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Inkluderar namnen: T Segaran, Toby Segaran

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A relevant text in 2010, outdated and superseded in 2020.

A testament to how quickly this area has developed. There are now many many additional computational options than those covered here.
yates9 | 3 andra recensioner | Feb 28, 2024 |
This book does a good job making an introduction of machine learning technologies to the average programmer. This is its main merit. Having said that, the introduction to the subjects is very simplified, so you'll need further reference to actually implement anything at all. It's full of Python code snippets only work to make the subject appear accessible to the programmer, and look like waffle to me. Mathematical formulas in which code snippets are based can only be found (without further explanation) on an annex. Algorithm alternatives or optimizations for real-life operations are not described. But in the end, this is the objective of this book. My main criticism would be that the book doesn't fully succeed at explaining exactly what you should use each technique for and which are their pros and cons.

To sum up, read this book if you are a programmer, you have no previous knowledge on machine learning topics and you want a math-free introduction on the subject.
… (mer)
jmones | 3 andra recensioner | Jun 18, 2012 |
Note: this review is based on a pre-release copy of the book.When I first encountered RDF years ago, I wrote it off. It seemed unlikely that it would get much use. But the recent arrival of collections of so-called 'semantic' data via organizations like Freebase, has made me rethink that position. Of course, figuring out how to make use of this data is another proposition, but Programming the Semantic Web serves as a solid introduction and survey of the tools and techniques necessary to make it into something worth your effort.I can say that after reading this book, I finally get the concept of semantic data and the relationships it defines. The book begins by walking through the building of a basic triple-store (that is, a data store full of triples -- if you don't know what they are, you should read the book). This and the ensuing discussion of the graph structures built from these triples leads into an introduction to RDF. In this context, it really starts to make sense.The examples in this book are quite useful and not too abstract. For instance, one of the examples shows how to take legacy data from an RDBMS and generate an RDF graph, going from implicit to explicit semantics. Another uses a programmatic version of the popular 'Six Degrees of Kevin Bacon' trivia game to show how you can use a semantic database of movie data to find the shortest path between two given actors (one, clearly, being the ever-popular Kevin Bacon). The final example in the book shows in brief how you might build a system for managing job listings for various companies. The example is thorough and reasonably complex, but still manages to cover a lot of ground, including integration with libraries for visualizing the data. The majority of the examples in the book are written in Python, though Java makes an appearance in the toolkit chapter, which covers various libraries available for working with RDF.One item of note is that in the conclusion, the authors do stress caution about this technology or at least particular approaches or tools. It's important to sort out the hype from the real deal and it takes a realists perspective to understand that semantic web tools have been considered the 'next great thing' by various pundits for much of the last decade -- clearly it's not what some envisioned back when the ideas were first brought forth.I can't say that I'm going to be rushing out and building next great application after having read this book, nor will I be looking at bring RDF into each system I build. But I do have an appreciation for what semantic data and RDF can bring to aspects of future projects I might work on. I would have enjoyed seeing more details about using external, non-semantic data source and using that data in a semantic graph, but given the range of material to cover, I can understand that this could be an entire book of it's own.… (mer)
tlockney | Feb 5, 2012 |
For an interaction designer, this edited collection has a refreshing approach: It starts from the concept of data, and develops many aspects -- from database organization and query efficiency to strategies for guerilla data collection projects, from accessing the deep web to visualization and digital data-based arts. After reading it, my sense was that I had received a glimpse of important concepts and concerns in several specialized fields related to my own -- and I also dog-eared a couple of chapters as immediately relevant to future work in information visualization and open-data aggregation.… (mer)
jonas.lowgren | 2 andra recensioner | Sep 15, 2011 |

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