Wydawca: 24
Asim Zulfiqar
ESP32 is a versatile microcontroller and a great starting point for anyone venturing into the IoT realm, but its configuration and interfacing of sensors can be challenging for new users. Arduino Integrated Development Environment (IDE) simplifies programming, uploading code, and utilization of ESP32 capabilities, enabling users to incorporate it into their IoT projects with ease. This book will help you learn the essentials of sensing, networking, data processing, and applications with ESP32, laying a strong foundation for further IoT development.Starting with ESP32 and Arduino Ide 2.0 basics, you'll first explore practical implementation examples of interfacing sensors with ESP32. These examples will also teach you how to interface the ESP32 camera and display modules with ESP32. As you progress, you’ll get to grips with IoT network and data protocols, as well as the many options they unlock within IoT applications. The book will also help you leverage your newly acquired knowledge with exciting projects ranging from smart connected devices to data loggers and automation.By the end of this book, you'll confidently navigate ESP32 projects with newfound knowledge and skills, know what IoT protocol to select for your applications, and successfully build and deploy your own IoT projects.
Hands-On Ethical Hacking Tactics. Strategies, tools, and techniques for effective cyber defense
Shane Hartman, Ken Dunham
If you’re an ethical hacker looking to boost your digital defenses and stay up to date with the evolving cybersecurity landscape, then this book is for you. Hands-On Ethical Hacking Tactics is a comprehensive guide that will take you from fundamental to advanced levels of ethical hacking, offering insights into both offensive and defensive techniques. Written by a seasoned professional with 20+ years of experience, this book covers attack tools, methodologies, and procedures, helping you enhance your skills in securing and defending networks.The book starts with foundational concepts such as footprinting, reconnaissance, scanning, enumeration, vulnerability assessment, and threat modeling. Next, you’ll progress to using specific tools and procedures for hacking Windows, Unix, web servers, applications, and databases. The book also gets you up to speed with malware analysis. Throughout the book, you’ll experience a smooth transition from theoretical concepts to hands-on techniques using various platforms. Finally, you’ll explore incident response, threat hunting, social engineering, IoT hacking, and cloud exploitation, which will help you address the complex aspects of ethical hacking.By the end of this book, you’ll have gained the skills you need to navigate the ever-changing world of cybersecurity.
Denis Rothman
Effectively translating AI insights to business stakeholders requires careful planning, design, and visualization choices. Describing the problem, the model, and the relationships among variables and their findings are often subtle, surprising, and technically complex.Hands-On Explainable AI (XAI) with Python will see you work with specific hands-on machine learning Python projects that are strategically arranged to enhance your grasp on AI results analysis. You will be building models, interpreting results with visualizations, and integrating XAI reporting tools and different applications.You will build XAI solutions in Python, TensorFlow 2, Google Cloud’s XAI platform, Google Colaboratory, and other frameworks to open up the black box of machine learning models. The book will introduce you to several open-source XAI tools for Python that can be used throughout the machine learning project life cycle.You will learn how to explore machine learning model results, review key influencing variables and variable relationships, detect and handle bias and ethics issues, and integrate predictions using Python along with supporting the visualization of machine learning models into user explainable interfaces.By the end of this AI book, you will possess an in-depth understanding of the core concepts of XAI.
Suresh Kumar Mukhiya, Usman Ahmed
Exploratory Data Analysis (EDA) is an approach to data analysis that involves the application of diverse techniques to gain insights into a dataset. This book will help you gain practical knowledge of the main pillars of EDA - data cleaning, data preparation, data exploration, and data visualization.You’ll start by performing EDA using open source datasets and perform simple to advanced analyses to turn data into meaningful insights. You’ll then learn various descriptive statistical techniques to describe the basic characteristics of data and progress to performing EDA on time-series data. As you advance, you’ll learn how to implement EDA techniques for model development and evaluation and build predictive models to visualize results. Using Python for data analysis, you’ll work with real-world datasets, understand data, summarize its characteristics, and visualize it for business intelligence.By the end of this EDA book, you’ll have developed the skills required to carry out a preliminary investigation on any dataset, yield insights into data, present your results with visual aids, and build a model that correctly predicts future outcomes.
Radhika Datar, Harish Garg
Hands-On Exploratory Data Analysis with R will help you build a strong foundation in data analysis and get well-versed with elementary ways to analyze data. You will learn how to understand your data and summarize its characteristics. You'll also study the structure of your data, and you'll explore graphical and numerical techniques using the R language.This book covers the entire exploratory data analysis (EDA) process—data collection, generating statistics, distribution, and invalidating the hypothesis. As you progress through the book, you will set up a data analysis environment with tools such as ggplot2, knitr, and R Markdown, using DOE Scatter Plot and SML2010 for multifactor, optimization, and regression data problems.By the end of this book, you will be able to successfully carry out a preliminary investigation on any dataset, uncover hidden insights, and present your results in a business context.
Shmuel Oluwa
Financial modeling is a core skill required by anyone who wants to build a career in finance. Hands-On Financial Modeling with Excel for Microsoft 365 explores financial modeling terminologies with the help of Excel.Starting with the key concepts of Excel, such as formulas and functions, this updated second edition will help you to learn all about referencing frameworks and other advanced components for building financial models. As you proceed, you'll explore the advantages of Power Query, learn how to prepare a 3-statement model, inspect your financial projects, build assumptions, and analyze historical data to develop data-driven models and functional growth drivers. Next, you'll learn how to deal with iterations and provide graphical representations of ratios, before covering best practices for effective model testing. Later, you'll discover how to build a model to extract a statement of comprehensive income and financial position, and understand capital budgeting with the help of end-to-end case studies.By the end of this financial modeling Excel book, you'll have examined data from various use cases and have developed the skills you need to build financial models to extract the information required to make informed business decisions.
Shmuel Oluwa
Financial modeling is a core skill required by anyone who wants to build a career in finance. Hands-On Financial Modeling with Microsoft Excel 2019 explores terminologies of financial modeling with the help of Excel.This book will provides you with an overview of the steps you should follow to build an integrated financial model. You will explore the design principles, functions, and techniques of building models in a practical manner. Starting with the key concepts of Excel, such as formulas and functions, you will learn about referencing frameworks and other advanced components for building financial models. Later chapters will help you understand your financial projects, build assumptions, and analyze historical data to develop data-driven models and functional growth drivers. The book takes an intuitive approach to model testing and covers best practices and practical use cases.By the end of this book, you will have examined the data from various use cases, and have the skills you need to build financial models to extract the information required to make informed business decisions.
Jiri Pik, Sourav Ghosh
Creating an effective system to automate your trading can help you achieve two of every trader’s key goals; saving time and making money. But to devise a system that will work for you, you need guidance to show you the ropes around building a system and monitoring its performance. This is where Hands-on Financial Trading with Python can give you the advantage.This practical Python book will introduce you to Python and tell you exactly why it’s the best platform for developing trading strategies. You’ll then cover quantitative analysis using Python, and learn how to build algorithmic trading strategies with Zipline using various market data sources.Using Zipline as the backtesting library allows access to complimentary US historical daily market data until 2018. As you advance, you will gain an in-depth understanding of Python libraries such as NumPy and pandas for analyzing financial datasets, and explore Matplotlib, statsmodels, and scikit-learn libraries for advanced analytics.As you progress, you’ll pick up lots of skills like time series forecasting, covering pmdarima and Facebook Prophet.By the end of this trading book, you will be able to build predictive trading signals, adopt basic and advanced algorithmic trading strategies, and perform portfolio optimization to help you get —and stay—ahead of the markets.