his first Young Adult novel “The Fourth World” became a #1 book on Amazon Kindle, spawned two sequels “The Million Year Journey” and “The Legend of the Locust”, and is currently being shopped around studios for a potential movie. “Space Cadets” is his latest, a cutting edge science fiction novel, based on real science that starts a new series charting out humanity’s course to the stars. He’s presently working on the sequel “The Quiet World”, which he hopes to finish in 2015. For his day job, Laurence works as a Developer Advocate for Google, where he is constantly counting his blessings for being part of the best workplace in the world…
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Displaying 1 - 7 of 7 reviews
March 23, 2022
A pretty good introduction to tensorflow in python. I followed along with the example code, there were a few minor issues with compatibility, and I would recommend the same. If you don't plan to get your hands dirty, then this book is of very little value. The explanations of the techniques are pretty brief, you will not gain a great understanding from this book alone. I tried to start this book prior to learning python and had great difficulty. My attempts after learning python was much smoother.
May 13, 2025
I’m a tad suspicious about listening to books that are too deep in the weeds with code. If they’re about programming concepts, audiobooks can be suitable, but if they involve code like this one, I like to have a physical picture of the lines of code. However, I was pleasantly surprised that this book conveyed many ideas despite communicating code aurally, too. Artificial intelligence (AI) and machine learning (ML) are huge topics today. I read this book just to supplement my broader knowledge, but while reading, I found a few applications that relate directly to my work. I’m going to try out TensorFlow, the software demoed here, in my work this week. I can see where it might be a lot more effective for my users than calling remote, server-based services from OpenAI.
This book features the Python-based TensorFlow as the main framework. It shows how to use it to build your own large-language model (LLM). When I started this book, I didn’t realize that it’d also demonstrate how to use TensorFlow in web situations, which is my main domain. TensorFlowJS can use an LLM built in Python to perform features in a website. This book also describes how an API can house AI/ML models from TensorFlow. Mobile devices and embedded systems like Raspberry Pi receive their own chapter, too, due to their limited processing capabilities.
Honestly, I did not have super-high expectations when I read this book. I just wanted to fill in my AI knowledge from a programmer’s perspective. I did not expect to apply the knowledge directly. Instead, I found my mind engaged with new ways to think about AI – even from a non-programmer’s perspective. I’m now able to better explain how to maximize AI use to my non-IT, scientific team. And I’m really chomping at the bit to see whether TensorFlowJS can meet the needs of my latest project. It’s a total joy when a book surprises with its intellectual depth and applicability. This book did both in spades, and I’m glad I listened to it!
This book features the Python-based TensorFlow as the main framework. It shows how to use it to build your own large-language model (LLM). When I started this book, I didn’t realize that it’d also demonstrate how to use TensorFlow in web situations, which is my main domain. TensorFlowJS can use an LLM built in Python to perform features in a website. This book also describes how an API can house AI/ML models from TensorFlow. Mobile devices and embedded systems like Raspberry Pi receive their own chapter, too, due to their limited processing capabilities.
Honestly, I did not have super-high expectations when I read this book. I just wanted to fill in my AI knowledge from a programmer’s perspective. I did not expect to apply the knowledge directly. Instead, I found my mind engaged with new ways to think about AI – even from a non-programmer’s perspective. I’m now able to better explain how to maximize AI use to my non-IT, scientific team. And I’m really chomping at the bit to see whether TensorFlowJS can meet the needs of my latest project. It’s a total joy when a book surprises with its intellectual depth and applicability. This book did both in spades, and I’m glad I listened to it!
July 14, 2020
I have reviewed and read this book and it was worth it.
The book will lead you through a journey of practicing and learning by doing Machine Learning while reading the book.
This book cover topics from how to perform your first model, train and evaluate it on areas such as Linear Regression, Classification, Computer Vision , NLP , Sequence Model, Time Series. And not only that but also you will go through how to deploy and render it on mobile, browser etc.
A valuable piece as it contains tools from the Tensorflow ecosystem and how to use them, like Tensorflow datasets and Tensorflow hub or the hyperparameter tuning from Keras.
As soon as the book is available to the public you should read it, it will serve fantastically as point of reference if you are working on Tensorflow.
The book will lead you through a journey of practicing and learning by doing Machine Learning while reading the book.
This book cover topics from how to perform your first model, train and evaluate it on areas such as Linear Regression, Classification, Computer Vision , NLP , Sequence Model, Time Series. And not only that but also you will go through how to deploy and render it on mobile, browser etc.
A valuable piece as it contains tools from the Tensorflow ecosystem and how to use them, like Tensorflow datasets and Tensorflow hub or the hyperparameter tuning from Keras.
As soon as the book is available to the public you should read it, it will serve fantastically as point of reference if you are working on Tensorflow.
This entire review has been hidden because of spoilers.
December 7, 2023
Does an excellent job of doing what it sets out to do. Moroney based this book on a course that he teaches, and his combination of mastery of the material and interweaving of examples/"hands on" learning really shines.
While I certainly don't expect to be an AI/ML developer after listening to a book for two days, it was a very good "first pass" at the material, which I will further explore by doing the code alongs and diving into the author's GitHub directory.
*Note that this book is specifically about ML using TensorFlow. While this is one of the main ways to do it in 2023, those who want to learn about Sci-Kit Learn, PyTorch, etc. will have to look elsewhere.
While I certainly don't expect to be an AI/ML developer after listening to a book for two days, it was a very good "first pass" at the material, which I will further explore by doing the code alongs and diving into the author's GitHub directory.
*Note that this book is specifically about ML using TensorFlow. While this is one of the main ways to do it in 2023, those who want to learn about Sci-Kit Learn, PyTorch, etc. will have to look elsewhere.
July 7, 2025
Unfortunately confusing name for this book in 2025. AI these days is about LLMs, Agentic AIs, ChatGPTs, etc. This book was written before the recent AI boom, so it doesn't cover all these trendy topics. The author is not at fault, of course. Before ChatGPT & CoPilot, the name of this book was perfectly fair.
The naming confusion aside, the book is primarily a primer on TensorFlow and its applications in various domains. It's an OK book, in that regard.
The naming confusion aside, the book is primarily a primer on TensorFlow and its applications in various domains. It's an OK book, in that regard.
September 17, 2023
Good overviews of aspects of ML. Way to much focus on tuning though for an introductory how to book.
March 25, 2024
It's a great book for first high overview how deep learning system works.
It's not a deep learning under the hood mathematics book.
I think that for first steps into deep-learning it's a great, but it's a paradox at the same time i think that if you read it with previous theory knowledge as neural networks works like, layers, optimizers, conv layers, etc... could be benefitial as well. Maybe if you grab this book with that prior-knowledge could give you a more edged sword than read this without prior-knowledge.
Personally, i think that, coming from Machine Learning theory and Deep learning mathematically with "ML and DL courses from DeepLearning.AI" and some Medium posts that i read, this books gives me the how and end-to-end deep learning system works, and also an engineering point of view to optimize it, and some integrations with other devices than only web development.
It's not a deep learning under the hood mathematics book.
I think that for first steps into deep-learning it's a great, but it's a paradox at the same time i think that if you read it with previous theory knowledge as neural networks works like, layers, optimizers, conv layers, etc... could be benefitial as well. Maybe if you grab this book with that prior-knowledge could give you a more edged sword than read this without prior-knowledge.
Personally, i think that, coming from Machine Learning theory and Deep learning mathematically with "ML and DL courses from DeepLearning.AI" and some Medium posts that i read, this books gives me the how and end-to-end deep learning system works, and also an engineering point of view to optimize it, and some integrations with other devices than only web development.
Displaying 1 - 7 of 7 reviews