Daily Dose for 2017.10.08

« Daily Dose for 2017.10.07 | Oct 2017 | 2017 | Daily Dose for 2017.10.09 »

Scientific Computing with Python 3
Magento 2 DIY
Think Like a Data Scientist
The Art of Data Usability
Introducing Data Science
The Python 3 Standard Library by Example, Second Edition

Books/Videos on Sale (or Free) Today

These deals are good for today only, so be sure to take advantage of the pricing before the offers expire.

Free Scientific Computing with Python 3

Scientific Computing with Python 3 Free Packt eBook by Claus Führer, Jan Erik Solem (valid through 10/08 at 19:00 EST). This book covers Python 3, SciPy, Matplotlib, SymPy.

Publisher’s Description

Python can be used for more than just general-purpose programming. It is a free, open source language and environment that has tremendous potential for use within the domain of scientific computing. This book presents Python in tight connection with mathematical applications and demonstrates how to use various concepts in Python for computing purposes, including examples with the latest version of Python 3. Python is an effective tool to use when coupling scientific computing and mathematics and this book will teach you how to use it for linear algebra, arrays, plotting, iterating, functions, polynomials, and much more.

What You Will Learn

  • The principal syntactical elements of Python
  • The most important and basic types in Python
  • The essential building blocks of computational mathematics, linear algebra, and related Python objects
  • Plot in Python using matplotlib to create high quality figures and graphics to draw and visualize your results
  • Define and use functions and learn to treat them as objects
  • How and when to correctly apply object-oriented programming for scientific computing in Python
  • Handle exceptions, which are an important part of writing reliable and usable code
  • Two aspects of testing for scientific programming: Manual and Automatic

About the Authors

Claus Führer is a professor of scientific computations at Lund University, Sweden. He has an extensive teaching record that includes intensive programming courses in numerical analysis and engineering mathematics across various levels in many different countries and teaching environments. Claus also develops numerical software in research collaboration with industry and received Lund University’s Faculty of Engineering Best Teacher Award in 2016.

Jan Erik Solem is a Python enthusiast, former associate professor, and currently the CEO of Mapillary, a street imagery computer vision company. He has previously worked as a face recognition expert, founder and CTO of Polar Rose, and computer vision team leader at Apple. Jan is a World Economic Forum technology pioneer and won the Best Nordic Thesis Award 2005-2006 for his dissertation on image analysis and pattern recognition. He is also the author of “Programming Computer Vision with Python” (O’Reilly 2012).

$9.99 Magento 2 DIY

Magento 2 DIY $9.99 Apress eBook by Viktor Khliupko. This book covers Magento 2, eCommerce.

Publisher’s Description

  • Fully up-to-date for the very latest 2.x version of Magento
  • Includes continuously updated tools, tips, extensions and services in an online repo available to readers
  • Each tip, technique and tool has been used in the development of live successful businesses and startups

Learn how Magento 2, the newest version of the eCommerce platform, works. Aimed at entrepreneurs, marketers, and other experts interested in eCommerce, this book is accessible for anyone who wants to learn how to use Magento with no previous experience.

Magento continues to be a top choice for eCommerce solutions in small and large businesses. Magento 2 DIY shows you how to set up and configure Magento for your own project. You will learn how to use extensions, templates and enterprise features. Various techniques are taught in an easy-to-understand way with real-world examples. Get started with Magento 2 using this book.

What You Will Learn

  • Set up, configure, use templates, designs and extensions
  • Use the SEO and SMO features of Magento 2
  • Optimize security and performance
  • Integrate with PIM, ERP, CRM, and other enterprise systems

Who This Book Is For

Anyone who wants to learn the basics of all aspects of Magento 2. You do not need any previous experience with Magento.

About the Author

Viktor Khliupko is an eCommerce expert, consultant, and developer. He is also a traveler and metal music fan. He has built successful Magento-based eCommerce businesses and startups worldwide. He is the founder of the FireBear Studio, and co-founder of Alamio.

50% off Think Like a Data Scientist Tackle the data science process step-by-step

Think Like a Data Scientist 50% off Manning’s eBook by Brian Godsey. This book covers Data Science.

Publisher’s Description

Think Like a Data Scientist presents a step-by-step approach to data science, combining analytic, programming, and business perspectives into easy-to-digest techniques and thought processes for solving real world data-centric problems.

About the technology

Data collected from customers, scientific measurements, IoT sensors, and so on is valuable only if you understand it. Data scientists revel in the interesting and rewarding challenge of observing, exploring, analyzing, and interpreting this data. Getting started with data science means more than mastering analytic tools and techniques, however; the real magic happens when you begin to think like a data scientist. This book will get you there.

About the book

Think Like a Data Scientist teaches you a step-by-step approach to solving real-world data-centric problems. By breaking down carefully crafted examples, you’ll learn to combine analytic, programming, and business perspectives into a repeatable process for extracting real knowledge from data. As you read, you’ll discover (or remember) valuable statistical techniques and explore powerful data science software. More importantly, you’ll put this knowledge together using a structured process for data science. When you’ve finished, you’ll have a strong foundation for a lifetime of data science learning and practice.

What’s inside

  • The data science process, step-by-step
  • How to anticipate problems
  • Dealing with uncertainty
  • Best practices in software and scientific thinking

About the reader

Readers need beginner programming skills and knowledge of basic statistics.

About the author

Brian Godsey has worked in software, academia, finance, and defense and has launched several data-centric start-ups.

50% off The Art of Data Usability

The Art of Data Usability 50% off Manning’s eBook by Tryggvi Bjorgvinsson. This book covers Big Data, Python, Data Usability.

Publisher’s Description

You’re planning a large event in Stockholm. It’s important for you to know who is coming and when, but you don’t need complete data about them-family history, employment status and property ownership is probably irrelevant. You need different things out of data for different situations. Crop forecasts are measured in days or weeks, while train schedules must be accurate within minutes or seconds. Knowing how data will be consumed and planning data projects accordingly is the essential art of data usability. Measures of data quality, such as precision, timeliness, format, and so on all depend on how those data are to be used.

About the book

The Art of Data Usability teaches you how to set up data projects in a way that maximizes their effectiveness for their intended users. In this interesting, practical guide, you’ll master techniques for understanding the type and role of the data you have and preparing those data to maximize their value. With the help of dozens of real world examples that the author has faced before, you’ll learn from them to piece together the perfect workflow for sorting through data for your clients, principles for establishing data projects, and techniques to apply to your datasets. Throw in a bit of coding, and you’ll be more than prepared to get the data you have in the right shape, exactly when you need it.

What’s inside

  • The attributes of quality data
  • Identifying user needs and requirements
  • Using Python for data quality monitoring
  • The correct way to disseminate your data
  • Best practices and methods to improve data usability

About the reader

Written for readers comfortable with data management and common data formats such as CSV and JSON. Some examples require novice-level programming skills.

About the author

Tryggvi Björgvinsson is the head of IT and dissemination at Statistics Iceland. He holds a Ph.D. in software engineering.

50% off Introducing Data Science Big data, machine learning, and more, using Python tools

Introducing Data Science 50% off Manning’s eBook by Davy Cielen, Arno D. B. Meysman, Mohamed Ali. This book covers Big Data, Data Science, Python, Machine Learning.

Publisher’s Description

Introducing Data Science teaches you how to accomplish the fundamental tasks that occupy data scientists. Using the Python language and common Python libraries, you’ll experience firsthand the challenges of dealing with data at scale and gain a solid foundation in data science.

About the technology

Many companies need developers with data science skills to work on projects ranging from social media marketing to machine learning. Discovering what you need to learn to begin a career as a data scientist can seem bewildering. This book is designed to help you get started.

About the book

Introducing Data Science explains vital data science concepts and teaches you how to accomplish the fundamental tasks that occupy data scientists. You?ll explore data visualization, graph databases, the use of NoSQL, and the data science process. You?ll use the Python language and common Python libraries as you experience firsthand the challenges of dealing with data at scale. Discover how Python allows you to gain insights from data sets so big that they need to be stored on multiple machines, or from data moving so quickly that no single machine can handle it. This book gives you hands-on experience with the most popular Python data science libraries, Scikit-learn and StatsModels. After reading this book, you?ll have the solid foundation you need to start a career in data science.

What’s inside

  • Handling large data
  • Introduction to machine learning
  • Using Python to work with data
  • Writing data science algorithms

About the reader

This book assumes you’re comfortable reading code in Python or a similar language, such as C, Ruby, or JavaScript. No prior experience with data science is required.

About the authors

Davy Cielen, Arno D. B. Meysman, and Mohamed Ali are the founders and managing partners of Optimately and Maiton, where they focus on developing data science projects and solutions in various sectors.

The Python 3 Standard Library by Example, Second Edition

The Python 3 Standard Library by Example, Second Edition InformIT eBook by Doug Hellmann. This book covers Python 3.

Publisher’s Description

The Python 3 Standard Library contains hundreds of modules for interacting with the operating system, interpreter, and Internet–all extensively tested and ready to jump-start application development. Now, Python expert Doug Hellmann introduces every major area of the Python 3.x library through concise source code and output examples. Hellmann’s examples fully demonstrate each feature and are designed for easy learning and reuse.

You’ll find practical code for working with text, data structures, algorithms, dates/times, math, the file system, persistence, data exchange, compression, archiving, crypto, processes/threads, networking, Internet capabilities, email, developer and language tools, the runtime, packages, and more. Each section fully covers one module, with links to additional resources, making this book an ideal tutorial and reference.

The Python 3 Standard Library by Example introduces Python 3.x’s new libraries, significant functionality changes, and new layout and naming conventions. Hellmann also provides expert porting guidance for moving code from 2.x Python standard library modules to their Python 3.x equivalents.

  • Manipulate text with string, textwrap, re (regular expressions), and difflib
  • Use data structures: enum, collections, array, heapq, queue, struct, copy, and more
  • Implement algorithms elegantly and concisely with functools, itertools, and contextlib
  • Handle dates/times and advanced mathematical tasks
  • Archive and data compression
  • Understand data exchange and persistence, including json, dbm, and sqlite
  • Sign and verify messages cryptographically
  • Manage concurrent operations with processes and threads
  • Test, debug, compile, profile, language, import, and package tools
  • Control interaction at runtime with interpreters or the environment

About the Author

Doug Hellmann is currently a senior developer with Racemi, Inc., and communications director of the Python Software Foundation. He has been programming in Python since version 1.4 and has worked on a variety of Unix and non-Unix platforms for projects in fields such as mapping, medical news publishing, banking, and data center automation. After a year as a regular columnist for Python Magazine, he served as editor-in-chief from 2008-2009. Since 2007, Doug has published the popular “Python Module of the Week” series on his blog. He lives in Athens, Georgia.

« Daily Dose for 2017.10.07 | Oct 2017 | 2017 | Daily Dose for 2017.10.09 »


© 2017. All rights reserved.

Powered by Hydejack v6.6.1