Mastering machine learning with Python in six steps : a practical implementation guide to predictive data analytics using Python /

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Your practical guide to moving from novice to master in machine learning with Python 3 in six steps, this book covers fundamental to advanced topics gradually helping beginners become worthy practitioners. --

Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Swamynathan, Manohar (Autor)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: [California] : Apress, [2019]
Edición:Second edition.
Temas:
Python (Computer program language)
Machine learning.
Artificial intelligence.
Artificial Intelligence
Python (Langage de programmation)
Apprentissage automatique.
Intelligence artificielle.
artificial intelligence.
Acceso en línea:Texto completo (Requiere registro previo con correo institucional)

MARC

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100 1 |a Swamynathan, Manohar,  |e author. 
245 1 0 |a Mastering machine learning with Python in six steps :  |b a practical implementation guide to predictive data analytics using Python /  |c Manohar Swamynathan. 
250 |a Second edition. 
264 1 |a [California] :  |b Apress,  |c [2019] 
264 2 |a New York, NY :  |b Distributed to the Book trade worldwide by Springer Science+Business Media New York,  |c [2019] 
264 4 |c Ã2019 
300 |a 1 online resource (1 volume) :  |b illustrations 
336 |a text  |b txt  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
338 |a online resource  |b cr  |2 rdacarrier 
588 0 |a Online resource; title from cover (Safari, viewed November 7, 2019). 
504 |a Includes bibliographical references. 
520 |a Your practical guide to moving from novice to master in machine learning with Python 3 in six steps, this book covers fundamental to advanced topics gradually helping beginners become worthy practitioners. --  |c Edited summary from book. 
505 0 |a Intro; Table of Contents; About the Author; About the Technical Reviewer; Acknowledgments; Introduction; Chapter 1: Step 1: Getting Started in Python 3; The Best Things in Life Are Free; The Rising Star; Choosing Python 2.x or Python 3.x; Windows; OSX; Graphical Installer; Command Line Installer; Linux; From Official Website; Running Python; Key Concepts; Python Identifiers; Keywords; My First Python Program; Code Blocks; Indentations; Suites; Basic Object Types; When to Use List, Tuple, Set, or Dictionary; Comments in Python; Multiline Statements; Multiple Statements on a Single Line 
505 8 |a Basic OperatorsArithmetic Operators; Comparison or Relational Operators; Assignment Operators; Bitwise Operators; Logical Operators; Membership Operators; Identity Operators; Control Structures; Selections; Iterations; Lists; Tuples; Sets; Changing Sets in Python; Removing Items from Sets; Set Operations; Set Unions; Set Intersections; Set Difference; Set Symmetric Difference; Basic Operations; Dictionary; User-Defined Functions; Defining a Function; The Scope of Variables; Default Argument; Variable Length Arguments; Modules; File Input/Output; Opening a File; Exception Handling; Summary 
505 8 |a Chapter 2: Step 2: Introduction to Machine LearningHistory and Evolution; Artificial Intelligence Evolution; Different Forms; Statistics; Frequentist; Bayesian; Regression; Data Mining; Data Analytics; Descriptive Analytics; Diagnostic Analytics; Predictive Analytics; Prescriptive Analytics; Data Science; Statistics vs. Data Mining vs. Data Analytics vs. Data Science; Machine Learning Categories; Supervised Learning; Unsupervised Learning; Reinforcement Learning; Frameworks for Building ML Systems; Knowledge Discovery in Databases; Selection; Preprocessing; Transformation; Data Mining 
505 8 |a Interpretation / EvaluationCross-Industry Standard Process for Data Mining; Phase 1: Business Understanding; Phase 2: Data Understanding; Phase 3: Data Preparation; Phase 4: Modeling; Phase 5: Evaluation; Phase 6: Deployment; SEMMA (Sample, Explore, Modify, Model, Assess); Sample; Explore; Modify; Model; Assess; Machine Learning Python Packages; Data Analysis Packages; NumPy; Array; Creating NumPy Array; Data Types; Array Indexing; Field Access; Basic Slicing; Advanced Indexing; Array Math; Broadcasting; Pandas; Data Structures; Series; DataFrame; Reading and Writing Data 
505 8 |a Basic Statistics SummaryViewing Data; Basic Operations; Merge/Join; Join; Grouping; Pivot Tables; Matplotlib; Using Global Functions; Customizing Labels; Object-Oriented; Line Plots Using ax.plot(); Multiple Lines on the Same Axis; Multiple Lines on Different Axis; Control the Line Style and Marker Style; Line Style Reference; Marker Reference; Colormaps Reference; Bar Plots Using ax.bar(); Horizontal Bar Charts Using ax.barh(); Side by Side Bar Chart; Stacked Bar Example Code; Pie Chart Using ax.pie(); Example Code for Grid Creation; Plotting Defaults; Machine Learning Core Libraries 
590 |a O'Reilly  |b O'Reilly Online Learning: Academic/Public Library Edition 
650 0 |a Python (Computer program language) 
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650 0 |a Artificial intelligence. 
650 2 |a Artificial Intelligence 
650 6 |a Python (Langage de programmation) 
650 6 |a Apprentissage automatique. 
650 6 |a Intelligence artificielle. 
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650 7 |a Machine learning.  |2 fast  |0 (OCoLC)fst01004795 
650 7 |a Python (Computer program language)  |2 fast  |0 (OCoLC)fst01084736 
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994 |a 92  |b IZTAP 

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