[[ Prime ]] Machine Learning With Random Forests And Decision Trees: A Visual Guide For Beginners (English Edition) Author Scott Hartshorn – Andy-palmer.co.uk

Machine Learning With Random Forests And Decision Trees: A Visual Guide For Beginners (English Edition) Machine Learning Made Easy To UnderstandIf You Are Looking For A Book To Help You Understand How The Machine Learning Algorithms Random Forest And Decision Trees Work Behind The Scenes, Then This Is A Good Book For You Those Two Algorithms Are Commonly Used In A Variety Of Applications Including Big Data Analysis For Industry And Data Analysis Competitions Like You Would Find On KaggleThis Book Explains How Decision Trees Work And How They Can Be Combined Into A Random Forest To Reduce Many Of The Common Problems With Decision Trees, Such As Overfitting The Training DataSeveral Dozen Visual ExamplesEquations Are Great For Really Understanding Every Last Detail Of An Algorithm But To Get A Basic Idea Of How Something Works, In A Way That Will Stick With You Months Later, Nothing Beats Pictures This Book Contains Several Dozen Images Which Detail Things Such As How A Decision Tree Picks What Splits It Will Make, How A Decision Tree Can Over Fit Its Data, And How Multiple Decision Trees Can Be Combined To Form A Random ForestThis Is Not A TextbookMost Books, And Other Information On Machine Learning, That I Have Seen Fall Into One Of Two Categories, They Are Either Textbooks That Explain An Algorithm In A Way Similar To And Then The Algorithm Optimizes This Loss Function Or They Focus Entirely On How To Set Up Code To Use The Algorithm And How To Tune The ParametersThis Book Takes A Different Approach That Is Based On Providing Simple Examples Of How Decision Trees And Random Forests Work, And Building On Those Examples Step By Step To Encompass The Complicated Parts Of The Algorithms The Actual Equations Behind Decision Trees And Random Forests Get Explained By Breaking Them Down And Showing What Each Part Of The Equation Does, And How It Affects The Examples In QuestionPython Files Things Like Error Checking Or Complicated Conditionals Are Hard To Replicate Outside Of Code However Some Topics Work Quite Well In A Spreadsheet Topics Such As Entropy And Information Gain, Which Is How A Decision Tree Picks Its Splits, Can Be Easily Calculated In A Spreadsheet The Spreadsheet Used To Generate Many Of The Examples In This Book Is Available For Free Download, As Are All Of The Python Scripts That Ran The Random Forests If You Are Someone Who Learns By Playing With The Code, And Editing The Data Or Equations To See What Changes, Then Use Those Resources Along With The Book For A Deeper UnderstandingTopics CoveredThe Topics Covered In This Book AreAn Overview Of Decision Trees And Random ForestsA Manual Example Of How A Human Would Classify A Dataset, Compared To How A Decision Tree Would WorkHow A Decision Tree Works, And Why It Is Prone To OverfittingHow Decision Trees Get Combined To Form A Random ForestHow To Use That Random Forest To Classify Data And Make PredictionsHow To Determine How Many Trees To Use In A Random ForestJust Where Does The Randomness Come FromOut Of Bag Errors Cross Validation How Good Of A Fit Did The Machine Learning Algorithm Make Gini Criteria Entropy Criteria How To Tell Which Split On A Decision Tree Is Best Among Many Possible ChoicesAnd MoreIf You Want To Know About How These Machine Learning Algorithms Work, But Don T Need To Reinvent Them, This Is A Good Book For You


About the Author: Scott Hartshorn

Is a well-known author, some of his books are a fascination for readers like in the Machine Learning With Random Forests And Decision Trees: A Visual Guide For Beginners (English Edition) book, this is one of the most wanted Scott Hartshorn author readers around the world.



8 thoughts on “Machine Learning With Random Forests And Decision Trees: A Visual Guide For Beginners (English Edition)

  1. Cliente mixtapeclothing.co.uk Cliente mixtapeclothing.co.uk says:

    If you want to understand how works CART and RandomForest in a easy and brief way, this is your guide.Si quieres entender cmo funciona CART y RandomForest de forma fcil y breve, esta es tu gua.


  2. Inigo Astarloa Inigo Astarloa says:

    Want to know the basics of random forest technique to create algorithms This is a good start that will explain the whys and the how s.


  3. JC JC says:

    Sin grandes aspiraciones, hace muy facil aprender machine learning.Da informacion y ejemplos en la medida justa para seguir bien el libro.


  4. mixtapeclothing.co.uk Customer mixtapeclothing.co.uk Customer says:

    Great starter book on the concept High level selection of topics, conversational presentation, and most importantly a fast read This is an excellent strategy because it covers all the essentials, while still leaving you enough time to dig into some application or play with a build as you go along wh


  5. Edem Togbey Edem Togbey says:

    This book is well written and it is an easy introduction to the concepts introduced.I would recommend it if you are just trying to have a better sense of the principles of Random Forest algorithm You are not going to become an expert in the subject just by reading it.


  6. KierONeil KierONeil says:

    Best 3.00 I spent that day The author tells you exactly how Random Forests work and when and when not to use them The explainations are in plain English and you don t have to be a data scientist to understand It is fairly short, I m not sure how many pages, but it gives you everything you need to know about Random


  7. Arizona Charles Echo Arizona Charles Echo says:

    This is one of the best intro books available on any topic It does not hand wave you into formulae with integrations of infinite series There isn t one sentence that sounds like it was translated from Russian to Chinese and then to English by a German speaker No sir.It says things like, you draw a line through the box so t


  8. fitzalling fitzalling says:

    I am exploring artificial intelligence, machine learning, data mining and the like Prior books in is area have included Only Humans Need Apply, Artificial Intelligence W hat Everyone Needs to Know and Machine Learning for Absolute Beginners I decided to read Machine Learning With Random Forest and Decision Trees for my next step i


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