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Lubanovic Bill: Introducing Python

Introducing Python

Modern Computing in Simple Packages

If you know how to program, you have the skills to turn data into knowledge. This thoroughly revised edition presents statistical concepts computationally, rather than mathematically, using programs written in Python. Through practical examples and exercises based on real-world datasets, you'll learn the entire process of exploratory data analysis--from wrangling data and generating statistics to identifying patterns and testing hypotheses. Whether you're a data scientist, software engineer, or data enthusiast, you'll get up to speed on commonly used tools including NumPy, SciPy, and Pandas. You'll explore distributions, relationships between variables, visualization, and many other concepts. And all chapters are available as Jupyter notebooks, so you can read the text, run the code, and work on exercises all in one place. <ul> <li>Analyze data distributions and visualize patterns using Python libraries</li> <li>Improve predictions and insights with regression models</li> <li>Dive into specialized topics like time series analysis and survival analysis</li> <li>Integrate statistical techniques and tools for validation, inference, and more</li> <li>Communicate findings with effective data visualization</li> <li>Troubleshoot common data analysis challenges</li> <li>Boost reproducibility and collaboration in data analysis projects with interactive notebooks</li> </ul>

Exploratory Data Analysis

Think STATS

Digital technology was supposed to change the world for the better, but it has left us miserable, divided and misinformed-when it hasn't posed a direct threat to our physical safety. As acclaimed writer Darryl Campbell explains, the problem isn't just greedy CEOs promising to "change the world" as they seek ever more eyeballs and app downloads. It's that the tech industry struggles to understand what its products actually do and how they might fail. The reason is twofold: an unshakeable faith in managerialism-the notion that every business can be reduced to a spreadsheet overseen by MBAs-and an equally strong belief in software as the solution to all problems. From aeroplane disasters to PowerPoint propaganda to the perils of generative AI, Campbell uncovers a pattern of recklessness and overconfidence in the managerial class-and ultimately argues that developers themselves must intervene to curb corporate power.

Why the Managerial Class Loses Control of Software

Fatal Abstraction

A one-stop-shop for all the math you should have learned for your programming career. Every great programming challenge has mathematical principles at its heart. Whether you’re optimizing search algorithms, building physics engines for games, or training neural networks, success depends on your grasp of core mathematical concepts.&nbsp; In Math for Programming, you’ll master the essential mathematics that will take you from basic coding to serious software development. You’ll discover how vectors and matrices give you the power to handle complex data, how calculus drives optimization and machine learning, and how graph theory leads to advanced search algorithms. Through clear explanations and practical examples, you’ll learn to: <ul><li>Harness linear algebra to manipulate data with unprecedented efficiency</li><li>Apply calculus concepts to optimize algorithms and drive simulations</li><li>Use probability and statistics to model uncertainty and analyze data</li><li>Master the discrete mathematics that powers&nbsp;modern data structures</li><li>Solve dynamic problems through differential equations</li></ul> Whether you’re seeking to fill gaps in your mathematical foundation or looking to refresh your understanding of core concepts, Math for Programming will turn complex math into a practical tool you’ll use every day.

A one-stop-shop for all the math you should have learned for your programming career. Every great programming challenge has mathematical principles at its heart. Whether you’re optimizing search algorithms, building physics engines for games, or training neural networks, success depends on your grasp of core mathematical concepts.&nbsp; In Math for Programming, you’ll master the essential mathematics that will take you from basic coding to serious software development. You’ll discover how vectors and matrices give you the power to handle complex data, how calculus drives optimization and machine learning, and how graph theory leads to advanced search algorithms. Through clear explanations and practical examples, you’ll learn to: <ul><li>Harness linear algebra to manipulate data with unprecedented efficiency</li><li>Apply calculus concepts to optimize algorithms and drive simulations</li><li>Use probability and statistics to model uncertainty and analyze data</li><li>Master the discrete mathematics that powers&nbsp;modern data structures</li><li>Solve dynamic problems through differential equations</li></ul> Whether you’re seeking to fill gaps in your mathematical foundation or looking to refresh your understanding of core concepts, Math for Programming will turn complex math into a practical tool you’ll use every day.

Math for Programming

AI-assisted coding and cloud-based tools are already transforming how modern applications are built. Bolt.new, a powerful in-browser AI agent from StackBlitz, streamlines the development process, allowing you to prototype quickly, debug intelligently, and launch confidently--no local setup required. Whether you're new to full stack development or looking to supercharge your workflow, this accessible guide takes you from JavaScript and React fundamentals all the way to deploying sophisticated apps with Bolt.new and StackBlitz. Through real-world projects like a movie explorer and a Supabase-powered workout tracker, you'll master prompt-first development, tap into WebContainers for running backend logic in the browser, and discover a seamless path from idea to deployment. If you're ready to rethink how web apps are built--from the command line to the cloud--this book is your blueprint. <ul> <li>Understand the principles behind prompt-first development and effectively use AI-assisted tooling in Bolt.new</li> <li> Explore the individual strengths of, differences between, and workflows for Bolt.new and StackBlitz</li> <li> Build, debug, and deploy full stack applications using Bolt.new with AI-assisted code generation, Supabase integration, and Netlify deployment</li> <li> Manage iterative development with Bolt.new features such as checkpoints, rollbacks, and prompt tuning</li> <li> Transition seamlessly from Bolt.new to StackBlitz, enhance your applications, and leverage browser-based backends, terminal access, and GitHub integration</li> <ul>
</ul></ul>

Unlock the Future of AI-First Development

Building Web Apps with Bolt

The transition to cloud computing has created unprecedented demand for professionals with the skills to implement solutions that take advantage of the scalability, flexibility, and resilience the cloud offers. The Microsoft Certified Azure Developer Associate (AZ-204) Study Guide is your comprehensive resource for mastering the competencies required to design, develop, and deploy secure and scalable Azure architectures tailored to your organization's needs. The foundational skills you'll learn in this guide will help you successfully navigate the Microsoft Certified Azure Developer Associate exam. But beyond its impact on your resume, this book will imbue you with the confidence to excel as a Microsoft Certified Azure Developer Associate for years to come. The certification journey is challenging, but with the right insights, a well-structured study plan, and hands-on practice, you can position yourself for success. <ul> <li>Design optimal cloud architectures aligned with best practices</li> <li>Provision and oversee core infrastructure with a focus on security and compliance</li> <li>Optimize both technical and business processes</li> <li>Manage critical cloud resources essential for organizational success</li> <li>Ensure operational reliability and high availability</li> </ul>

In-Depth Guidance and Practice

Microsoft Certified Azure Developer Associate (AZ-204) Study Guide

Learn Kotlin Through 37 Projects Kotlin isn’t just for building Android apps. As you’ll learn in Kotlin from Scratch, it’s also a general programming language for crafting both elegant and efficient code. With the aid of 37 hands-on projects, you’ll move quickly through the language basics while building your problem-solving skills, even tackling advanced concepts like fractals, dynamic systems, and nature-inspired algorithms. You’ll explore the way Kotlin handles variables, control structures, functions, classes, and data structures, and you’ll learn to create visualizations using Kotlin and the JavaFX graphics library. Then you’ll build increasingly sophisticated apps to practice what you’ve learned while tackling challenges from math and science to algorithms and optimization. As you progress through the book, you will: <ul><li>Simulate physical systems, like the intricate dance of binary stars</li><li>Implement the classic Hill cipher for encryption and decryption&nbsp;</li><li>Generate beautiful fractals with recursive algorithms&nbsp;</li><li>Program classic computer science algorithms for sorting and searching</li><li>Solve the infamous Berlin52 traveling salesman problem&nbsp;</li></ul> Expand your language repertoire and improve your computational thinking with Kotlin from Scratch.

Learn Kotlin Through 37 Projects Kotlin isn’t just for building Android apps. As you’ll learn in Kotlin from Scratch, it’s also a general programming language for crafting both elegant and efficient code. With the aid of 37 hands-on projects, you’ll move quickly through the language basics while building your problem-solving skills, even tackling advanced concepts like fractals, dynamic systems, and nature-inspired algorithms. You’ll explore the way Kotlin handles variables, control structures, functions, classes, and data structures, and you’ll learn to create visualizations using Kotlin and the JavaFX graphics library. Then you’ll build increasingly sophisticated apps to practice what you’ve learned while tackling challenges from math and science to algorithms and optimization. As you progress through the book, you will: <ul><li>Simulate physical systems, like the intricate dance of binary stars</li><li>Implement the classic Hill cipher for encryption and decryption&nbsp;</li><li>Generate beautiful fractals with recursive algorithms&nbsp;</li><li>Program classic computer science algorithms for sorting and searching</li><li>Solve the infamous Berlin52 traveling salesman problem&nbsp;</li></ul> Expand your language repertoire and improve your computational thinking with Kotlin from Scratch.

A Project-Based Introduction for the Intrepid Programmer

Kotlin from Scratch

If you've been curious about artificial intelligence and machine learning but didn't know where to start, this is the book you've been waiting for. Focusing on the subfield of machine learning known as deep learning, it explains core concepts and gives you the foundation you need to start building your own models. Rather than simply outlining recipes for using existing toolkits, Practical Deep Learning, 2nd Edition teaches you the why of deep learning and will inspire you to explore further. All you need is basic familiarity with computer programming and high school math - the book will cover the rest. After an introduction to Python, you'll move through key topics like how to build a good training dataset, work with the scikit-learn and Keras libraries, and evaluate your models' performance. You'll also learn: How to use classic machine learning models like k-Nearest Neighbours, Random Forests, and Support Vector Machines, How neural networks work and how they're trained, How to use convolutional neural networks, How to develop a successful deep learning model from scratch. You'll conduct experiments along the way, building to a final case study that incorporates everything you've learned. This second edition is thoroughly revised and updated, and adds six new chapters to further your exploration of deep learning from basic CNNs to more advanced models. New chapters cover fine tuning, transfer learning, object detection, semantic segmentation, multilabel classification, self-supervised learning, generative adversarial networks, and large language models. The perfect introduction to this dynamic, ever-expanding field, Practical Deep Learning, 2nd Edition will give you the skills and confidence to dive into your own machine learning projects.

Deep learning made simple. Dip into deep learning without drowning in theory with this fully updated edition of Practical Deep Learning from experienced author and AI expert Ronald T. Kneusel. After a brief review of basic math and coding principles, you’ll dive into hands-on experiments and learn to build working models for everything from image analysis to creative writing, and gain a thorough understanding of how each technique works under the hood. Whether you’re a developer looking to add AI to your toolkit or a student seeking practical machine learning skills, this book will teach you: <ul><li>How neural networks work and how they’re trained</li><li>How to use classical machine learning models</li><li>How to develop a deep learning model from scratch</li><li>How to evaluate models with industry-standard metrics</li><li>How to create your own generative AI models</li></ul> Each chapter emphasizes practical skill development and experimentation, building to a case study that incorporates everything you’ve learned to classify audio recordings. Examples of working code you can easily run and modify are provided, and all code is freely available on GitHub. With Practical Deep Learning, second edition, you’ll gain the skills and confidence you need to build real AI systems that solve real problems. New to this edition: Material on computer vision, fine-tuning and transfer learning, localization, self-supervised learning, generative AI for novel image creation, and large language models for in-context learning, semantic search, and retrieval-augmented generation (RAG).

A Python-Based Introduction

Practical Deep Learning, 2nd Edition

Whether they're building a startup or scaling an established org, engineering leaders know the real job is keeping chaos under control. In a world of shifting priorities, scarce resources, and rapid change, leadership means embracing the unknown, managing moving targets, and creating clarity where there's none. Sometimes, you're building the plane as you're flying it--writing the roadmap as you go, designing processes in real time. Engineering Leadership: The Hard Parts cuts through the noise, offering a guide for tackling these gritty, real-world challenges. Current and future leaders, this is your toolkit. It's packed with principles, techniques, and mental models for thriving in uncertainty. <ul><li>Navigate the full scope: Step into engineering leadership's complex, multifaceted role</li> <li>Build high-impact teams: Master advanced techniques to grow and lead your technical talent</li> <li>Align and execute: Connect strategy to business outcomes, scale effectively, and balance innovation with precision</li> <li>Lead with resilience: Adapt quickly and drive continuous improvement</li> <li>Accelerate your career: Develop your leadership edge and unlock new growth</li> </ul> Stay ahead. Lead with purpose.

Navigating Chaos to Build Teams That Deliver

Engineering Leadership: The Hard Parts

Not the Same Old JavaScript. Think you know JavaScript? Think again. This isn’t your typical coding book—it’s a deep dive into the powerful world of data structures and algorithms that will transform the way you approach problem solving in JavaScript. Whether you’re a frontend developer tackling complex applications, a backend engineer building scalable systems, or a programmer preparing for technical interviews, this book will revolutionize the way you code.&nbsp; Key features include: <ul><li>Modern JavaScript techniques: Use the latest language features and functional programming principles for cleaner, more efficient code.</li><li>Performance-focused approach: Analyze and optimize algorithms using Big O notation.</li><li>Essential algorithms explained: Implement and fine-tune core algorithms like quicksort, merge sort, digital search, and binary search.</li><li>Algorithm design strategies: Solve challenging problems with techniques like recursion, dynamic programming, backtracking, and brute-force search.</li><li>Advanced data structures: Explore complex structures such as binary search trees, heaps, and graphs. </li></ul> Each chapter is carefully crafted with clear, no-nonsense explanations of complex concepts, real-world coding examples, and challenging questions (with answers at the end) to reinforce your understanding. Ready to break free from ordinary JavaScript? Whether your aim is to build cutting-edge web applications, optimize critical systems, or land your dream job, this book equips you with the advanced JavaScript knowledge that sets true experts apart.

Not the Same Old JavaScript. Think you know JavaScript? Think again. This isn’t your typical coding book—it’s a deep dive into the powerful world of data structures and algorithms that will transform the way you approach problem solving in JavaScript. Whether you’re a frontend developer tackling complex applications, a backend engineer building scalable systems, or a programmer preparing for technical interviews, this book will revolutionize the way you code.&nbsp; Key features include: <ul><li>Modern JavaScript techniques: Use the latest language features and functional programming principles for cleaner, more efficient code.</li><li>Performance-focused approach: Analyze and optimize algorithms using Big O notation.</li><li>Essential algorithms explained: Implement and fine-tune core algorithms like quicksort, merge sort, digital search, and binary search.</li><li>Algorithm design strategies: Solve challenging problems with techniques like recursion, dynamic programming, backtracking, and brute-force search.</li><li>Advanced data structures: Explore complex structures such as binary search trees, heaps, and graphs. </li></ul> Each chapter is carefully crafted with clear, no-nonsense explanations of complex concepts, real-world coding examples, and challenging questions (with answers at the end) to reinforce your understanding. Ready to break free from ordinary JavaScript? Whether your aim is to build cutting-edge web applications, optimize critical systems, or land your dream job, this book equips you with the advanced JavaScript knowledge that sets true experts apart.

Data Structures and Algorithms in JavaScript

A hands-on toolkit for securing contemporary cloud environments In Cloud Security Fundamentals: Building the Foundations for Secure Cloud Platforms, cybersecurity leader and educator, Jason Edwards, delivers a comprehensive guide to safeguarding data, applications, and infrastructure in the cloud. The author offers a complete walkthrough of cloud security, moving from foundational concepts to advanced, forward-looking practices. The book is filled with practical examples, hands-on guidance, and lessons drawn from real-world cloud security incidents and breaches. It equips readers with the tools and knowledge they need to defend against threats in cloud environments and how to understand coming developments in cloud technology that will impact organizations in all industries. Inside the book: <ul><li>A thorough introduction to cloud-native and advanced security practices for contemporary firms</li> <li> A chapter on relevant cloud security certifications and professional growth advice</li> <li>Practical discussions of foundational concepts in cloud security, including IAM, Zero Trust, and DevSecOps</li> <li> Complete treatments of advanced cloud security themes, like leadership strategies, operational best practices, and techniques for dealing with common and emerging threats</li></ul> Perfect for cloud security professionals, IT managers, and DevOps professionals, Cloud Security Fundamentals will also benefit system administrators, compliance and risk officers, consultants, auditors, and technology students in a variety of fields who require a foundational understanding of cloud security concepts.

Building the Foundations for Secure Cloud Platforms

Cloud Security Fundamentals

Master the inner workings of your x64 Linux system and expand your OS expertise by writing your very own debugger using C++. If debuggers seem like magic to you, there is no better way to demystify them than to write your own. This book will show you exactly how to do it, walking you through the entire process of building a debugger for x64 Linux systems using C++. As go from an empty filesystem folder to a fully fledged debugger capable of setting breakpoints, stepping through code, manipulating variables, and more, you’ll learn how to: <ul><li>Attach to a process</li><li>Read and write to registers</li><li>Set hardware and software breakpoints</li><li>Output disassembly</li><li>Support multithreading and other tasks</li></ul> As you add features to your debugger, you’ll also pick up a wealth of knowledge about operating systems, compilers, software testing, and low-level programming that you can use in your day-to-day development.

Building a Debugger

As a working software developer, you know how to complete your tasks with solid code, whether it's on the frontend or backend. Now you're ready to move to the next level in your career, and you need to understand the subtle yet deep skills it takes to become a senior developer. This practical book shows you everything it takes to create a full-stack web application hosted on a cloud platform. Senior staff engineer Milecia McGregor helps you see how the whole system works and how senior developers arrive at technical decisions. You'll learn about design and development principles and when to apply them. You'll also discover strategies for working with different teams and understand how the product team makes its decisions. In four parts, this book shows you how to: <ul> <li>Translate designs into tasks and learn the questions you'll need to ask the product team </li><li>Walk through development considerations for the backend like overall architecture, security, and third-party services </li><li>Build the project's user interface as well as state and data management, performance, and other concerns associated with frontend apps </li><li>Connect the frontend, backend, and other systems and deploy a full stack app to production </li></ul>

The Hidden Parts Every Mid-Level Developer Needs to Know

Full-Stack JavaScript Strategies

Introducing Python

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