Practical Data Analysis. Pandas, MongoDB, Apache Spark, and more - Second Edition

Hector Cuesta, Dr. Sampath Kumar

Beyond buzzwords like Big Data or Data Science, there are a great opportunities to innovate in many businesses using data analysis to get data-driven products. Data analysis involves asking many questions about data in order to discover insights and generate value for a product or a service.This book explains the basic data algorithms without the theoretical jargon, and you’ll get hands-on turning data into insights using machine learning techniques. We will perform data-driven innovation processing for several types of data such as text, Images, social network graphs, documents, and time series, showing you how to implement large data processing with MongoDB and Apache Spark.

Practical Data Analysis Using Jupyter Notebook. Learn how to speak the language of data by extracting useful and actionable insights using Python

Marc Wintjen, Andrew Vlahutin

Data literacy is the ability to read, analyze, work with, and argue using data. Data analysis is the process of cleaning and modeling your data to discover useful information. This book combines these two concepts by sharing proven techniques and hands-on examples so that you can learn how to communicate effectively using data.After introducing you to the basics of data analysis using Jupyter Notebook and Python, the book will take you through the fundamentals of data. Packed with practical examples, this guide will teach you how to clean, wrangle, analyze, and visualize data to gain useful insights, and you'll discover how to answer questions using data with easy-to-follow steps.Later chapters teach you about storytelling with data using charts, such as histograms and scatter plots. As you advance, you'll understand how to work with unstructured data using natural language processing (NLP) techniques to perform sentiment analysis. All the knowledge you gain will help you discover key patterns and trends in data using real-world examples. In addition to this, you will learn how to handle data of varying complexity to perform efficient data analysis using modern Python libraries.By the end of this book, you'll have gained the practical skills you need to analyze data with confidence.

Practical Data Quality. Learn practical, real-world strategies to transform the quality of data in your organization

Robert Hawker, Nicola Askham

Poor data quality can lead to increased costs, hinder revenue growth, compromise decision-making, and introduce risk into organizations. This leads to employees, customers, and suppliers finding every interaction with the organization frustrating.Practical Data Quality provides a comprehensive view of managing data quality within your organization, covering everything from business cases through to embedding improvements that you make to the organization permanently. Each chapter explains a key element of data quality management, from linking strategy and data together to profiling and designing business rules which reveal bad data. The book outlines a suite of tried-and-tested reports that highlight bad data and allow you to develop a plan to make corrections. Throughout the book, you’ll work with real-world examples and utilize re-usable templates to accelerate your initiatives.By the end of this book, you’ll have gained a clear understanding of every stage of a data quality initiative and be able to drive tangible results for your organization at pace.

Practical Data Science Cookbook. Data pre-processing, analysis and visualization using R and Python - Second Edition

Prabhanjan Narayanachar Tattar, Bhushan Purushottam Joshi, Sean Patrick Murphy, ABHIJIT DASGUPTA, ...

As increasing amounts of data are generated each year, the need to analyze and create value out of it is more important than ever. Companies that know what to do with their data and how to do it well will have a competitive advantage over companies that don’t. Because of this, there will be an increasing demand for people that possess both the analytical and technical abilities to extract valuable insights from data and create valuable solutions that put those insights to use. Starting with the basics, this book covers how to set up your numerical programming environment, introduces you to the data science pipeline, and guides you through several data projects in a step-by-step format. By sequentially working through the steps in each chapter, you will quickly familiarize yourself with the process and learn how to apply it to a variety of situations with examples using the two most popular programming languages for data analysis—R and Python.

Practical Data Science with Python. Learn tools and techniques from hands-on examples to extract insights from data

Nathan George

Practical Data Science with Python teaches you core data science concepts, with real-world and realistic examples, and strengthens your grip on the basic as well as advanced principles of data preparation and storage, statistics, probability theory, machine learning, and Python programming, helping you build a solid foundation to gain proficiency in data science.The book starts with an overview of basic Python skills and then introduces foundational data science techniques, followed by a thorough explanation of the Python code needed to execute the techniques. You'll understand the code by working through the examples. The code has been broken down into small chunks (a few lines or a function at a time) to enable thorough discussion.As you progress, you will learn how to perform data analysis while exploring the functionalities of key data science Python packages, including pandas, SciPy, and scikit-learn. Finally, the book covers ethics and privacy concerns in data science and suggests resources for improving data science skills, as well as ways to stay up to date on new data science developments.By the end of the book, you should be able to comfortably use Python for basic data science projects and should have the skills to execute the data science process on any data source.

Practical Data Wrangling. Expert techniques for transforming your raw data into a valuable source for analytics

Allan Visochek

Around 80% of time in data analysis is spent on cleaning and preparing data for analysis. This is, however, an important task, and is a prerequisite to the rest of the data analysis workflow, including visualization, analysis and reporting. Python and R are considered a popular choice of tool for data analysis, and have packages that can be best used to manipulate different kinds of data, as per your requirements. This book will show you the different data wrangling techniques, and how you can leverage the power of Python and R packages to implement them.You’ll start by understanding the data wrangling process and get a solid foundation to work with different types of data. You’ll work with different data structures and acquire and parse data from various locations. You’ll also see how to reshape the layout of data and manipulate, summarize, and join data sets. Finally, we conclude with a quick primer on accessing and processing data from databases, conducting data exploration, and storing and retrieving data quickly using databases.The book includes practical examples on each of these points using simple and real-world data sets to give you an easier understanding. By the end of the book, you’ll have a thorough understanding of all the data wrangling concepts and how to implement them in the best possible way.

Practical Deep Learning at Scale with MLflow. Bridge the gap between offline experimentation and online production

Yong Liu, Dr. Matei Zaharia

The book starts with an overview of the deep learning (DL) life cycle and the emerging Machine Learning Ops (MLOps) field, providing a clear picture of the four pillars of deep learning: data, model, code, and explainability and the role of MLflow in these areas.From there onward, it guides you step by step in understanding the concept of MLflow experiments and usage patterns, using MLflow as a unified framework to track DL data, code and pipelines, models, parameters, and metrics at scale. You’ll also tackle running DL pipelines in a distributed execution environment with reproducibility and provenance tracking, and tuning DL models through hyperparameter optimization (HPO) with Ray Tune, Optuna, and HyperBand. As you progress, you’ll learn how to build a multi-step DL inference pipeline with preprocessing and postprocessing steps, deploy a DL inference pipeline for production using Ray Serve and AWS SageMaker, and finally create a DL explanation as a service (EaaS) using the popular Shapley Additive Explanations (SHAP) toolbox.By the end of this book, you’ll have built the foundation and gained the hands-on experience you need to develop a DL pipeline solution from initial offline experimentation to final deployment and production, all within a reproducible and open source framework.

Practical Design Patterns for Java Developers. Hone your software design skills by implementing popular design patterns in Java

Miroslav Wengner, Bruno Souza

Design patterns are proven solutions to standard problems in software design and development, allowing you to create reusable, flexible, and maintainable code. This book enables you to upskill by understanding popular patterns to evolve into a proficient software developer.You’ll start by exploring the Java platform to understand and implement design patterns. Then, using various examples, you’ll create different types of vehicles or their parts to enable clarity in design pattern thinking, along with developing new vehicle instances using dedicated design patterns to make the process consistent. As you progress, you’ll find out how to extend vehicle functionalities and keep the code base structure and behavior clean and shiny. Concurrency plays an important role in application design, and you'll learn how to employ a such design patterns with the visualization of thread interaction. The concluding chapters will help you identify and understand anti-pattern utilization in the early stages of development to address refactoring smoothly. The book covers the use of Java 17+ features such as pattern matching, switch cases, and instances of enhancements to enable productivity.By the end of this book, you’ll have gained practical knowledge of design patterns in Java and be able to apply them to address common design problems.

Practical DevOps. Harness the power of DevOps to boost your skill set and make your IT organization perform better

joakim verona

DevOps is a practical field that focuses on delivering business value as efficiently as possible. DevOps encompasses all the flows from code through testing environments to production environments. It stresses the cooperation between different roles, and how they can work together more closely, as the roots of the word imply—Development and Operations.After a quick refresher to DevOps and continuous delivery, we quickly move on to looking at how DevOps affects architecture. You'll create a sample enterprise Java application that you’ll continue to work with through the remaining chapters. Following this, we explore various code storage and build server options. You will then learn how to perform code testing with a few tools and deploy your test successfully. Next, you will learn how to monitor code for any anomalies and make sure it’s running properly. Finally, you will discover how to handle logs and keep track of the issues that affect processes

Practical DevOps. Implement DevOps in your organization by effectively building, deploying, testing, and monitoring code - Second Edition

joakim verona

DevOps is a practical field that focuses on delivering business value as efficiently as possible. DevOps encompasses all code workflows from testing environments to production environments. It stresses cooperation between different roles, and how they can work together more closely, as the roots of the word imply—Development and Operations.Practical DevOps begins with a quick refresher on DevOps and continuous delivery and quickly moves on to show you how DevOps affects software architectures. You'll create a sample enterprise Java application that you’'ll continue to work with through the remaining chapters. Following this, you will explore various code storage and build server options. You will then learn how to test your code with a few tools and deploy your test successfully. In addition to this, you will also see how to monitor code for any anomalies and make sure that it runs as expected. Finally, you will discover how to handle logs and keep track of the issues that affect different processes.By the end of the book, you will be familiar with all the tools needed to deploy, integrate, and deliver efficiently with DevOps.

Practical Digital Forensics. Get started with the art and science of digital forensics with this practical, hands-on guide!

Richard Boddington

Digital Forensics is a methodology which includes using various tools, techniques, and programming language. This book will get you started with digital forensics and then follow on to preparing investigation plan and preparing toolkit for investigation.In this book you will explore new and promising forensic processes and tools based on ‘disruptive technology’ that offer experienced and budding practitioners the means to regain control of their caseloads. During the course of the book, you will get to know about the technical side of digital forensics and various tools that are needed to perform digital forensics. This book will begin with giving a quick insight into the nature of digital evidence, where it is located and how it can be recovered and forensically examined to assist investigators. This book will take you through a series of chapters that look at the nature and circumstances of digital forensic examinations and explains the processes of evidence recovery and preservation from a range of digital devices, including mobile phones, and other media. This book has a range of case studies and simulations will allow you to apply the knowledge of the theory gained to real-life situations. By the end of this book you will have gained a sound insight into digital forensics and its key components.

Practical Discrete Mathematics. Discover math principles that fuel algorithms for computer science and machine learning with Python

Ryan T. White, Archana Tikayat Ray

Discrete mathematics deals with studying countable, distinct elements, and its principles are widely used in building algorithms for computer science and data science. The knowledge of discrete math concepts will help you understand the algorithms, binary, and general mathematics that sit at the core of data-driven tasks.Practical Discrete Mathematics is a comprehensive introduction for those who are new to the mathematics of countable objects. This book will help you get up to speed with using discrete math principles to take your computer science skills to a more advanced level.As you learn the language of discrete mathematics, you’ll also cover methods crucial to studying and describing computer science and machine learning objects and algorithms. The chapters that follow will guide you through how memory and CPUs work. In addition to this, you’ll understand how to analyze data for useful patterns, before finally exploring how to apply math concepts in network routing, web searching, and data science.By the end of this book, you’ll have a deeper understanding of discrete math and its applications in computer science, and be ready to work on real-world algorithm development and machine learning.

Practical Finite Element Simulations with SOLIDWORKS 2022. An illustrated guide to performing static analysis with SOLIDWORKS Simulation

Khameel B. Mustapha

SOLIDWORKS is a dominant computer-aided design (CAD) software for the 3D modeling, designing, and analysis of components. This book helps you get to grips with SOLIDWORKS Simulation, which is a remarkable and integral part of SOLIDWORKS predominantly deployed for advanced product performance assessment and virtual prototyping.With this book, you'll take a hands-on approach to learning SOLIDWORKS Simulation with the help of step-by-step guidelines on various aspects of the simulation workflow. You'll begin by learning about the requirements for effective simulation of parts and components, along with the idealization of physical components and their representation with finite element models. As you progress through the book, you'll find exercises at the end of each chapter, and you'll be able to download the geometry models used in all the chapters from GitHub. Finally, you’ll discover how to set up finite element simulations for the static analysis of components under various types of loads, and with different types of materials, from simple isotropic to composite, and different boundary conditions.By the end of this SOLIDWORKS 2022 book, you'll be able to conduct basic and advanced static analyses with SOLIDWORKS Simulation and have practical knowledge of how to best use the family of elements in the SOLIDWORKS Simulation library.

Practical Game AI Programming. Unleash the power of Artificial Intelligence to your game

Micael DaGraça

The book starts with the basics examples of AI for different game genres and directly jumps into defining the probabilities and possibilities of the AI character to determine character movement. Next, you’ll learn how AI characters should behave within the environment created.Moving on, you’ll explore how to work with animations. You’ll also plan and create pruning strategies, and create Theta algorithms to find short and realistic looking game paths. Next, you’ll learn how the AI should behave when there is a lot of characters in the same scene.You'll explore which methods and algorithms, such as possibility maps, Forward Chaining Plan, Rete Algorithm, Pruning Strategies, Wall Distances, and Map Preprocess Implementation should be used on different occasions. You’ll discover how to overcome some limitations, and how to deliver a better experience to the player. By the end of the book, you think differently about AI.

Practical Game Design. A modern and comprehensive guide to video game design - Second Edition

Adam Kramarzewski, Ennio De Nucci

If you’re in search of a cutting-edge actionable guide to game design, your quest ends here! Immerse yourself in the fundamentals of game design with expert guidance from veterans with decades of game design experience across a variety of genres and platforms.The second edition of this book remains dedicated to its original goal of helping you master the fundamentals of game design in a practical manner with the addition of some of the latest trends in game design and a whole lot of fresh, real-world examples from games of the current generation. This update brings a new chapter on games as a service, explaining the evolving role of the game designer and diving deeper into the design of games that are meant to be played forever. From conceptualizing a game idea, you’ll gradually move on to devising a design plan and adapting solutions from existing games, exploring the craft of producing original game mechanics, and eliminating anticipated design risks through testing. You’ll then be introduced to level design, interactive storytelling, user experience and accessibility.By the end of this game design book, you’ll have learned how to wrap up a game ahead of its release date, work through the challenges of designing free-to-play games and games as a service, and significantly improve their quality through iteration, playtesting, and polishing.

Practical Game Design. Learn the art of game design through applicable skills and cutting-edge insights

Adam Kramarzewski, Ennio De Nucci

If you are looking for an up-to-date and highly applicable guide to game design, then you have come to the right place! Immerse yourself in the fundamentals of game design with this book, written by two highly experienced industry professionals to share their profound insights as well as give valuable advice on creating games across genres and development platforms.This book covers the basics of game design one piece at a time. Starting with learning how to conceptualize a game idea and present it to the development team, you will gradually move on to devising a design plan for the whole project and adapting solutions from other games. You will also discover how to produce original game mechanics without relying on existing reference material, and test and eliminate anticipated design risks. You will then design elements that compose the playtime of a game, followed by making game mechanics, content, and interface accessible to all players. You will also find out how to simultaneously ensure that the gameplay mechanics and content are working as intended.As the book reaches its final chapters, you will learn to wrap up a game ahead of its release date, work through the different challenges of designing free-to-play games, and understand how to significantly improve their quality through iteration, polishing and playtesting.

Practical Generative AI with ChatGPT. Unleash your prompt engineering potential with OpenAI technologies for productivity and creativity - Second Edition

Valentina Alto

Practical Generative AI with ChatGPT is your hands-on guide to unlocking the full potential of ChatGPT. From building AI assistants and mastering prompt engineering to analyzing documents and images and even generating code, this book equips you with the skills to integrate generative AI into your workflow.Written by a technical architect specializing in AI and intelligent applications, this book provides the tools and knowledge you need to streamline tasks, enhance productivity, and create intelligent solutions. You’ll learn how to craft precise prompts, leverage ChatGPT for daily efficiency, and develop custom AI assistants tailored to your needs.The chapters show you how to use ChatGPT’s multimodal capabilities to generate images with DALL·E and even transform images into code. This ChatGPT book goes beyond basic interactions by showing you how to design custom GPTs and integrate OpenAI’s APIs into your applications. You’ll explore how businesses use OpenAI models, from building AI applications, including semantic search, to creating an AI roadmap. Each chapter is packed with practical examples, ensuring you can apply the techniques right away.By the end of this book, you’ll be well equipped to leverage OpenAI's technology for competitive advantage.

Practical GIS. Learn novice to advanced topics such as QGIS, Spatial data analysis, and more

Gábor Farkas

The most commonly used GIS tools automate tasks that were historically done manually—compiling new maps by overlaying one on top of the other or physically cutting maps into pieces representing specific study areas, changing their projection, and getting meaningful results from the various layers by applying mathematical functions and operations. This book is an easy-to-follow guide to use the most matured open source GIS tools for these tasks.We’ll start by setting up the environment for the tools we use in the book. Then you will learn how to work with QGIS in order to generate useful spatial data. You will get to know the basics of queries, data management, and geoprocessing.After that, you will start to practice your knowledge on real-world examples. We will solve various types of geospatial analyses with various methods. We will start with basic GIS problems by imitating the work of an enthusiastic real estate agent, and continue with more advanced, but typical tasks by solving a decision problem. Finally, you will find out how to publish your data (and results) on the web. We will publish our data with QGIS Server and GeoServer, and create a basic web map with the API of the lightweight Leaflet web mapping library.

Practical gRPC. Build highly-connected systems with a framework that can run on any platform

Joshua B. Humphries, David Konsumer, David Muto, Robert Ross, ...

While building systems that contain several components, you need a framework that is fast and has minimal network overhead. gRPC is one such open-source tool that is quickly becoming popular and gaining popularity with programmers.Practical gRPC introduces you to gRPC and explains how it compares and contrasts with similar technologies. You’ll be introduced to key technologies such as Protocol Buffers, and work your way up from basic gRPC usage, all the way through to its more advanced capabilities. You’ll learn the best practices for defining and evolving your gRPC APIs, and discover how different tools can be leveraged to get the most out of gRPC and even extend it.By the end of this book, you'll have all the information you need to get started building systems with gRPC.

Practical Guide to Applied Conformal Prediction in Python. Learn and apply the best uncertainty frameworks to your industry applications

Valery Manokhin, Agus Sudjianto

In the rapidly evolving landscape of machine learning, the ability to accurately quantify uncertainty is pivotal. Practical Guide to Applied Conformal Prediction in Python addresses this need by offering an in-depth exploration of Conformal Prediction, a cutting-edge framework set to revolutionize uncertainty management in various ML applications.Embark on a comprehensive journey through Conformal Prediction, exploring its fundamentals and practical applications in binary classification, regression, time series forecasting, imbalanced data, computer vision, and NLP. Each chapter delves into specific aspects, offering hands-on insights and best practices for enhancing prediction reliability. The book concludes with a focus on multi-class classification nuances, providing expert-level proficiency to seamlessly integrate Conformal Prediction into diverse industries. Practical examples in Python using real-world datasets reinforce intuitive explanations, ensuring you acquire a robust understanding of this modern framework for uncertainty quantification.This guide is a beacon for mastering Conformal Prediction in Python, providing a blend of theory and practical application. It serves as a comprehensive toolkit to enhance machine learning skills, catering to professionals from data scientists to ML engineers.

Practical Guide to Azure Cognitive Services. Leverage the power of Azure OpenAI to optimize operations, reduce costs, and deliver cutting-edge AI solutions

Chris Seferlis, Christopher Nellis, Andy Roberts

Azure Cognitive Services and OpenAI are a set of pre-built artificial intelligence (AI) solution APIs that can be leveraged from existing applications, allowing customers to take advantage of Microsoft’s award-winning Vision, Speech, Text, Decision, and GPT-4 AI capabilities.With Practical Guide to Azure Cognitive Services, you’ll work through industry-specific examples of implementations to get a head-start in your production journey. You’ll begin with an overview of the categorization of Azure Cognitive Services and the benefits of embracing AI solutions for practical business applications. After that, you’ll explore the benefits of using Azure Cognitive Services to optimize efficiency and improve predictive capabilities. Then, you’ll learn how to leverage Vision capabilities for quality control, Form Recognizer to streamline supply chain nuances, language understanding to improve customer service, and Cognitive Search for next-generation knowledge-mining solutions.By the end of this book, you’ll be able to implement various Cognitive Services solutions that will help you enhance efficiency, reduce costs, and improve the customer experience at your organization. You’ll also be well equipped to automate mundane tasks by reaping the full potential of OpenAI.

Practical Hardware Pentesting. A guide to attacking embedded systems and protecting them against the most common hardware attacks

Jean-Georges Valle

If you’re looking for hands-on introduction to pentesting that delivers, then Practical Hardware Pentesting is for you. This book will help you plan attacks, hack your embedded devices, and secure the hardware infrastructure.Throughout the book, you will see how a specific device works, explore the functional and security aspects, and learn how a system senses and communicates with the outside world. You’ll set up a lab from scratch and then gradually work towards an advanced hardware lab—but you’ll still be able to follow along with a basic setup. As you progress, you’ll get to grips with the global architecture of an embedded system and sniff on-board traffic, learn how to identify and formalize threats to the embedded system, and understand its relationship with its ecosystem. You’ll discover how to analyze your hardware and locate its possible system vulnerabilities before going on to explore firmware dumping, analysis, and exploitation. The reverse engineering chapter will get you thinking from an attacker point of view; you’ll understand how devices are attacked, how they are compromised, and how you can harden a device against the most common hardware attack vectors. By the end of this book, you will be well-versed with security best practices and understand how they can be implemented to secure your hardware.

Practical Hardware Pentesting. Learn attack and defense techniques for embedded systems in IoT and other devices - Second Edition

Jean-Georges Valle

Practical Hardware Pentesting, Second Edition, is an example-driven guide that will help you plan attacks, hack your embedded devices, and secure the hardware infrastructure.Throughout the book, you’ll explore the functional and security aspects of a device and learn how a system senses and communicates with the outside world. You’ll set up a lab from scratch and gradually work towards an advanced hardware lab.The first part of this book will get you attacking the software of an embedded device. This will get you thinking from an attacker point of view; you’ll understand how devices are attacked, compromised, and how you can harden a device against the most common hardware attack vectors. As you progress, you’ll get to grips with the global architecture of an embedded system and sniff on-board traffic, learn how to identify and formalize threats to the embedded system, and understand its relationship with its ecosystem. This 2nd Edition covers real-world examples featuring various devices like smart TVs, baby monitors, or pacemakers, you’ll discover how to analyze hardware and locate its possible vulnerabilities before going on to explore firmware dumping, analysis, and exploitation.By the end of this book, you’ll and understand how to implement best practices to secure your hardware.

Practical HTML and CSS. Elevate your internet presence by creating modern and high-performance websites for the web - Second Edition

Brett Jephson, Lewis Coulson, Ana Carolina Silveira

In the ever-evolving landscape of web development, mastering HTML and CSS is crucial for building modern, responsive websites. This comprehensive guide equips you with the essential knowledge and skills you need to excel in web design and development.Starting with the foundational principles of HTML and CSS, the book swiftly advances to cover more complex topics, providing a thorough understanding of these vital technologies. You’ll learn how to build websites from scratch, create intuitive user input forms, and enhance web design by integrating multimedia elements like videos, animations, and themes. Emphasizing responsive web design principles, this book teaches you how to create layouts that flawlessly adapt to different devices using media queries. You’ll also get to grips with SEO essentials to optimize website visibility and search engine rankings. A dedicated section guides you through performance optimization techniques to ensure your websites deliver a smooth and lightning-fast user experience.By the end of this HTML and CSS book, you’ll have developed confidence in your web development skills, and you'll be well-equipped to build modern, visually appealing, and high-performing websites.