Produktdetaljer
ISBN
9781119547624
Publisert
2019-04-05
Utgave
2. utgave
Utgiver
Vendor
For Dummies
Vekt
658 gr
Høyde
231 mm
Bredde
185 mm
Dybde
31 mm
Aldersnivå
G, 01
Språk
Product language
Engelsk
Format
Product format
Heftet
Antall sider
496
Biographical note
John Paul Mueller is a tech editor and the author of over 100 books on topics from networking and home security to database management and heads-down programming. Follow John's blog at http://blog.johnmuellerbooks.com/. Luca Massaron is a data scientist who specializes in organizing and interpreting big data and transforming it into smart data. He is a Google Developer Expert (GDE) in machine learning.
The fast and easy way to learn Python programming and statistics Python is a general-purpose programming language created in the late 1980s—and named after Monty Python—that's used by thousands of people to do things from testing microchips at Intel, to powering Instagram, to building video games with the PyGame library. Python For Data Science For Dummies is written for people who are new to data analysis, and discusses the basics of Python data analysis programming and statistics. The book also discusses Google Colab, which makes it possible to write Python code in the cloud. Get started with data science and PythonVisualize informationWrangle dataLearn from data The book provides the statistical background needed to get started in data science programming, including probability, random distributions, hypothesis testing, confidence intervals, and building regression models for prediction.
Les mer
Introduction 1 Part 1: Getting Started with Data Science and Python 7 Chapter 1: Discovering the Match between Data Science and Python 9 Chapter 2: Introducing Python’s Capabilities and Wonders 21 Chapter 3: Setting Up Python for Data Science 39 Chapter 4: Working with Google Colab 59 Part 2: Getting Your Hands Dirty with Data 81 Chapter 5: Understanding the Tools 83 Chapter 6: Working with Real Data 99 Chapter 7: Conditioning Your Data 121 Chapter 8: Shaping Data 149 Chapter 9: Putting What You Know in Action 169 Part 3: Visualizing Information 183 Chapter 10: Getting a Crash Course in MatPlotLib 185 Chapter 11: Visualizing the Data 201 Part 4: Wrangling Data 227 Chapter 12: Stretching Python’s Capabilities 229 Chapter 13: Exploring Data Analysis 251 Chapter 14: Reducing Dimensionality 275 Chapter 15: Clustering 295 Chapter 16: Detecting Outliers in Data 313 Part 5: Learning from Data 327 Chapter 17: Exploring Four Simple and Effective Algorithms 329 Chapter 18: Performing Cross-Validation, Selection, and Optimization 347 Chapter 19: Increasing Complexity with Linear and Nonlinear Tricks 371 Chapter 20: Understanding the Power of the Many 411 Part 6: The Part of Tens 429 Chapter 21: Ten Essential Data Resources 431 Chapter 22: Ten Data Challenges You Should Take 437 Index 447
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Learn Python data analysis programming and statisticsWrite code in the cloud with Google Colab™Wrangle data and visualize information Relax! Data science doesn't have to be scary Curious about data science, but a bit intimidated? Don't be! This book shows you how to use Python to do all sorts of cool things with data science. You'll see how to install the Anaconda tool suite, so working with Python is a breeze. You'll discover Google Colab, which lets you write code in the cloud using your tablet. You'll find out how to perform all kinds of interesting calculations using the latest version of Python. And you'll learn to use the various libraries that enable scientific statistical analysis, plotting and graphing, and much more. Inside... Python set-up for data scienceWorking with Jupyter NotebookConditioning and shaping dataGraphing with MatPlotLibWays to analyze your dataGetting more from PythonUseful data science algorithmsTen essential data resources
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Introduction 1
Part 1: Getting Started With Data Science and Python 7
Chapter 1: Discovering the Match between Data Science and Python 9
Chapter 2: Introducing Python’s Capabilities and Wonders 21
Chapter 3: Setting Up Python for Data Science 39
Part 2: Getting Your Hands Dirty With Data 81
Chapter 5: Understanding the Tools 83
Chapter 6: Working with Real Data 99
Chapter 7: Conditioning Your Data 121
Chapter 8: Shaping Data 149
Chapter 9: Putting What You Know in Action 169
Part 3: Visualizing Information 183
Chapter 10: Getting a Crash Course in MatPlotLib 185
Chapter 11: Visualizing the Data 201
Part 4: Wrangling Data 227
Chapter 12: Stretching Python’s Capabilities 229
Chapter 13: Exploring Data Analysis 251
Chapter 14: Reducing Dimensionality 275
Chapter 15: Clustering 295
Chapter 16: Detecting Outliers in Data 313
Part 5: Learning From Data 327
Chapter 17: Exploring Four Simple and Effective Algorithms 329
Chapter 18: Performing Cross-Validation, Selection, and Optimization 347
Chapter 19: Increasing Complexity with Linear and Nonlinear Tricks 371
Chapter 20: Understanding the Power of the Many 411
Part 6: The Part of Tens 429
Chapter 21: Ten Essential Data Resources 431
Chapter 22: Ten Data Challenges You Should Take 437
Index 447
Les mer
Produktdetaljer
ISBN
9781119547624
Publisert
2019-04-05
Utgave
2. utgave
Utgiver
Vendor
For Dummies
Vekt
658 gr
Høyde
231 mm
Bredde
185 mm
Dybde
31 mm
Aldersnivå
G, 01
Språk
Product language
Engelsk
Format
Product format
Heftet
Antall sider
496
Biographical note
John Paul Mueller is a tech editor and the author of over 100 books on topics from networking and home security to database management and heads-down programming. Follow John's blog at http://blog.johnmuellerbooks.com/. Luca Massaron is a data scientist who specializes in organizing and interpreting big data and transforming it into smart data. He is a Google Developer Expert (GDE) in machine learning.