Learning Data Mining with Python: Harness the power of Python to analyze data and create insightful predictive models

Robert Layton

$27.98 ~~$39.99~~

3.7 (7 Ratings)

eBook Jul 2015 344 pages 1st Edition

Robert Layton

$27.98 ~~$39.99~~

3.7 (7 Ratings)

eBook Jul 2015 344 pages 1st Edition

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Description

If you are a programmer who wants to get started with data mining, then this book is for you.

Who is this book for?

If you are a programmer who wants to get started with data mining, then this book is for you.

What you will learn

Apply data mining concepts to realworld problems
Predict the outcome of sports matches based on past results
Determine the author of a document based on their writing style
Use APIs to download datasets from social media and other online services
Find and extract good features from difficult datasets
Create models that solve realworld problems
Design and develop data mining applications using a variety of datasets
Set up reproducible experiments and generate robust results
Recommend movies, online celebrities, and news articles based on personal preferences
Compute on big data, including realtime data from the Internet

What do you get with eBook?

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Download this book in EPUB and PDF formats

Access this title in our online reader with advanced features

DRM FREE - Read whenever, wherever and however you want

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Python Data Visualization Cookbook (Second Edition)

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Anon Oct 24, 2015

Pretty good book on the subject matter, I especially enjoyed the variety in examples for applications of machine learning. Other books similar to the subject like Mastering Machine Learning with Scikit-Learn are alright, but this is definitely a cool addition to such a library or collection of similar topic books.The author uses scikit-learn, python libraries in general. Pretty easy to understand, and definitely nice as a reference in case you are facing a similar problem at work or school and want to consult with a tutorial in a book.Definitely worth looking into.

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Amazon Reader Aug 23, 2015

This is the most excellent book on Data Mining and Python I have come across. The books comes with plenty of code examples explained in simple and easy to understand language. I would highly recommend this book to novice users and enthusiasts.

Mouha Apr 13, 2016

The Robert's book is one of those I've finished used and reuse. I have many books on AI, Machine learning /data mining . Very few give me access to the minimum knowledge so I'd be able to use AI by myself. Jeff Heaton book was one of them, now I can add this book because it allows you to understand the main algorithms in this area, in a way that even you are not strong in maths through Python code you can really apply each algorithms in a minute. Really easy and understandable. Some could argue that the author doesn't dive deeply in the explanation: I think this is on purpose, and btw there are so much book about the theory. I didn't put 5 start because of some (small) cons : In chapter 8 "Beating Captcha...." The author would have use a recent framework like FANN instead of Pybrain which seems to be abandoned since years. This is not a showstopper anyway. I was so happy to use NN which for me is a kind of magic sometimes.

Dimitri Shvorob Aug 20, 2016

Wishing to learn Python's machine-learning toolkit - I am an emigrant from R Country - I rounded up several relevant books, and set out to narrow the field to one or two suitable for further study. My haul included (in no particular order)"Machine Learning in Python" by Bowles, published in 2015 by Wiley, 360 pages, $25 for the cheapest hardcopy now available from Amazon (including shipping)"Designing Machine Learning Systems with Python" by Julian, 2016, Packt, 232 pages, $42"Mastering Python for Data Science" by Madhavan, 2015, Packt, 294 pages, $39"Learning Data Mining with Python" by Layton, 2015, 369 pages, $43"Python Data Science Cookbook" by Subramanian, 2015, 347 pages, $48"Data Science From Scratch" by Grus, 2015, 330 pages, $24"Learning scikit-learn" by Moncecchi and Garreta, 2013, 118 pages, $28"Building Machine Learning Systems with Python" by Coelho and Richert, 2015, 305 pages, $49"Python Machine Learning" by Raschka, 2015, 454 pages, $34The whittling-down turned out to be harder than expected: Python titles are better than R counterparts, and Madhavan's book alone was easy to dismiss. Subramanian, Moncecchi-Garreta and Julian did not make the cut based on comparison with alternatives, but were not of themselves bad. Grus is the beginner's best bet - beginners can stop reading here - while Bowles is a book which I like a lot, but which may be a bit too specialist. As a reviewer, thinking about what other "intermediate" readers might find useful, I end up pointing to the trio of Raschka, Layton and Coelho-Richert as the books worth choosing from.I distinguish Raschka, in appreciation of his more pedagogical style - or maybe I am just giving the top spot to the thickest book! - but the other two titles are definitely worth checking out. Compared to Coelho-Richert (CR), Layton's book surveys a wider range of algorithms - a good third of CR's page count is devoted to text analysis, which means less space for everything else - but strangely neglects regression, my own primary interest. (This is why I dock one star). The writing is more "cohesive" and methodical - but while Coelho and Richert know to "liven up" the early chapters with visualizations, Layton does not use "matplotlib" till page 98. (And after that, you see charts in the chapter on graph mining - notably, a topic you don't find in the other two books). Get both, and see which one you prefer.

Amazon Customer Aug 04, 2016

Fine for introducing the learner to data mining with Python...but not much else. Many typos in the code and text, key concepts and vocabulary poorly assumed to be understood by the reader. Not good continuity either. Definitely written by a committee.

Learning Data Mining with Python: Harness the power of Python to analyze data and create insightful predictive models

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