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Practical Web Scraping for Data Science

Practical Web Scraping for Data Science: Best Practices and Examples with Python by Seppe vanden Broucke, Bart Baesens
This book provides a complete and modern guide to web scraping, using Python as the programming language, without glossing over important details or best practices. Written with a data science audience in mind, the book explores both scraping and the larger context of web technologies in which it operates, to ensure full understanding. The authors recommend web scraping as a powerful tool for any data scientist’s arsenal, as many data science projects start by obtaining an appropriate data set.
Starting with a brief overview on scraping and real-life use cases, the authors explore the core concepts of HTTP, HTML, and CSS to provide a solid foundation. Along with a quick Python primer, they cover Selenium for JavaScript-heavy sites, and web crawling in detail. The book finishes with a recap of best practices and a collection of examples that bring together everything you’ve learned and illustrate various data science use cases.
**What You’ll Learn**
* Leverage well-established best practices and commonly-used Python packages
* Handle today’s web, including JavaScript, cookies, and common web scraping mitigation techniques
* Understand the managerial and legal concerns regarding web scraping
**Who This Book is For**
A data science oriented audience that is probably already familiar with Python or another programming language or analytical toolkit (R, SAS, SPSS, etc). Students or instructors in university courses may also benefit. Readers unfamiliar with Python will appreciate a quick Python primer in chapter 1 to catch up with the basics and provide pointers to other guides as well.

Practical Tableau

Practical Tableau: 100 Tips, Tutorials, and Strategies from a Tableau Zen Master by Ryan Sleeper
Whether you have some experience with Tableau software or are just getting started, this manual goes beyond the basics to help you build compelling, interactive data visualization applications. Author Ryan Sleeper, one of the world’s most qualified Tableau consultants, complements his web posts and instructional videos with this guide to give you a firm understanding of how to use Tableau to find valuable insights in data.
Over five sections, Sleeper—recognized as a Tableau Zen Master, Tableau Public Visualization of the Year author, and Tableau Iron Viz Champion—provides visualization tips, tutorials, and strategies to help you avoid the pitfalls and take your Tableau knowledge to the next level.
*Practical Tableau* sections include:
* **Fundamentals:** get started with Tableau from the beginning
* **Chart types:** use step-by-step tutorials to build a variety of charts in Tableau
* **Tips and tricks:** learn innovative uses of parameters, color theory, how to make your Tableau workbooks run efficiently, and more
* **Framework:** explore the INSIGHT framework, a proprietary process for building Tableau dashboards
* **Storytelling:** learn tangible tactics for storytelling with data, including specific and actionable tips you can implement immediately

Practical Python AI Projects

Practical Python AI Projects: Mathematical Models of Optimization Problems with Google OR-Tools by Serge Kruk
Discover the art and science of solving artificial intelligence problems with Python using optimization modeling. This book covers the practical creation and analysis of mathematical algebraic models such as linear continuous models, non-obviously linear continuous models,
and pure linear integer models. Rather than focus on theory, *Practical Python AI Projects*, the product of the author’s decades of industry teaching and consulting, stresses the model creation aspect; contrasting alternate approaches and practical variations.
Each model is explained thoroughly and written to be executed. The source code from all examples in the book is available, written in Python using Google OR-Tools. It also includes a random problem generator, useful for industry application or study.
**What You Will Learn**
* Build basic Python-based artificial intelligence (AI) applications
* Work with mathematical optimization methods and the Google OR-Tools (Optimization Tools) suite
* Create several types of projects using Python and Google OR-Tools
**Who This Book Is For**
Developers and students who already have prior experience in Python coding. Some prior mathematical experience or comfort level may be helpful as well.

Practical Network Automation

Key Features Get started with network automation (and different automation tasks) with relevant use cases Apply software design principles such as Continuous Integration and DevOps to your network toolkit Guides you through some best practices in automation Book Description
Network automation is the use of IT controls to supervise and carry out every-day network management functions. It plays a key role in network virtualization technologies and network functions.
The book starts by providing an introduction to network automation, SDN, and its applications, which include integrating DevOps tools to automate the network efficiently. It then guides you through different network automation tasks and covers various data digging and reporting methodologies such as IPv6 migration, DC relocations, and interface parsing, all the while retaining security and improving data center robustness. The book then moves on to the use of Python and the management of SSH keys for machine-to-machine (M2M) communication, all followed by practical use cases. The book also covers the importance of Ansible for network automation including best practices in automation, ways to test automated networks using different tools, and other important techniques.
By the end of the book, you will be well acquainted with the various aspects of network automation.
What you will learn Get the detailed analysis of Network automation Trigger automations through available data factors Improve data center robustness and security through specific access and data digging Get an Access to APIs from Excel for dynamic reporting Set up a communication with SSH-based devices using netmiko Make full use of practical use cases and best practices to get accustomed with the various aspects of network automation About the Author
**Abhishek Ratan** has around 15 years of technical experience in networking, automation, and various ITIL processes, and has worked in various roles in different organizations. As a network engineer, security engineer, automation engineer, TAC engineer, tech lead, and content writer, he has gained a wealth of experience during the 15 years of his career. Abhishek also has a deep interest in strategy game playing, and if he is not working on technical stuff, he is busy spending time on his strategy games.
He is currently working as a Sr Automation Engineer at ServiceNow, learning, and expanding his automation skills in the ServiceNow platform. His earlier experience includes working for companies such as Microsoft, Symantec, and Navisite,which has given him exposure to various environments.
Table of Contents Fundamental Concepts Python for Network Engineers Accessing and Mining Data from Network Web Framework for Automation triggers Ansible for Network Automation Continuous Integration for Network Engineers SDN Concepts in Network Automation

Practical Machine Learning Cookbook

Key Features Implement a wide range of algorithms and techniques for tackling complex data Improve predictions and recommendations to have better levels of accuracy Optimize performance of your machine-learning systems Book Description
Machine learning has become the new black. The challenge in today’s world is the explosion of data from existing legacy data and incoming new structured and unstructured data. The complexity of discovering, understanding, performing analysis, and predicting outcomes on the data using machine learning algorithms is a challenge. This cookbook will help solve everyday challenges you face as a data scientist. The application of various data science techniques and on multiple data sets based on real-world challenges you face will help you appreciate a variety of techniques used in various situations.
The first half of the book provides recipes on fairly complex machine-learning systems, where you’ll learn to explore new areas of applications of machine learning and improve its efficiency. That includes recipes on classifications, neural networks, unsupervised and supervised learning, deep learning, reinforcement learning, and more.
The second half of the book focuses on three different machine learning case studies, all based on real-world data, and offers solutions and solves specific machine-learning issues in each one.
What You Will Learn Get equipped with a deeper understanding of how to apply machine-learning techniques Implement each of the advanced machine-learning techniques Solve real-life problems that are encountered in order to make your applications produce improved results Gain hands-on experience in problem solving for your machine-learning systems Understand the methods of collecting data, preparing data for usage, training the model, evaluating the model’s performance, and improving the model’s performance About the Author
**Atul Tripathi** has spent more than 11 years in the fields of machine learning and quantitative finance. He has a total of 14 years of experience in software development and research. He has worked on advanced machine learning techniques, such as neural networks and Markov models. While working on these techniques, he has solved problems related to image processing, telecommunications, human speech recognition, and natural language processing. He has also developed tools for text mining using neural networks. In the field of quantitative finance, he has developed models for Value at Risk, Extreme Value Theorem, Option Pricing, and Energy Derivatives using Monte Carlo simulation techniques.
Table of Contents Introduction to Machine Learning Classification Clustering Model Selection and Regularization Nonlinearity Supervised Learning Unsupervised Learning Reinforcement Learning Structured Prediction Neural Networks Deep Learning Case Study – Exploring World Bank Data Case Study – Pricing Reinsurance Contracts Case Study – Forecast of Electricity Consumption

Practical Machine Learning

**Tackle the real-world complexities of modern machine learning with innovative, cutting-edge, techniques**About This Book
* Fully-coded working examples using a wide range of machine learning libraries and tools, including Python, R, Julia, and Spark
* Comprehensive practical solutions taking you into the future of machine learning
* Go a step further and integrate your machine learning projects with Hadoop
Who This Book Is For
This book has been created for data scientists who want to see machine learning in action and explore its real-world application. With guidance on everything from the fundamentals of machine learning and predictive analytics to the latest innovations set to lead the big data revolution into the future, this is an unmissable resource for anyone dedicated to tackling current big data challenges. Knowledge of programming (Python and R) and mathematics is advisable if you want to get started immediately.What You Will Learn
* Implement a wide range of algorithms and techniques for tackling complex data
* Get to grips with some of the most powerful languages in data science, including R, Python, and Julia
* Harness the capabilities of Spark and Hadoop to manage and process data successfully
* Apply the appropriate machine learning technique to address real-world problems
* Get acquainted with Deep learning and find out how neural networks are being used at the cutting-edge of machine learning
* Explore the future of machine learning and dive deeper into polyglot persistence, semantic data, and more
In Detail
Finding meaning in increasingly larger and more complex datasets is a growing demand of the modern world. Machine learning and predictive analytics have become the most important approaches to uncover data gold mines. Machine learning uses complex algorithms to make improved predictions of outcomes based on historical patterns and the behaviour of data sets. Machine learning can deliver dynamic insights into trends, patterns, and relationships within data, immensely valuable to business growth and development.
This book explores an extensive range of machine learning techniques uncovering hidden tricks and tips for several types of data using practical and real-world examples. While machine learning can be highly theoretical, this book offers a refreshing hands-on approach without losing sight of the underlying principles. Inside, a full exploration of the various algorithms gives you high-quality guidance so you can begin to see just how effective machine learning is at tackling contemporary challenges of big data.
This is the only book you need to implement a whole suite of open source tools, frameworks, and languages in machine learning. We will cover the leading data science languages, Python and R, and the underrated but powerful Julia, as well as a range of other big data platforms including Spark, Hadoop, and Mahout. Practical Machine Learning is an essential resource for the modern data scientists who want to get to grips with its real-world application.
With this book, you will not only learn the fundamentals of machine learning but dive deep into the complexities of real world data before moving on to using Hadoop and its wider ecosystem of tools to process and manage your structured and unstructured data.
You will explore different machine learning techniques for both supervised and unsupervised learning; from decision trees to Naive Bayes classifiers and linear and clustering methods, you will learn strategies for a truly advanced approach to the statistical analysis of data. The book also explores the cutting-edge advancements in machine learning, with worked examples and guidance on deep learning and reinforcement learning, providing you with practical demonstrations and samples that help take the theory–and mystery–out of even the most advanced machine learning methodologies.Style and approach
A practical data science tutorial designed to give you an insight into the practical application of machine learning, this book takes you through complex concepts and tasks in an accessible way. Featuring information on a wide range of data science techniques, Practical Machine Learning is a comprehensive data science resource.
(source: Bol.com)

Practical Docker with Python

Learn the key differences between containers and virtual machines. Adopting a project based approach, this book introduces you to a simple Python application to be developed and containerized with Docker.

After an introduction to Containers and Docker you’ll be guided through Docker installation and configuration. You’ll also learn basic functions and commands used in Docker by running a simple container using Docker commands.

The book then moves on to developing a Python based Messaging Bot using required libraries and virtual environment where you’ll add Docker Volumes to your project, ensuring your container data is safe.

You’ll create a database container and link your project to it and finally, bring up the Bot-associated database all at once with Docker Compose.

What You’ll Learn


Build, run, and distribute Docker containers

Develop a Python App and containerize it

Use Dockerfile to run the Python App

Define and run multi-container applications with Docker Compose

Work with persisting data generated by and used by Docker containers

Who This Book Is For

Intermediate developers/DevOps practitioners who are looking to improve their build and release workflow by containerizing applications

(source: Bol.com)

Practical Django 2 and Channels 2

Learn how to rapidly build your own ecommerce site by applying Django’s battle-tested components. This book demonstrates Django’s features and conventions to help you develop modern web applications quickly. You’ll adopt a ”learn by doing” approach and gain a deeper understanding Django by working through a project in which the real-time component will be critical.

The book starts with the basics and explains the difference between a Django project and a Django app, the most important settings, how to change them, and the fundamentals of packaging. You’ll then be introduced to all the standard tools of Django, along with a sample project. The book then moves on to Channels, a recent addition to the Django ecosystem. It extends the framework with support for real-time operations such as Websockets and other asynchronous features.

*Practical Django 2 and Channels 2 *provides the practical concepts needed to create complex, database-driven websites as easily as possible.

What You’ll Learn


Build and deploy a simple company site with Django

Develop more complex, data-heavy sites using the Django ORM

Integrate Django with Channels

Unit-test your solutions

Who This Book Is For

Python developers and web developers wanting to learn Django 2 and Channels 2

(source: Bol.com)

Practical Bot Development

Explore the concept of bots and discover the motivation behind working with these new apps with messaging platforms. This book is an accessible resource teaching the basic concepts behind bot design and implementation. Each chapter builds on previous topics and, where appropriate, real working code is shown that implements the concepts. By just picking up a code editor, you can start creating smart, engaging, and useful bot experiences today.

Practical Bot Development will teach you how to create your own bots on platforms like Facebook Messenger and Slack, incorporate extension APIs, and apply AI and ML algorithms in the cloud. By the end of this book, you’ll be equipped with the information to reach thousands of new users with the bots you create!

The book is a great resource for those looking to harness the benefits of building their own bots and leveraging the platform feasibility of them.

What You’ll Learn


Understand the general architecture of a bot

Distinguish between a great bot experience versus a bad bot experience.

Explore the ideas behind natural language processing and apply them to bot development

Implement real Messenger, Slack, and custom channel bots using Node.js and the Microsoft Bot Builder framework

Deploy bots to Facebook Messenger and Slack

Who This Book Is For

Engineers, hobbyists, and the design oriented community looking looking for an introduction to the technologies and concepts involved in building bots. The experience level could be from beginner to expert, although some familiarity with Node.js and APIs will be assumed.

(source: Bol.com)

Practical Big Data Analytics

Get command of your organizational Big Data using the power of data science and analytics
Key Features

* A perfect companion to boost your Big Data storing, processing, analyzing skills to help you take informed business decisions

* Work with the best tools such as Apache Hadoop, R, Python, and Spark for NoSQL platforms to perform massive online analyses

* Get expert tips on statistical inference, machine learning, mathematical modeling, and data visualization for Big Data

Book Description

Big Data analytics relates to the strategies used by organizations to collect, organize and analyze large amounts of data to uncover valuable business insights that otherwise cannot be analyzed through traditional systems. Crafting an enterprise-scale cost-efficient Big Data and machine learning solution to uncover insights and value from your organization’s data is a challenge. Today, with hundreds of new Big Data systems, machine learning packages and BI Tools, selecting the right combination of technologies is an even greater challenge. This book will help you do that.

With the help of this guide, you will be able to bridge the gap between the theoretical world of technology with the practical ground reality of building corporate Big Data and data science platforms. You will get hands-on exposure to Hadoop and Spark, build machine learning dashboards using R and R Shiny, create web-based apps using NoSQL databases such as MongoDB and even learn how to write R code for neural networks.

By the end of the book, you will have a very clear and concrete understanding of what Big Data analytics means, how it drives revenues for organizations, and how you can develop your own Big Data analytics solution using different tools and methods articulated in this book.
What you will learn

* – Get a 360-degree view into the world of Big Data, data science and machine learning

* – Broad range of technical and business Big Data analytics topics that caters to the interests of the technical experts as well as corporate IT executives

* – Get hands-on experience with industry-standard Big Data and machine learning tools such as Hadoop, Spark, MongoDB, KDB+ and R

* – Create production-grade machine learning BI Dashboards using R and R Shiny with step-by-step instructions

* – Learn how to combine open-source Big Data, machine learning and BI Tools to create low-cost business analytics applications

* – Understand corporate strategies for successful Big Data and data science projects

* – Go beyond general-purpose analytics to develop cutting-edge Big Data applications using emerging technologies

Who this book is for

The book is intended for existing and aspiring Big Data professionals who wish to become the go-to person in their organization when it comes to Big Data architecture, analytics, and governance. While no prior knowledge of Big Data or related technologies is assumed, it will be helpful to have some programming experience.

(source: Bol.com)

Practical Astrodynamics

This modern textbook guides the reader through the theory and practice of the motion and attitude control of space vehicles. It first presents the fundamental principles of spaceflight mechanics and then addresses more complex concepts and applications of perturbation theory, orbit determination and refinement, space propulsion, orbital maneuvers, interplanetary trajectories, gyroscope dynamics, attitude control, and rocket performance. Many algorithms used in the modern practice of trajectory computation are also provided. The numerical treatment of the equations of motion, the related methods, and the tables needed to use them receive particular emphasis. A large collection of bibliographical references (including books, articles, and items from the gray literature ) is provided at the end of each chapter, and attention is drawn to many internet resources available to the reader. The book will be of particular value to undergraduate and graduate students in aerospace engineering.
(source: Bol.com)

Practical Artificial Intelligence

Practical Artificial Intelligence: Machine Learning, Bots, and Agent Solutions Using C# by Arnaldo Pérez Castaño
Discover how all levels Artificial Intelligence (AI) can be present in the most unimaginable scenarios of ordinary lives. This book explores subjects such as neural networks, agents, multi agent systems, supervised learning, and unsupervised learning. These and other topics will be addressed with real world examples, so you can learn fundamental concepts with AI solutions and apply them to your own projects.
People tend to talk about AI as something mystical and unrelated to their ordinary life. *Practical Artificial Intelligence* provides simple explanations and hands on instructions. Rather than focusing on theory and overly scientific language, this book will enable practitioners of all levels to not only learn about AI but implement its practical uses.
**What You’ll Learn**
* Understand agents and multi agents and how they are incorporated
* How machine learning relates to real world problems and what it means to you
* Apply supervised and unsupervised learning techniques and methods in the real world
* Implement reinforcement learning, game programming, simulation, and neural networks
**Who This Book Is For**
Computer science students, professionals, and hobbyists interested in AI and its applications.

PowerShell for SQL Server Essentials

**Manage and monitor SQL Server administration and application deployment with PowerShell** About This Book Create scripts using PowerShell to manage and monitor server administration and application deployment Automate creation of SQL Database objects through PowerShell with the help of SQL Server module (SQLPS) and SQL Server snapins A fast paced guide, packed with hands-on examples on profiling and configuring SQL Server Who This Book Is For
This book is written for SQL Server administrators and developers who want to leverage PowerShell to work with SQL Server. Some background with scripting will be helpful but not necessary.
What You Will Learn Create scripts using PowerShell to manage and monitor server administration and application deployment Automate the creation of SQL Database objects through PowerShell with the help of the SQL Server module (SQLPS) and SQL Server snap-ins Use PowerShell to work with SQL Server specific providers and cmdlets Identify and manage SQL Server services, instances, settings, and confi gurations Profile your SQL Server instances and export current configurations to a file Monitor SQL Server jobs and alerts Manage logins, database users, and instance security and permissions Invoke T-SQL queries from PowerShell and export results Accomplish tasks from your DBA daily/weekly/monthly/yearly checklists with PowerShell In Detail
PowerShell for SQL Server Essentials helps us to manage and monitor server administration and application deployment. Use PowerShell along with SQL Server to perform common DBA tasks.
Starting with a basic introduction to PowerShell, the initial chapters will provide the SQL Server professional PowerShell fundamentals, covering topics such as PowerShell notations and syntax, cmdlets, pipeline, and getting help. Succeeding chapters build upon these fundamentals, and illustrate how to administer and automate SQL Server. Tasks covered throughout include profiling the SQL Server instance, performing backup and restores, invoking T-SQL scripts using PowerShell, and monitoring jobs, security, and permissions.
Packed with practical examples and numerous ready-to-use snippets, this book gets you to an intermediate level in using PowerShell for SQL Server.


Two hundred thousand feet up, things go horribly wrong. An experimental low-orbit spaceplane breaks up on reentry, falling to earth over a trail hundreds of miles long. And it its wake is the beginning of the most important mission in the history of space.
America needs energy, and Dan Randolph is determined to give it to them. He dreams of an array of geosynchronous powersats, satellites which gather solar energy and beam it to generators on Earth, freeing America from its addiction to fossil fuels and breaking the power of the oil cartels forever. But the wreck of the spaceplane has left his company, Astro Manufacturing, on the edge of bankruptcy.
Worse, Dan discovers that the plane worked perfectly right up until the moment that saboteurs knocked it out of the sky. And whoever brought it down is willing and able to kill again to keep Astro grounded.
Now Dan has to thread a dangerous maze. The visible threats are bad enough: Rival firms want to buy him out and take control of his dreams. His former lover wants to co-opt his unlimited-energy ideal as a campaign plank for the candidate she’s grooming for the presidency. NASA and the FAA want to shut down his maverick firm. And his creditors are breathing down his neck.
Making matters even more dangerous, an international organization of terrorists sees the powersat as a threat to their own oil-based power. And they’ve figured out how to use it as a weapon in their war against the West.
A sweeping mix of space, murder, romance, politics, secrets, and betrayal, *Powersat* will take you to the edge of space and the dawning of a new world.
At the Publisher’s request, this title is being sold without Digital Rights Management Software (DRM) applied.

Power: Why Some People Have It—and Others Don’t

“Pfeffer [blends] academic rigor and practical genius into wonderfully readable text. The leading thinker on the topic of power, Pfeffer here distills his wisdom into an indispensable guide.”—Jim Collins, author of New York Times bestselling author Good to Great and How the Mighty Fall Some people have it, and others don’t—Jeffrey Pfeffer explores why in Power. One of the greatest minds in management theory and author or co-author of thirteen books, including the seminal business school text Managing With Power, Pfeffer shows readers how to succeed and wield power in the real world.

The Power

The Power by Naomi Alderman
**One of the *New York Times*’s Ten Best Books of 2017**
**A *Los Angeles Times *Best Book of 2017**
**One of the *Washington Post*’s Ten Best Books of 2017**
**An *NPR *Best Book of 2017**
**One of *Entertainment Weekly*’s Ten Best Books of 2017**
**A *****Bustle *****B****est Book of 2017**
**A *Paste* Magazine Best Novel of 2017**
**A *San Francisco Chronicle *****B****est Book of 2017**
**Winner of the Baileys Women’s Prize for Fiction
**One of President Obama’s favorite reads of 2017**
****”*The Power *is our era’s *The Handmaid’s Tale*.” —Ron Charles, *Washington Post*****
“Novels based on premises like the one at the core of *The Power* can quickly become little more than thought experiments, but Alderman dodges this trap deftly — her writing is beautiful, and her intelligence seems almost limitless. She also has a pitch-dark sense of humor that she wields perfectly.” —Michael Schaub, NPR
A *New York Times Book Review *Editors’ Choice**
**An Amazon Best Book of 2017**** ****
What would happen if women suddenly possessed a fierce new power?****
In THE POWER, the world is a recognizable place: there’s a rich Nigerian boy who lounges around the family pool; a foster kid whose religious parents hide their true nature; an ambitious American politician; a tough London girl from a tricky family. But then a vital new force takes root and flourishes, causing their lives to converge with devastating effect. Teenage girls now have immense physical power—they can cause agonizing pain and even death. And, with this small twist of nature, the world drastically resets.
From award-winning author Naomi Alderman, THE POWER is speculative fiction at its most ambitious and provocative, at once taking us on a thrilling journey to an alternate reality, and exposing our own world in bold and surprising ways.