Markov Models: Understanding Markov Models and Unsupervised Machine Learning in Python with Real-World Applications
Robert Tier
- 出版商: CreateSpace Independ
- 出版日期: 2017-03-12
- 售價: $880
- 貴賓價: 9.5 折 $836
- 語言: 英文
- 頁數: 66
- 裝訂: Paperback
- ISBN: 1544657285
- ISBN-13: 9781544657288
-
相關分類:
Python、程式語言、Machine Learning
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商品描述
Discover How to Master Unsupervised Machine Learning and Crack Some of the Greatest Data Enigmas With Markov Models!
Would you like to unlock the mysteries of Data Science?Are you yearning to understand how to make educated predictions on the weather, horse races, your unborn baby’s facial features, or your boss’s next black mood?
Would you like a guide to explain these and many other “phenomenons” in clear, easy-to-understand language?
If the answer is ‘yes’ then you’ll want to Download this book today!
It’s never been easier to make predictions and smart analysis with the use of Markov Models. You don’t need a crystal ball or any wizardry. The only thing you need is science, some average high-school math skills and a decent knowledge of Python programming in order to solve the most perplexing problems.
And if you’re unfamiliar with Python programming or Machine learning, don’t worry, it’ll all be explained in this book.
Inside this book I’m going to show you how to be a data master. You’ll discover how to solve almost-unsolvable machine learning problems in no time. I’m going to show you the tools, code, and methods needed to effectively use Markov Models for any event or situation you come across.
Download This Book Today and Discover:
- How to program with Python
- The secrets behind unsupervised machine learning
- How to use Markov Models to master machine learning
- How to make predictions with Markov Models
- How to use Markov Chains
- How to use Hidden Markov Models
- The 3 main problems of Markov Models and how to overcome them
- How to use Python to find the probability of longer and more complex problems
- What packages to get for using Python for Markov Models
- How to implement HMM algorithms
- How to build a speech recognizer
- A code that will turn gibberish into understandable text
- How to forecast the weather
- The secrets behind Queueing Theory
- The Markov Mutation Model
- The Secret Structure of Google’s PageRank Algorithm
- How to perform Google PageRank in Python And much, much more!
So save yourself some time and frustration trying to learning these intricate algorithms on your own. Let me help you get started quickly and easily.
Download Markov Models today and Enjoy Mastering Data Science!
商品描述(中文翻譯)
發現如何精通無監督機器學習並解開一些最偉大的數據謎團,與馬爾可夫模型一起!你想解開數據科學的神秘嗎?你渴望了解如何對天氣、賽馬、未出生嬰兒的面部特徵或老闆的下一個壞情緒做出有根據的預測嗎?你想要一個指南以清晰易懂的語言解釋這些和其他許多“現象”嗎?如果答案是“是”,那麼你會想要立即下載這本書!使用馬爾可夫模型進行預測和智能分析從未如此容易。你不需要水晶球或任何巫術。你唯一需要的是科學、一些普通高中數學技能和對Python編程的良好知識,以解決最棘手的問題。如果你對Python編程或機器學習不熟悉,不用擔心,這本書會解釋一切。在這本書中,我將向你展示如何成為數據大師。你將在短時間內發現如何解決幾乎無法解決的機器學習問題。我將向你展示使用馬爾可夫模型有效解決任何事件或情況所需的工具、代碼和方法。立即下載這本書,並發現以下內容:如何使用Python編程、無監督機器學習背後的秘密、如何使用馬爾可夫模型精通機器學習、如何使用馬爾可夫鏈、如何使用隱藏馬爾可夫模型、馬爾可夫模型的三個主要問題以及如何克服它們、如何使用Python找到更長、更複雜問題的概率、使用Python進行馬爾可夫模型所需的套件、如何實現HMM算法、如何構建語音識別器、將胡言亂語轉換為可理解文本的代碼、如何預測天氣、排隊理論背後的秘密、馬爾可夫突變模型、Google PageRank算法的秘密結構、如何在Python中執行Google PageRank等等!所以,不要浪費時間和精力自己學習這些複雜的算法。讓我幫助你快速且輕鬆地入門。立即下載馬爾可夫模型,享受精通數據科學的樂趣!