---
product_id: 533083667
title: "AI and Machine Learning for Coders: A Programmer's Guide to Artificial Intelligence"
price: "B/.4"
currency: PAB
in_stock: true
reviews_count: 9
url: https://www.desertcart.com.pa/products/533083667-ai-and-machine-learning-for-coders-a-programmers-guide-to
store_origin: PA
region: Panama
---

# AI and Machine Learning for Coders: A Programmer's Guide to Artificial Intelligence

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desertcart.com: AI and Machine Learning for Coders: A Programmer's Guide to Artificial Intelligence (Audible Audio Edition): Laurence Moroney, Timothy Howard Jackson, Ascent Audio: Books

Review: Exceeded expectations: I hope to use TensorFlow tomorrow! - 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!
Review: Very Practical, Memorable Introduction - I’d summarize this in a sentence as “an introduction to machine learning with TensorFlow,” TensorFlow being Google’s platform for building, training and distributing AI models. I enjoyed this book a lot more than than 100-Page Book on Machine Learning, because the examples and scenarios felt more practice and grounded in the kind of interface that I would have with AI/ML in the workplace. This book was more focused on tools than theory, and went into theoretical concepts when needed to demystify the parameters/API of various TensorFlow toolsets. So far, this has been my favorite introduction to the topic, and I have ready 3-5 different AI/ML books.

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![AI and Machine Learning for Coders: A Programmer's Guide to Artificial Intelligence - Image 1](https://m.media-amazon.com/images/I/81RnKN6BRuL.jpg)

## Customer Reviews

### ⭐⭐⭐⭐⭐ Exceeded expectations: I hope to use TensorFlow tomorrow!
*by S***N on 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!

### ⭐⭐⭐⭐⭐ Very Practical, Memorable Introduction
*by R***E on July 12, 2024*

I’d summarize this in a sentence as “an introduction to machine learning with TensorFlow,” TensorFlow being Google’s platform for building, training and distributing AI models. I enjoyed this book a lot more than than 100-Page Book on Machine Learning, because the examples and scenarios felt more practice and grounded in the kind of interface that I would have with AI/ML in the workplace. This book was more focused on tools than theory, and went into theoretical concepts when needed to demystify the parameters/API of various TensorFlow toolsets. So far, this has been my favorite introduction to the topic, and I have ready 3-5 different AI/ML books.

### ⭐⭐⭐⭐⭐ Really loved this book
*by D***R on November 29, 2020*

Tonight, I completed reading of Laurence Moroney’s book “AI and Machine Learning for Coders”. I enjoyed this book from cover to cover, and I am especially thankful for a few things. First, this book did a great job of explaining how tensorflow can be used to solve different types of problems, such as computer vision, natural language processing, and time series forecasting. It even went into text generation, which got my creativity going. Second, this book is written for coders, but it does explain how neural networks work at a high level. It doesn’t drop a wall of math on the reader, which I appreciated. I feel much more comfortable now, after reading this. And finally, the book ends by discussing interpretability, bias/fairness, and Google’s AI principles. I found that to be a beautiful ending. I give this five stars. The few issues I had were trivial. This book is outstanding. I’m so much better off for having read it.

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*Product available on Desertcart Panama*
*Store origin: PA*
*Last updated: 2026-05-19*