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  • Building Machine Learning Systems with Python

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Willi Richert
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Building Machine Learning Systems with Python

by Willi Richert (Author), Luis Pedro Coelho (Author)
4.1 out of 5 stars (61)
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Expand your Python knowledge and learn all about machine-learning libraries in this user-friendly manual. ML is the next big breakthrough in technology and this book will give you the head-start you need.


Key Features:

  • Master Machine Learning using a broad set of Python libraries and start building your own Python-based ML systems
  • Covers classification, regression, feature engineering, and much more guided by practical examples
  • A scenario-based tutorial to get into the right mind-set of a machine learner (data exploration) and successfully implement this in your new or existing projects


Book Description:

Machine learning, the field of building systems that learn from data, is exploding on the Web and elsewhere. Python is a wonderful language in which to develop machine learning applications. As a dynamic language, it allows for fast exploration and experimentation and an increasing number of machine learning libraries are developed for Python.Building Machine Learning system with Python shows you exactly how to find patterns through raw data. The book starts by brushing up on your Python ML knowledge and introducing libraries, and then moves on to more serious projects on datasets, Modelling, Recommendations, improving recommendations through examples and sailing through sound and image processing in detail. Using open-source tools and libraries, readers will learn how to apply methods to text, images, and sounds. You will also learn how to evaluate, compare, and choose machine learning techniques. Written for Python programmers, Building Machine Learning Systems with Python teaches you how to use open-source libraries to solve real problems with machine learning. The book is based on real-world examples that the user can build on.


Readers will learn how to write programs that classify the quality of StackOverflow answers or whether a music file is Jazz or Metal. They will learn regression, which is demonstrated on how to recommend movies to users. Advanced topics such as topic modeling (finding a text's most important topics), basket analysis, and cloud computing are covered as well as many other interesting aspects.Building Machine Learning Systems with Python will give you the tools and understanding required to build your own systems, which are tailored to solve your problems.



What You Will Learn:

  • Build a classification system that can be applied to text, images, or sounds
  • Use scikit-learn, a Python open-source library for machine learning
  • Explore the mahotas library for image processing and computer vision
  • Build a topic model of the whole of Wikipedia
  • Get to grips with recommendations using the basket analysis
  • Use the Jug package for data analysis
  • Employ Amazon Web Services to run analyses on the cloud
  • Recommend products to users based on past purchases
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Previous slide of product details
  1. ISBN-10
    1782161406
  2. ISBN-13
    978-1782161400
  3. Publisher
    Packt Publishing
  4. Publication date
    July 26, 2013
  5. Language
    English
  6. Dimensions
    7.5 x 0.66 x 9.25 inches
  7. Print length
    271 pages
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From the brand

Editorial Reviews

About the Author

Willi Richert has a PhD in machine learning/robotics, where he has used reinforcement learning, hidden Markov models, and Bayesian networks to let heterogeneous robots learn by imitation. Now at Microsoft, he is involved in various machine learning areas, such as deep learning, active learning, or statistical machine translation. Willi started as a child with BASIC on his Commodore 128. Later, he discovered Turbo Pascal, then Java, then C++ - only to finally arrive at his true love: Python.

Luis Pedro Coelho is a computational biologist who analyzes DNA from microbial communities to characterize their behavior. He has also worked extensively in bioimage informatics - the application of machine learning techniques for the analysis of images of biological specimens. His main focus is on the processing and integration of large-scale datasets. He has a PhD from Carnegie Mellon University and has authored several scientific publications. In 2004, he began developing in Python and has contributed to several open source libraries. He is currently a faculty member at Fudan University in Shanghai.

Product details

  • Publisher ‏ : ‎ Packt Publishing
  • Publication date ‏ : ‎ July 26, 2013
  • Language ‏ : ‎ English
  • Print length ‏ : ‎ 271 pages
  • ISBN-10 ‏ : ‎ 1782161406
  • ISBN-13 ‏ : ‎ 978-1782161400
  • Item Weight ‏ : ‎ 1.15 pounds
  • Dimensions ‏ : ‎ 7.5 x 0.66 x 9.25 inches
  • Best Sellers Rank: #4,454,467 in Books (See Top 100 in Books)
  • Customer Reviews:
    4.1 out of 5 stars (61)

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Willi Richert

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Customer reviews

4.1 out of 5 stars
61 global ratings

Customers say

Customers find the book provides a hands-on approach to machine learning using Python, making it particularly suitable for Python experts. The explanations receive mixed feedback, with some finding them well thought out while others consider them sketchy.
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7 customers mention practical, 7 positive, 0 negative
Customers appreciate the practical approach of the book, particularly its hands-on approach to machine learning using Python.
...This book has a hands on approach to ML using python. Which is great. But thats where the greatness ends. 1....Read more
Dives right in. Perfect for the python expert, not so good for a beginner python programmer.Read more
I love this book. It provides a lot of practical, clear examples and explanations that a lot of other machine learning courses just don't provide or...Read more
...it was theoretically exactly what I was looking for, a practical guide to getting up and running with Machine Learning and some of it major Python...Read more
5 customers mention explanations, 3 positive, 2 negative
Customers have mixed opinions about the explanations in the book, with some finding them well thought out, while others report that they are sketchy and not thorough.
I love this book. It provides a lot of practical, clear examples and explanations that a lot of other machine learning courses just don't provide or...Read more
I think some of the lessons are a little convoluted/ round-about ways of accomplishing goals, but it's holistically pretty good.Read more
...illustrates many useful machine learning techniques with well thought out explanations.Read more
...1. The explanations in the book in general are sketchy and not thorough. 2. They use code snippets in the book....Read more

Top reviews from the United States

  • Amazon Customer
    5.0 out of 5 stars Practical, clear code examples.
    Reviewed in the United States on January 5, 2014
    Format: KindleVerified Purchase
    I love this book. It provides a lot of practical, clear examples and explanations that a lot of other machine learning courses just don't provide or are too slow to reach (for my ADD). I love the way the author gives enough explanation for you to grasp the concepts involved with practical machine learning systems, without going into so much detail that you just give up halfway through. 5 stars, I'm definitely looking forward to more books of this quality from Willi Richert.

    Daniel
    One person found this helpful
    Helpful
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  • Dr. Howard B. Bandy
    4.0 out of 5 stars Practical advice with useful examples
    Reviewed in the United States on July 7, 2014
    Format: PaperbackVerified Purchase
    Both authors earned PhD degrees related to machine learning, and both are employed applying machine learning to real world problems.

    The book illustrates many useful machine learning techniques with well thought out explanations.
    One person found this helpful
    Helpful
     Report
  • J_Stout
    5.0 out of 5 stars Good Learning Tool
    Reviewed in the United States on November 4, 2013
    Format: PaperbackVerified Purchase
    This book is a good addition to other theoretical books. Although much of the information could be gained through websites, this is a more condensed and straightforward way to learn it. This is not an all in one book and does rely on the reader to fill in the gaps with theoretical knowledge and python programming knowledge. It is well written and easy to follow.
    2 people found this helpful
    Helpful
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  • Subhrajit Bhattacharya
    3.0 out of 5 stars Hands on approach to ML using Python. Thats great - but thats where the greatness ends
    Reviewed in the United States on March 15, 2015
    Format: KindleVerified Purchase
    I can not understand how so many people have given this book a 4 or 5 rating. 3 is the max that can be given.

    This book has a hands on approach to ML using python. Which is great. But thats where the greatness ends.

    1. The explanations in the book in general are sketchy and not thorough.

    2. They use code snippets in the book. Complete code has to be downloaded. However the way the code snippets are explained
    does little to help understand the complete code. It's better to read the complete code directly.

    3. The code is not portable. I had to make some modifications to make some of the routines work.

    4. In some cases I just could not make the code work.

    5. They do not explain the scikit and numpy routines at a decent level of detail. So you are often left wondering how the code works,
    and then you have to read the scikit or numpy routine to figure this out.

    6. There are several perl files for a given chapter. I have no idea in which sequence to go through them.

    If you are a decent python programmer, and you have decent knowledge of numpy and scikits, then you will probably not find the book very frustrating. Otherwise, be ready to be frustrated.

    I think the reason this book is still selling is its cheap, and i think there is nothing better available.

    There a few books which directly discus scikits-learn. Maybe people should look at them.
    3 people found this helpful
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  • Fitzgerald Stowers
    5.0 out of 5 stars I highly recommend this book to anyone who has programmed in Python ...
    Reviewed in the United States on August 4, 2014
    Format: KindleVerified Purchase
    I highly recommend this book to anyone who has programmed in Python and are looking to take it to the next level!
    One person found this helpful
    Helpful
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  • Schwallie
    2.0 out of 5 stars Too Many Bugs in Code
    Reviewed in the United States on March 20, 2014
    Format: KindleVerified Purchase
    Unfortunately this book is basically a non-starter. I can't seem to get through any of it as the code doesn't work in most cases. I agree with a previous reviewer -- I could spend my time debugging and making it work, but that's not why I bought the book. I shouldn't have to jump through hurdles to read this.

    I wish I could get a refund.
    19 people found this helpful
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  • Kindle Customer
    4.0 out of 5 stars but seems like it could use more editing and a bit more ...
    Reviewed in the United States on February 14, 2015
    Format: KindleVerified Purchase
    There aren't a lot of reasonably priced intermediate/advanced books on this topic. It's a strong book, but seems like it could use more editing and a bit more polish to make it a great book. I'd still recommend it, but a better book is "Python for Data Analysis"
    Helpful
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  • Cyril Michy
    5.0 out of 5 stars Five Stars
    Reviewed in the United States on July 20, 2014
    Format: PaperbackVerified Purchase
    One of the best book in that field I have never read.
    One person found this helpful
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Top reviews from other countries

  • Di CAMILLO JIM
    1.0 out of 5 stars Old book :-(
    Reviewed in France on February 29, 2024
    Format: PaperbackVerified Purchase
    Old book 2013 version
    Customer image
    Di CAMILLO JIM
    1.0 out of 5 stars
    Old book :-(

    Reviewed in France on February 29, 2024
    Old book 2013 version
    Images in this review
    Customer image Customer image
    Report
  • SRC
    5.0 out of 5 stars Excellent self-learning book
    Reviewed in India on February 11, 2016
    Verified Purchase
    Excellent book ... simple and structured introduction to python and data science using python ... plus well worked out examples ... one of the few self-learning books available on the market
    Report
  • Zorba the Greek
    4.0 out of 5 stars Not for begineers.
    Reviewed in India on March 16, 2018
    Format: PaperbackVerified Purchase
    Good one. Not for begineers. It does not teach ml it teaches the programming.
    Report
  • Anwesh Mishra
    5.0 out of 5 stars Five Stars
    Reviewed in India on September 7, 2015
    Verified Purchase
    awesome book
    Report
  • Manasa
    2.0 out of 5 stars Two Stars
    Reviewed in India on September 13, 2017
    Format: PaperbackVerified Purchase
    Not a good book for beginners.
    Not explained code in details we will get lot of confusions.
    Report
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