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Python for Data Science For Dummies (For Dummies (Computer/Tech))

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Unleash the power of Python for your data analysis projectswith For Dummies!

Python is the preferred programming language for data scientistsand combines the best features of Matlab, Mathematica, and R intolibraries specific to data analysis and visualization. Pythonfor Data Science For Dummies shows you how to take advantage ofPython programming to acquire, organize, process, and analyze largeamounts of information and use basic statistics concepts toidentify trends and patterns. You’ll get familiar with thePython development environment, manipulate data, design compellingvisualizations, and solve scientific computing challenges as youwork your way through this user-friendly guide.

  • Covers the fundamentals of Python data analysis programming andstatistics to help you build a solid foundation in data scienceconcepts like probability, random distributions, hypothesistesting, and regression models
  • Explains objects, functions, modules, and libraries and theirrole in data analysis
  • Walks you through some of the most widely-used libraries,including NumPy, SciPy, BeautifulSoup, Pandas, and MatPlobLib

Whether you’re new to data analysis or just new to Python,Python for Data Science For Dummies is your practical guideto getting a grip on data overload and doing interesting thingswith the oodles of information you uncover.

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Derivatives Analytics with Python: Data Analysis, Models, Simulation, Calibration and Hedging (The Wiley Finance Series)
Derivatives Analytics with Python: Data Analysis, Models, Simulation, Calibration and Hedging (The Wiley Finance Series)

Supercharge options analytics and hedging using the power ofPython

Derivatives Analytics with Python shows you how toimplement market-consistent valuation and hedging approaches usingadvanced financial models, efficient numerical techniques, and thepowerful capabilities of the Python programming language. Thisunique...

Scrum: Novice to Ninja: Methods for Agile, Powerful Development
Scrum: Novice to Ninja: Methods for Agile, Powerful Development

Why should you use Scrum in your web projects? Simply put, it'll enable your team to get more done in less time.

Scrum is the most popular agile project management methodology used in web projects today. While most Scrum books tend to be lengthy textbooks that cover every detail of Scrum for all types of...

Testing Python: Applying Unit Testing, TDD, BDD and Acceptance Testing
Testing Python: Applying Unit Testing, TDD, BDD and Acceptance Testing

Fundamental testing methodologies applied to the popular Pythonlanguage

Testing Python; Applying Unit Testing, TDD, BDD andAcceptance Testing is the most comprehensive book available ontesting for one of the top software programming languages in theworld. Python is a natural choice for new and experienceddevelopers,...


Building Machine Learning Systems with Python - Second Edition
Building Machine Learning Systems with Python - Second Edition

Get more from your data through creating practical machine learning systems with Python

About This Book

  • Build your own Python-based machine learning systems tailored to solve any problem
  • Discover how Python offers a multiple context solution for create machine learning systems
  • ...
Deep Learning Cookbook: Practical Recipes to Get Started Quickly
Deep Learning Cookbook: Practical Recipes to Get Started Quickly

Deep learning doesn’t have to be intimidating. Until recently, this machine-learning method required years of study, but with frameworks such as Keras and Tensorflow, software engineers without a background in machine learning can quickly enter the field. With the recipes in this cookbook, you’ll learn how to solve...

Practical Statistics for Data Scientists: 50 Essential Concepts
Practical Statistics for Data Scientists: 50 Essential Concepts

Statistical methods are a key part of of data science, yet very few data scientists have any formal statistics training. Courses and books on basic statistics rarely cover the topic from a data science perspective. This practical guide explains how to apply various statistical methods to data science, tells you how to avoid their...

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