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Puppet Types and Providers: Extending Puppet with Ruby
by Dan Bode Nan LiuPuppet’s true power exists in the simple resource model it uses to manage the state of complex operating systems. This concise guide shows you how to extend that model and implement custom functionality on top of Puppet by working with the type and provider APIs.Two experts from Puppet Labs explain the concepts behind these APIs, and provide instructions and examples to help you write your own fully functional types and providers. You’ll also delve into Puppet’s source code to get a better understanding of how types and providers are implemented internally. If you’re familiar with basic Puppet concepts, you’re ready to get started.Learn the fundamental concepts behind resources, and become familiar with the structure of Puppet’s Resource ModelDiscover how the type API is used to create new resource types that Puppet can manageUnderstand how providers interact with the system to achieve the desired state of a declared resourceExplore advanced features to get a more complete understanding of how Puppet worksSimplify the troubleshooting process when developing types and providers
Puppetry, Puppet Animation and the Digital Age
by Rolf GiesenRolf Giesen’s Puppetry, Puppet Animation and the Digital Age explores the unique world of puppetry animation and its application in the digital age. With the advent of digital animation, many individuals see puppetry and 2D animation as being regulated to a niche market. Giesen’s text argues against this viewpoint, by demonstrating the pure aesthetic value they have, as well as examples of some of the greatest cinematic uses of puppets. Such samples include, The Adventures of Prince Achmed, Ladislas Starevich, O’Brien, Harryhausen and Danforth, Trnka and Švankmajer, Aardman and Laika Studios, ParaNorman, and the Boxtrolls. Even live-action blockbusters, such as the Star Wars saga utilize puppetry for costume applications as noted within the text. The use of puppets not only helps create a wonderous world and memorable characters, but is also one of the purest extensions of an artist. Key Features Includes interviews with past and present practitioners of model animation as well as computer animation Reviews of classic and recent entries in both fields Comparison of what is better in stop motion versus computer animation A detailed history of animation and stop motion films
Purchasing and Financial Management of Information Technology
by Frank BannisterPurchasing and Financial Management of Information Technology aims to significantly reduce the amount of money wasted on IT by providing readers with a comprehensive guide to all aspects of planning, managing and controlling IT purchasing and finance. Starting from a recognition that IT purchasing and the financial management often needs to be treated differently from other types of expenditure, the author draws on over 25 years of experience in the field to provide readers with useful mixture of good procedures and common sense rules that have been tried, tested and found to work. Many of these are illustrated by case histories, each with a moral or a lesson.Purchasing and Financial Management of Information Technology provides useful guidelines and advice on whole range of topics including:* IT acquisitions policy* Dealing with suppliers* Budgeting and cost control* IT cost and risk management* Specification, selection and evaluation of systems* IT value for money
Purely Functional Data Structures
by Chris OkasakiMost books on data structures assume an imperative language such as C or C++. However, data structures for these languages do not always translate well to functional languages such as Standard ML, Haskell, or Scheme. This book describes data structures from the point of view of functional languages, with examples, and presents design techniques that allow programmers to develop their own functional data structures. The author includes both classical data structures, such as red-black trees and binomial queues, and a host of new data structures developed exclusively for functional languages. All source code is given in Standard ML and Haskell, and most of the programs are easily adaptable to other functional languages. This handy reference for professional programmers working with functional languages can also be used as a tutorial or for self-study.
Purple Team Strategies: Enhancing global security posture through uniting red and blue teams with adversary emulation
by David Routin Simon Thoores Samuel RossierLeverage cyber threat intelligence and the MITRE framework to enhance your prevention mechanisms, detection capabilities, and learn top adversarial simulation and emulation techniquesKey FeaturesApply real-world strategies to strengthen the capabilities of your organization's security systemLearn to not only defend your system but also think from an attacker's perspectiveEnsure the ultimate effectiveness of an organization's red and blue teams with practical tipsBook DescriptionWith small to large companies focusing on hardening their security systems, the term "purple team" has gained a lot of traction over the last couple of years. Purple teams represent a group of individuals responsible for securing an organization's environment using both red team and blue team testing and integration – if you're ready to join or advance their ranks, then this book is for you.Purple Team Strategies will get you up and running with the exact strategies and techniques used by purple teamers to implement and then maintain a robust environment. You'll start with planning and prioritizing adversary emulation, and explore concepts around building a purple team infrastructure as well as simulating and defending against the most trendy ATT&CK tactics. You'll also dive into performing assessments and continuous testing with breach and attack simulations.Once you've covered the fundamentals, you'll also learn tips and tricks to improve the overall maturity of your purple teaming capabilities along with measuring success with KPIs and reporting.With the help of real-world use cases and examples, by the end of this book, you'll be able to integrate the best of both sides: red team tactics and blue team security measures.What you will learnLearn and implement the generic purple teaming processUse cloud environments for assessment and automationIntegrate cyber threat intelligence as a processConfigure traps inside the network to detect attackersImprove red and blue team collaboration with existing and new toolsPerform assessments of your existing security controlsWho this book is forIf you're a cybersecurity analyst, SOC engineer, security leader or strategist, or simply interested in learning about cyber attack and defense strategies, then this book is for you. Purple team members and chief information security officers (CISOs) looking at securing their organizations from adversaries will also benefit from this book. You'll need some basic knowledge of Windows and Linux operating systems along with a fair understanding of networking concepts before you can jump in, while ethical hacking and penetration testing know-how will help you get the most out of this book.
Pursuit of the Universal
by Arnold Beckmann Laurent Bienvenu Nataša JonoskaThis book constitutes the refereed proceedings of the 12th Conference on Computability in Europe, CiE 2016, held in Paris, France, in June/July 2016. The 18 revised full papers and 19 invited papers and invited extended abstracts were carefully reviewed and selected from 40 submissions. The conference CiE 2016 has six special sessions - two sessions, cryptography and information theory and symbolic dynamics, are organized for the first time in the conference series. In addition to this new developments in areas frequently covered in the CiE conference series were addressed in the following sessions: computable and constructive analysis; computation in biological systems; history and philosophy of computing; weak arithmetic.
Pusheen the Cat's Guide to Everything (I Am Pusheen)
by Claire BeltonPusheen the Cat is back with a brand-new collection of adorable comics, expert advice, and silly antics featuring Pusheen and all her friends! <p><p> Whether you’re hoping to learn how to tell if your cat is a Vampurr or looking to study a comprehensive guide to being lazy—Pusheen has got you covered in this super cute guide to everything! This delightful collection of comics and illustrations features some of the most popular and purr-fectly adorable Pusheen comics you know and love, plus a healthy serving of never-before-seen material. Pusheen the Cat has charmed millions of fans worldwide with her humor, bounces, and tail wiggles. Join in on the fun with this super cute collection perfect for cat lovers and comics fans alike!
Pushing Pixels: Chris Georgenes’ Secret Weapons for the Modern Flash Animator
by Chris GeorgenesYou've got the cheats, tutorials, and how-tos. What else do you need? Go above and beyond those stop-gaps and step-by-steps with Pushing Pixels, the real-world guide to developing dynamic and fun content from conception to deployment. Whether you are animating for a short, a fun cartoon, or a mobile game, renowned Flash expert Chris Georgenes will show you his approach with various types of animation projects, from start to finish. Providing in-depth knowledge of the little-known secrets used by the pros to produce creative, professional animations, this is the go-to source for anyone looking to create great animation.
Putting Balloons on a Wall Is Not a Book: Inspirational Advice (and Non-Advice) for Life from @blcksmth
by Michael James SchneiderFrom viral balloon-word artist and Instagram sensation Michael James Schneider (@blcksmth) comes a one-of-a-kind debut gift book with never-before-seen original artwork!Featuring many of @blcksmth&’s most iconic balloon, flower, and light installations—plus exclusive new content—this book has a little something for everyone. Filled with funny, inspiring, and heartwarming messages on topics like self-love, self-growth, self-doubt, and advice for your future self, this is the perfect gift for any occasion or reader.
Putting Ourselves Back in the Equation: Why Physicists Are Studying Human Consciousness and AI to Unravel the Mysteries of the Universe
by George MusserDistant galaxies, dark matter, black holes – elusive, incomprehensible and inhospitable – these are the building blocks of modern physics. But where do we fit in this picture? For centuries, we have separated mind from matter. While physicists have pursued a theory of &‘everything&’ with single-minded purpose, the matter of the mind, of human consciousness, has been conveniently sidestepped and ignored – consigned to priests, philosophers and poets. With the ambition of Stephen Hawking, Carlo Rovelli and Brian Cox, Putting Ourselves Back in the Equation sets out a bold new vision for theoretical physics, unrestricted by sleek equations and neat formulations. Combining cutting-edge neuroscience with the latest in quantum mechanics, acclaimed writer Musser offers a new interpretation of human consciousness. From bizarre cognitive phenomena, like lucid dreaming and self-taught synaesthesia, to the latest technological developments in AI, Musser asks: what can physics teach us about what it means to be human?
Putting People On The Map: Protecting Confidentiality With Linked Social-spatial Data
by National Research Council of the National AcademiesPrecise, accurate spatial information linked to social and behavioral data is revolutionizing social science by opening new questions for investigation and improving understanding of human behavior in its environmental context. At the same time, precise spatial data make it more likely that individuals can be identified, breaching the promise of confidentiality made when the data were collected. Because norms of science and government agencies favor open access to all scientific data, the tension between the benefits of open access and the risks associated with potential breach of confidentiality pose significant challenges to researchers, research sponsors, scientific institutions, and data archivists. Putting People on the Map finds that several technical approaches for making data available while limiting risk have potential, but none is adequate on its own or in combination. This book offers recommendations for education, training, research, and practice to researchers, professional societies, federal agencies, institutional review boards, and data stewards.
Putting Social Media and Networking Data in Practice for Education, Planning, Prediction and Recommendation (Lecture Notes in Social Networks)
by Jalal Kawash Reda Alhajj Mehmet Kaya Şuayip BirinciThis book focusses on recommendation, behavior, and anomaly, among of social media analysis. First, recommendation is vital for a variety of applications to narrow down the search space and to better guide people towards educated and personalized alternatives. In this context, the book covers supporting students, food venue, friend and paper recommendation to demonstrate the power of social media data analysis. Secondly, this book treats behavior analysis and understanding as important for a variety of applications, including inspiring behavior from discussion platforms, determining user choices, detecting following patterns, crowd behavior modeling for emergency evacuation, tracking community structure, etc. Third, fraud and anomaly detection have been well tackled based on social media analysis. This has is illustrated in this book by identifying anomalous nodes in a network, chasing undetected fraud processes, discovering hidden knowledge, detecting clickbait, etc. With this wide coverage, the book forms a good source for practitioners and researchers, including instructors and students.
Putting the Local in Global Education: Models for Transformative Learning Through Domestic Off-Campus Programs
by Neal W. SobaniaThe position taken in this volume is that domestic off-campus study can be just as powerful a transformative learning experience as study overseas, and that domestic programs can equally expand students’ horizons, their knowledge of global issues and processes, their familiarity and experience with cultural diversity, their intercultural skills, and sense of citizenship.This book presents both the rationale for and examples of “study away”, an inclusive concept that embraces study abroad while advocating for a wide variety of domestic study programs, including community-based education programs that employ academic service-learning and internships.With the growing diversification—regionally, demographically, culturally, and socio-economically—of developed economies such as the US, the local is potentially a “doorstep to the planet” and presents opportunities for global learning. Moreover, study away programs can address many of the problematic issues associated with study abroad, such as access, finance, participation, health and safety, and faculty support. Between lower costs, the potential to increase the participation of student cohorts typically under-represented in study abroad, the lowering of language barriers, and the engagement of faculty whose disciplines focus on domestic issues, study at home can greatly expand the reach of global learning.The book is organized in five sections, the first providing a framework and the rationale for domestic study way programs; addressing administrative support for domestic vs. study abroad programs; exploring program goals, organization, structure, assessment and continuous improvement; and considering the distinct pedagogies of experiential and transformative education.The second section focuses on Semester Long Faculty Led Programs, featuring examples of programs located in a wide variety of locations – from investigations into history, immigration, culture, and the environment through localities in the West and the Lowcountry to exploring globalization in L.A and New York. Section three highlights five Short Term Faculty Led Programs. While each includes an intensive immersive study away experience, two illustrate how a 7 – 10 day study away experience can be effectively embedded into a regular course taught on campus. The fourth section, on Consortium Programs, describes programs that are either sponsored by a college that makes its program available to consortium members and non-members, or is offered by an independent non-for-profit to which institutions send their students. The final section on Community Engagement and Domestic Study Away addresses the place of community-based education in global learning and provides examples of academic programs that employ service-learning as a tool for collaborative learning, focusing on issues of pedagogy, faculty development and the building long-term reciprocal relationship with community partners to co-create knowledge.The book is intended for study abroad professionals, multicultural educators, student affairs professionals, alternative spring break directors, and higher education administrators concerned about affordably expanding global education opportunities.
The Pyramid of Game Design: Designing, Producing and Launching Service Games
by Nicholas LovellGame design is changing. The emergence of service games on PC, mobile and console has created new expectations amongst consumers and requires new techniques from game makers. <P><P>In The Pyramid of Game Design, Nicholas Lovell identifies and explains the frameworks and techniques you need to deliver fun, profitable games. Using examples of games ranging from modern free-to-play titles to the earliest arcade games, via PC strategy and traditional boxed titles, Lovell shows how game development has evolved, and provides game makers with the tools to evolve with it. <P><P>Lovell shows how service games require all the skills of product game development, and more. He provides a toolset for game makers of all varieties to create fun, profitable games. Filled with practical advice, memorable anecdotes and a wealth of game knowledge, the Pyramid of Game Design is a must-read for all game developers. <P><P>Key Features <li>Harness the Base, Retention and Superfan Layers to create a powerful Core Loop. <li>Design the player Session to keep players playing while being respectful of their time. <li>Accept that there are few fixed rules: just trade-offs with consequences. <li>Adopt Agile and Lean techniques to "learn what you need you learn" quickly. <li>Use analytics, paired with design skills and player feedback, to improve the fun, engagement and profitability of your games. <li>Adapt your marketing techniques to the reality of the service game era. <li>Consider the ethics of game design in a rapidly changing world.
PySide GUI Application Development
by Venkateshwaran LoganathanAn accessible and practical guide to developing GUI's for Python applications.This book is written for Python programmers who want to learn about GUI programming. It is also suitable for those who are new to Python but are familiar with object-oriented programming.
PySide GUI Application Development - Second Edition
by Gopinath Jaganmohan Venkateshwaran LoganathanDevelop more dynamic and robust GUI applications using PySide, an open source cross-platform UI framework About This Book * Designed for beginners to help you get started with GUI application development * Develop your own applications by creating customized widgets and dialogs * Written in a simple and elegant structure so you easily understand how to program various GUI components Who This Book Is For This book is written for Python programmers who want to learn about GUI programming. It is also suitable for those who are new to Python but are familiar with object-oriented programming. What You Will Learn * Program GUI applications in an easy and efficient way * Download and install PySide, a cross-platform GUI development toolkit for Python * Create menus, toolbars, status bars, and child windows * Develop a text editor application on your own * Connect your GUI to a database and manage it * Execute SQL queries by handling databases In Detail Elegantly-built GUI applications are always a massive hit among users. PySide is an open source software project that provides Python bindings for the Qt cross-platform UI framework. Combining the power of Qt and Python, PySide provides easy access to the Qt framework for Python developers and also acts as an excellent rapid application development platform. This book will take you through everything you need to know to develop UI applications. You will learn about installing and building PySide in various major operating systems as well as the basics of GUI programming. The book will then move on to discuss event management, signals and slots, and the widgets and dialogs available with PySide. Database interaction and manipulation is also covered. By the end of this book, you will be able to program GUI applications efficiently and master how to develop your own applications and how to run them across platforms. Style and approach This is an accessible and practical guide to developing GUIs for Python applications.
PySpark Cookbook: Over 60 recipes for implementing big data processing and analytics using Apache Spark and Python
by Denny Lee Tomasz DrabasCombine the power of Apache Spark and Python to build effective big data applicationsKey FeaturesPerform effective data processing, machine learning, and analytics using PySparkOvercome challenges in developing and deploying Spark solutions using PythonExplore recipes for efficiently combining Python and Apache Spark to process dataBook DescriptionApache Spark is an open source framework for efficient cluster computing with a strong interface for data parallelism and fault tolerance. The PySpark Cookbook presents effective and time-saving recipes for leveraging the power of Python and putting it to use in the Spark ecosystem.You’ll start by learning the Apache Spark architecture and how to set up a Python environment for Spark. You’ll then get familiar with the modules available in PySpark and start using them effortlessly. In addition to this, you’ll discover how to abstract data with RDDs and DataFrames, and understand the streaming capabilities of PySpark. You’ll then move on to using ML and MLlib in order to solve any problems related to the machine learning capabilities of PySpark and use GraphFrames to solve graph-processing problems. Finally, you will explore how to deploy your applications to the cloud using the spark-submit command.By the end of this book, you will be able to use the Python API for Apache Spark to solve any problems associated with building data-intensive applications.What you will learnConfigure a local instance of PySpark in a virtual environment Install and configure Jupyter in local and multi-node environmentsCreate DataFrames from JSON and a dictionary using pyspark.sqlExplore regression and clustering models available in the ML moduleUse DataFrames to transform data used for modelingConnect to PubNub and perform aggregations on streamsWho this book is forThe PySpark Cookbook is for you if you are a Python developer looking for hands-on recipes for using the Apache Spark 2.x ecosystem in the best possible way. A thorough understanding of Python (and some familiarity with Spark) will help you get the best out of the book.
pytest Quick Start Guide: Write better Python code with simple and maintainable tests
by Bruno OliveiraLearn the pytest way to write simple tests which can also be used to write complex testsKey FeaturesBecome proficient with pytest from day one by solving real-world testing problemsUse pytest to write tests more efficientlyScale from simple to complex and functional testingBook DescriptionPython's standard unittest module is based on the xUnit family of frameworks, which has its origins in Smalltalk and Java, and tends to be verbose to use and not easily extensible.The pytest framework on the other hand is very simple to get started, but powerful enough to cover complex testing integration scenarios, being considered by many the true Pythonic approach to testing in Python.In this book, you will learn how to get started right away and get the most out of pytest in your daily workflow, exploring powerful mechanisms and plugins to facilitate many common testing tasks. You will also see how to use pytest in existing unittest-based test suites and will learn some tricks to make the jump to a pytest-style test suite quickly and easily.What you will learnWrite and run simple and complex testsOrganize tests in fles and directoriesFind out how to be more productive on the command lineMarkers and how to skip, xfail and parametrize testsExplore fxtures and techniques to use them effectively, such as tmpdir, pytestconfg, and monkeypatchConvert unittest suites to pytest using little-known techniquesUse third-party pluginsWho this book is forThis book is for Python programmers that want to learn more about testing. This book is also for QA testers, and those who already benefit from programming with tests daily but want to improve their existing testing tools.
Pythagorean Fuzzy Sets: Theory and Applications
by Harish GargThis book presents a collection of recent research on topics related to Pythagorean fuzzy set, dealing with dynamic and complex decision-making problems. It discusses a wide range of theoretical and practical information to the latest research on Pythagorean fuzzy sets, allowing readers to gain an extensive understanding of both fundamentals and applications. It aims at solving various decision-making problems such as medical diagnosis, pattern recognition, construction problems, technology selection, and more, under the Pythagorean fuzzy environment, making it of much value to students, researchers, and professionals associated with the field.
Python: Penetration Testing for Developers
by Christopher Duffy Mohit Cameron Buchanan Terry Ip Andrew Mabbitt Benjamin May Dave MoundUnleash the power of Python scripting to execute effective and efficient penetration tests About This Book Sharpen your pentesting skills with Python Develop your fluency with Python to write sharper scripts for rigorous security testing Get stuck into some of the most powerful tools in the security world Who This Book Is For If you are a Python programmer or a security researcher who has basic knowledge of Python programming and wants to learn about penetration testing with the help of Python, this course is ideal for you. Even if you are new to the field of ethical hacking, this course can help you find the vulnerabilities in your system so that you are ready to tackle any kind of attack or intrusion. What You Will Learn Familiarize yourself with the generation of Metasploit resource files and use the Metasploit Remote Procedure Call to automate exploit generation and execution Exploit the Remote File Inclusion to gain administrative access to systems with Python and other scripting languages Crack an organization's Internet perimeter and chain exploits to gain deeper access to an organization's resources Explore wireless traffic with the help of various programs and perform wireless attacks with Python programs Gather passive information from a website using automated scripts and perform XSS, SQL injection, and parameter tampering attacks Develop complicated header-based attacks through Python In Detail Cybercriminals are always one step ahead, when it comes to tools and techniques. This means you need to use the same tools and adopt the same mindset to properly secure your software. This course shows you how to do just that, demonstrating how effective Python can be for powerful pentesting that keeps your software safe. Comprising of three key modules, follow each one to push your Python and security skills to the next level. In the first module, we'll show you how to get to grips with the fundamentals. This means you'll quickly find out how to tackle some of the common challenges facing pentesters using custom Python tools designed specifically for your needs. You'll also learn what tools to use and when, giving you complete confidence when deploying your pentester tools to combat any potential threat. In the next module you'll begin hacking into the application layer. Covering everything from parameter tampering, DDoS, XXS and SQL injection, it will build on the knowledge and skills you learned in the first module to make you an even more fluent security expert. Finally in the third module, you'll find more than 60 Python pentesting recipes. We think this will soon become your trusted resource for any pentesting situation. This Learning Path combines some of the best that Packt has to offer in one complete, curated package. It includes content from the following Packt products: Learning Penetration Testing with Python by Christopher Duffy Python Penetration Testing Essentials by Mohit Python Web Penetration Testing Cookbook by Cameron Buchanan,Terry Ip, Andrew Mabbitt, Benjamin May and Dave Mound Style and approach This course provides a quick access to powerful, modern tools, and customizable scripts to kick-start the creation of your own Python web penetration testing toolbox.
Python: Journey from Novice to Expert
by Rick Van Hattem Fabrizio Romano Dusty PhillipsLearn core concepts of Python and unleash its power to script highest quality Python programs About This Book * Develop a strong set of programming skills with Pyhton that you will be able to express in any situation, on every platform, thanks to Python's portability * Stop writing scripts and start architecting programs by applying object-oriented programming techniques in Python * Learn the trickier aspects of Python and put it in a structured context for deeper understanding of the language Who This Book Is For This course is meant for programmers who wants to learn Python programming from a basic to an expert level. The course is mostly self-contained and introduces Python programming to a new reader and can help him become an expert in this trade. What You Will Learn * Get Python up and running on Windows, Mac, and Linux in no time * Grasp the fundamental concepts of coding, along with the basics of data structures and control flow * Understand when to use the functional or the object-oriented programming approach * Extend class functionality using inheritance * Exploit object-oriented programming in key Python technologies, such as Kivy and Django * Understand how and when to use the functional programming paradigm * Use the multiprocessing library, not just locally but also across multiple machines In Detail Python is a dynamic and powerful programming language, having its application in a wide range of domains. It has an easy-to-use, simple syntax, and a powerful library, which includes hundreds of modules to provide routines for a wide range of applications, thus making it a popular language among programing enthusiasts.This course will take you on a journey from basic programming practices to high-end tools and techniques giving you an edge over your peers. It follows an interesting learning path, divided into three modules. As you complete each one, you'll have gained key skills and get ready for the material in the next module.The first module will begin with exploring all the essentials of Python programming in an easy-to-understand way. This will lay a good foundation for those who are interested in digging deeper. It has a practical and example-oriented approach through which both the introductory and the advanced topics are explained. Starting with the fundamentals of programming and Python, it ends by exploring topics, like GUIs, web apps, and data science.In the second module you will learn about object oriented programming techniques in Python. Starting with a detailed analysis of object-oriented technique and design, you will use the Python programming language to clearly grasp key concepts from the object-oriented paradigm. This module fully explains classes, data encapsulation, inheritance, polymorphism, abstraction, and exceptions with an emphasis on when you can use each principle to develop well-designed software.With a good foundation of Python you will move onto the third module which is a comprehensive tutorial covering advanced features of the Python language. Start by creating a project-specific environment using venv. This will introduce you to various Pythonic syntax and common pitfalls before moving onto functional features and advanced concepts, thereby gaining an expert level knowledge in programming and teaching how to script highest quality Python programs. Style and approach This course follows a theory-cum-practical approach having all the ingredients that will help you jump into the field of Python programming as a novice and grow-up as an expert. The aim is to create a smooth learning path that will teach you how to get started with Python and carry out expert-level programming techniques at the end of course.
Python: Deeper Insights into Machine Learning
by John Hearty David Julian Sebastian RaschkaLeverage benefits of machine learning techniques using Python About This Book * Improve and optimise machine learning systems using effective strategies. * Develop a strategy to deal with a large amount of data. * Use of Python code for implementing a range of machine learning algorithms and techniques. Who This Book Is For This title is for data scientist and researchers who are already into the field of data science and want to see machine learning in action and explore its real-world application. Prior knowledge of Python programming and mathematics is must with basic knowledge of machine learning concepts. What You Will Learn * Learn to write clean and elegant Python code that will optimize the strength of your algorithms * Uncover hidden patterns and structures in data with clustering * Improve accuracy and consistency of results using powerful feature engineering techniques * Gain practical and theoretical understanding of cutting-edge deep learning algorithms * Solve unique tasks by building models * Get grips on the machine learning design process In Detail Machine learning and predictive analytics are becoming one of the key strategies for unlocking growth in a challenging contemporary marketplace. It is one of the fastest growing trends in modern computing, and everyone wants to get into the field of machine learning. In order to obtain sufficient recognition in this field, one must be able to understand and design a machine learning system that serves the needs of a project. The idea is to prepare a learning path that will help you to tackle the real-world complexities of modern machine learning with innovative and cutting-edge techniques. Also, it will give you a solid foundation in the machine learning design process, and enable you to build customized machine learning models to solve unique problems. The course begins with getting your Python fundamentals nailed down. It focuses on answering the right questions that cove a wide range of powerful Python libraries, including scikit-learn Theano and Keras.After getting familiar with Python core concepts, it's time to dive into the field of data science. You will further gain a solid foundation on the machine learning design and also learn to customize models for solving problems. At a later stage, you will get a grip on more advanced techniques and acquire a broad set of powerful skills in the area of feature selection and feature engineering. Style and approach This course includes all the resources that will help you jump into the data science field with Python. The aim is to walk through the elements of Python covering powerful machine learning libraries. This course will explain important machine learning models in a step-by-step manner. Each topic is well explained with real-world applications with detailed guidance.Through this comprehensive guide, you will be able to explore machine learning techniques.
Python: End-to-end Data Analysis
by Ivan Idris Luiz Felipe Martins Magnus Vilhelm Persson Martin Czygan Phuong VothihongLeverage the power of Python to clean, scrape, analyze, and visualize your data About This Book • Clean, format, and explore your data using the popular Python libraries and get valuable insights from it • Analyze big data sets; create attractive visualizations; manipulate and process various data types using NumPy, SciPy, and matplotlib; and more • Packed with easy-to-follow examples to develop advanced computational skills for the analysis of complex data Who This Book Is For This course is for developers, analysts, and data scientists who want to learn data analysis from scratch. This course will provide you with a solid foundation from which to analyze data with varying complexity. A working knowledge of Python (and a strong interest in playing with your data) is recommended. What You Will Learn • Understand the importance of data analysis and master its processing steps • Get comfortable using Python and its associated data analysis libraries such as Pandas, NumPy, and SciPy • Clean and transform your data and apply advanced statistical analysis to create attractive visualizations • Analyze images and time series data • Mine text and analyze social networks • Perform web scraping and work with different databases, Hadoop, and Spark • Use statistical models to discover patterns in data • Detect similarities and differences in data with clustering • Work with Jupyter Notebook to produce publication-ready figures to be included in reports In Detail Data analysis is the process of applying logical and analytical reasoning to study each component of data present in the system. Python is a multi-domain, high-level, programming language that offers a range of tools and libraries suitable for all purposes, it has slowly evolved as one of the primary languages for data science. Have you ever imagined becoming an expert at effectively approaching data analysis problems, solving them, and extracting all of the available information from your data? If yes, look no further, this is the course you need! In this course, we will get you started with Python data analysis by introducing the basics of data analysis and supported Python libraries such as matplotlib, NumPy, and pandas. Create visualizations by choosing color maps, different shapes, sizes, and palettes then delve into statistical data analysis using distribution algorithms and correlations. You'll then find your way around different data and numerical problems, get to grips with Spark and HDFS, and set up migration scripts for web mining. You'll be able to quickly and accurately perform hands-on sorting, reduction, and subsequent analysis, and fully appreciate how data analysis methods can support business decision-making. Finally, you will delve into advanced techniques such as performing regression, quantifying cause and effect using Bayesian methods, and discovering how to use Python's tools for supervised machine learning. The course provides you with highly practical content explaining data analysis with Python, from the following Packt books: 1. Getting Started with Python Data Analysis. 2. Python Data Analysis Cookbook. 3. Mastering Python Data Analysis. By the end of this course, you will have all the knowledge you need to analyze your data with varying complexity levels, and turn it into actionable insights. Style and approach Learn Python data analysis using engaging examples and fun exercises, and with a gentle and friendly but comprehensive "learn-by-doing" approach. It offers you a useful way of analyzing the data that's specific to this course, but that can also be applied to any other data. This course is designed to be both a guide and a reference for moving beyond the basics of data analysis.
Python: Gain practical insights by exploiting data in your business to build advanced predictive modeling applications
by Joseph J Ashish KumarKey Features A step-by-step guide to predictive modeling including lots of tips, tricks, and best practices Learn how to use popular predictive modeling algorithms such as Linear Regression, Decision Trees, Logistic Regression, and Clustering Master open source Python tools to build sophisticated predictive models Book Description Social Media and the Internet of Things have resulted in an avalanche of data. Data is powerful but not in its raw form; it needs to be processed and modeled, and Python is one of the most robust tools out there to do so. It has an array of packages for predictive modeling and a suite of IDEs to choose from. Using the Python programming language, analysts can use these sophisticated methods to build scalable analytic applications. This book is your guide to getting started with predictive analytics using Python. You'll balance both statistical and mathematical concepts, and implement them in Python using libraries such as pandas, scikit-learn, and NumPy. Through case studies and code examples using popular open-source Python libraries, this book illustrates the complete development process for analytic applications. Covering a wide range of algorithms for classification, regression, clustering, as well as cutting-edge techniques such as deep learning, this book illustrates explains how these methods work. You will learn to choose the right approach for your problem and how to develop engaging visualizations to bring to life the insights of predictive modeling. Finally, you will learn best practices in predictive modeling, as well as the different applications of predictive modeling in the modern world. The course provides you with highly practical content from the following Packt books: 1. Learning Predictive Analytics with Python 2. Mastering Predictive Analytics with Python What you will learn Understand the statistical and mathematical concepts behind predictive analytics algorithms and implement them using Python libraries Get to know various methods for importing, cleaning, sub-setting, merging, joining, concatenating, exploring, grouping, and plotting data with pandas and NumPy Master the use of Python notebooks for exploratory data analysis and rapid prototyping Get to grips with applying regression, classification, clustering, and deep learning algorithms Discover advanced methods to analyze structured and unstructured data Visualize the performance of models and the insights they produce Ensure the robustness of your analytic applications by mastering the best practices of predictive analysis
Python: Real World Machine Learning
by Prateek JoshiLearn to solve challenging data science problems by building powerful machine learning models using Python About This Book Understand which algorithms to use in a given context with the help of this exciting recipe-based guide This practical tutorial tackles real-world computing problems through a rigorous and effective approach Build state-of-the-art models and develop personalized recommendations to perform machine learning at scale Who This Book Is For This Learning Path is for Python programmers who are looking to use machine learning algorithms to create real-world applications. It is ideal for Python professionals who want to work with large and complex datasets and Python developers and analysts or data scientists who are looking to add to their existing skills by accessing some of the most powerful recent trends in data science. Experience with Python, Jupyter Notebooks, and command-line execution together with a good level of mathematical knowledge to understand the concepts is expected. Machine learning basic knowledge is also expected. What You Will Learn Use predictive modeling and apply it to real-world problems Understand how to perform market segmentation using unsupervised learning Apply your new-found skills to solve real problems, through clearly-explained code for every technique and test Compete with top data scientists by gaining a practical and theoretical understanding of cutting-edge deep learning algorithms Increase predictive accuracy with deep learning and scalable data-handling techniques Work with modern state-of-the-art large-scale machine learning techniques Learn to use Python code to implement a range of machine learning algorithms and techniques In Detail Machine learning is increasingly spreading in the modern data-driven world. It is used extensively across many fields such as search engines, robotics, self-driving cars, and more. Machine learning is transforming the way we understand and interact with the world around us. In the first module, Python Machine Learning Cookbook, you will learn how to perform various machine learning tasks using a wide variety of machine learning algorithms to solve real-world problems and use Python to implement these algorithms. The second module, Advanced Machine Learning with Python, is designed to take you on a guided tour of the most relevant and powerful machine learning techniques and you'll acquire a broad set of powerful skills in the area of feature selection and feature engineering. The third module in this learning path, Large Scale Machine Learning with Python, dives into scalable machine learning and the three forms of scalability. It covers the most effective machine learning techniques on a map reduce framework in Hadoop and Spark in Python. This Learning Path will teach you Python machine learning for the real world. The machine learning techniques covered in this Learning Path are at the forefront of commercial practice. This Learning Path combines some of the best that Packt has to offer in one complete, curated package. It includes content from the following Packt products: Python Machine Learning Cookbook by Prateek Joshi Advanced Machine Learning with Python by John Hearty Large Scale Machine Learning with Python by Bastiaan Sjardin, Alberto Boschetti, Luca Massaron Style and approach This course is a smooth learning path that will teach you how to get started with Python machine learning for the real world, and develop solutions to real-world problems. Through this comprehensive course, you'll learn to create the most effective machine learning techniques from scratch and more!