ePub: Download Markov Models Understanding Unsupervised Applications eBook (KINDLE, PDF, MOBI) + Audio Version

  • File Size: 1990 KB
  • Print Length: 72 pages
  • Publisher:
  • Publication Date: March 4, 2017
  • Language: English

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Certain, I had only basic knowledge of Markov Models, but it was great to see the Python code!!! I really really felt like this is a great commence to HMM beyond what I could have found searching myself, because people always assume you understand some concepts before & rushing through small details. While this book will rush, it is a well calculated rush, since the author gives just enough keywords to look into without feeling lost. Thank you again for the wonderful read & the wonderful code. This is delightful to see probability models in Python code (':, I like the book. But I actually gave 3 stars for the Kindle one I actually acquired because it consists of too many typos. I actually have gotten some backdrop in probability so I actually wished I could you know what their right words should be., Introductory and well organized., Lots of code without a write up of the intent. It is the intent at the rear of the code that I actually like to read about., Junk. No clear idea of who his audience is, no explanations of important tools used with HMM, just copies of code with little or no réflexion, poor examples, sloppily written and not proof read., This book is a comprehensive treatment of inference for Markov models, including both algorithms and statistical theory. It provides just about all information that tackles about the subject, how to use it, the secrets at the rear of unresponsive machines, how to use hidden Markov models and a lot more. There's also a short discussion on Python encoding. I believe, this book will suit anybody with an interest in inference for stochastic processes, and it will be useful for researchers and practitioners in areas such as data, signal processing, communications executive, control theory, econometrics, financial and more., It's completely possible that I'll be bowled over by the depth expertise this guide provides me. Hard to say - I just acquired it minutes ago, and haven't yet read it.

For the record, Now i'm optimistic, and will upgrade this review if I actually find the book to be as excellent as I'm sure the creator intended it to be.

However, in reading the other reviews, I had been struck by one of the (mild) complaints, on July 2, 2017 about it delivering less than it guaranteed. I read the full list of things promised in the description of the book, and decided that the comment was both spot-on and helpful.

Plus then I acquired the book, partly because the comment referenced above said " not bad for the price", and mainly because I wanted the right, as a verified buyer, to point out the cartoonishly hyperbolic overreach of the promises, some absolutely incoherent (e. g. " How to use Python to find the probability of longer and more complex problems". What? ) made about this, only 72 page long guide.

I'm 100% certain that my money was not wasted, because there's 0% chance the book is without value at all, but having gotten this complaint off my chest, I will not again buy any book, however well reviewed, that makes such a jumbled mess of frankly absurd claims for itself.

Seriously, it would be better simply to say " You were intrigued by the name, it's an inexpensive guide, live just a little, buy the book, enjoy yourself, and don't force me to feel rhapsodic about all the imaginary things it will do for you", Excellent book, can’t say enough good things about it. The coverage is well thought out and the answers are extremely thorough. Really helped me learn and understand everything about Markov Models and its uses!

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Markov Models Understanding Unsupervised Applications
Average Rating: 4.75
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