---
product_id: 50550860
title: "Machine Learning For Dummies"
price: "€ 41.06"
currency: EUR
in_stock: true
reviews_count: 13
url: https://www.desertcart.ie/products/50550860-machine-learning-for-dummies
store_origin: IE
region: Ireland
---

# Machine Learning For Dummies

**Price:** € 41.06
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- **What is this?** Machine Learning For Dummies
- **How much does it cost?** € 41.06 with free shipping
- **Is it available?** Yes, in stock and ready to ship
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## Description

Buy Machine Learning For Dummies 1 by Mueller, John Paul, Massaron, Luca (ISBN: 9781119245513) from desertcart's Book Store. Everyday low prices and free delivery on eligible orders.

Review: Attention to detail - Bought that as a new learning tool. It does the job. Good book.
Review: Surprising level of valuable Insight into ML for an Introductory Text - I am reading through rad Kuhns brilliant Applied Predictive Modelling, and various other detailed Machine learning texts. (Gave up on numerous books when the maths got too heavy. ) I bought this as a lighter summer refresher read, and to get into applying R Machine learning. This book is really quite impressive in providing a lot of useful insight and explanation into core machine learning principles and application. So after a rather slow start on justifications of machine learning and the necessary setting up of both Python and R Machine learning, the book eventually gets into the real subject matter at Chapt 9, and goes through basic probabilistic, naïve bayes, before concentrating on Gradient descents , Overfitting, PCA and SVD reduction, k Means clustering and K nearest neighbour classification algorithms are easily explained. Then in to the linear methods, Neural nets, SVMs and Random Forests are well explained. The EigenFaces explanation and execution for Face recognition was new to me, even though I have read a number of detailed deeper books on Machine learning. Extensive links are provided throughout and within context the text to offer expansions on detail, without detracting from the flow. If you want an easier introduction to Machine Learning, without being exposed to excessive maths to cloud your insights, this is an excellent way to get into the subject and start applying the technology in Python and R from the get go. Don't be a ML snob, get this book if you want to get into ML.

## Technical Specifications

| Specification | Value |
|---------------|-------|
| Best Sellers Rank | 1,446,224 in Books ( See Top 100 in Books ) 490 in Data Mining (Books) |
| Customer reviews | 4.3 4.3 out of 5 stars (510) |
| Dimensions  | 18.42 x 2.54 x 23.5 cm |
| Edition  | 1st |
| ISBN-10  | 1119245516 |
| ISBN-13  | 978-1119245513 |
| Item weight  | 590 g |
| Language  | English |
| Print length  | 432 pages |
| Publication date  | 19 July 2016 |
| Publisher  | For Dummies |

## Images

![Machine Learning For Dummies - Image 1](https://m.media-amazon.com/images/I/61bJpYocNhL.jpg)

## Customer Reviews

### ⭐⭐⭐⭐⭐ Attention to detail
*by A***I on 26 December 2019*

Bought that as a new learning tool. It does the job. Good book.

### ⭐⭐⭐⭐ Surprising level of valuable Insight into ML for an Introductory Text
*by J***S on 6 September 2016*

I am reading through rad Kuhns brilliant Applied Predictive Modelling, and various other detailed Machine learning texts. (Gave up on numerous books when the maths got too heavy. ) I bought this as a lighter summer refresher read, and to get into applying R Machine learning. This book is really quite impressive in providing a lot of useful insight and explanation into core machine learning principles and application. So after a rather slow start on justifications of machine learning and the necessary setting up of both Python and R Machine learning, the book eventually gets into the real subject matter at Chapt 9, and goes through basic probabilistic, naïve bayes, before concentrating on Gradient descents , Overfitting, PCA and SVD reduction, k Means clustering and K nearest neighbour classification algorithms are easily explained. Then in to the linear methods, Neural nets, SVMs and Random Forests are well explained. The EigenFaces explanation and execution for Face recognition was new to me, even though I have read a number of detailed deeper books on Machine learning. Extensive links are provided throughout and within context the text to offer expansions on detail, without detracting from the flow. If you want an easier introduction to Machine Learning, without being exposed to excessive maths to cloud your insights, this is an excellent way to get into the subject and start applying the technology in Python and R from the get go. Don't be a ML snob, get this book if you want to get into ML.

### ⭐⭐⭐⭐⭐ Good
*by A***I on 3 August 2020*

Best

## Frequently Bought Together

- Machine Learning for Dummies
- Machine Learning For Absolute Beginners: A Plain English Introduction (Data Storytelling: Learn AI, Data Science & Python Books for Beginners)

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*Store origin: IE*
*Last updated: 2026-03-13*