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The Kaggle Book. Data analysis and machine learning for competitive data science
Konrad Banachewicz, Luca Massaron, Anthony Goldbloom
Millions of data enthusiasts from around the world compete on Kaggle, the most famous data science competition platform of them all. Participating in Kaggle competitions is a surefire way to improve your data analysis skills, network with an amazing community of data scientists, and gain valuable experience to help grow your career.The first book of its kind, The Kaggle Book assembles in one place the techniques and skills you’ll need for success in competitions, data science projects, and beyond. Two Kaggle Grandmasters walk you through modeling strategies you won’t easily find elsewhere, and the knowledge they’ve accumulated along the way. As well as Kaggle-specific tips, you’ll learn more general techniques for approaching tasks based on image, tabular, textual data, and reinforcement learning. You’ll design better validation schemes and work more comfortably with different evaluation metrics.Whether you want to climb the ranks of Kaggle, build some more data science skills, or improve the accuracy of your existing models, this book is for you.Plus, join our Discord Community to learn along with more than 1,000 members and meet like-minded people!
Luca Massaron, Bojan Tunguz, Konrad Banachewicz, Anthony...
Kaggle has become the proving ground for millions of data enthusiasts worldwide, offering what no classroom tutorial can match: battle-tested skills built through real-world challenges and the hands-on experience that employers seek. Every competition sharpens your data analysis skills, expands your network within the data scientist community, and gives compelling proof of expertise to unlock career opportunities.The first book of its kind, The Kaggle Book brings together everything you need to excel in competitions, data science projects, and beyond. This new edition includes fresh content and new chapters on Kaggle Models, time series, and Generative AI competitions, with three Kaggle Grandmasters guiding you through modeling strategies and sharing hard-earned insights accumulated over years of competition.The book extends far past competition tactics, revealing techniques for tackling image, tabular, and textual data as well as reinforcement learning tasks. You’ll also discover tips for designing better validation schemes and working confidently with both standard and unconventional evaluation metrics.Whether you want to climb the Kaggle leaderboard, accelerate your data science career, or improve the accuracy of your models, this book is for you.Join our Discord community of over 1,000 members to learn, share, and grow together!
Konrad Banachewicz, Luca Massaron
More than 80,000 Kaggle novices currently participate in Kaggle competitions. To help them navigate the often-overwhelming world of Kaggle, two Grandmasters put their heads together to write The Kaggle Book, which made plenty of waves in the community. Now, they’ve come back with an even more practical approach based on hands-on exercises that can help you start thinking like an experienced data scientist.In this book, you’ll get up close and personal with four extensive case studies based on past Kaggle competitions. You’ll learn how bright minds predicted which drivers would likely avoid filing insurance claims in Brazil and see how expert Kagglers used gradient-boosting methods to model Walmart unit sales time-series data. Get into computer vision by discovering different solutions for identifying the type of disease present on cassava leaves. And see how the Kaggle community created predictive algorithms to solve the natural language processing problem of subjective question-answering.You can use this workbook as a supplement alongside The Kaggle Book or on its own alongside resources available on the Kaggle website and other online communities. Whatever path you choose, this workbook will help make you a formidable Kaggle competitor.
The KCNA Book. Pass the Kubernetes and Cloud Native Associate exam in style
Nigel Poulton
There is a huge benefit in building small, specialized, single-purpose apps that can self-heal, auto scale, and update regularly without needing downtime. Kubernetes and cloud-native technologies come in handy in building such apps. Possessing the knowledge and skills to leverage Kubernetes can positively enhance possibilities in favor of architects who specialize in cloud-native microservices applications.‘The KCNA Book’ is designed to help those working in technology with a passion to become certified in the Kubernetes and Cloud-Native Associate Exam. You will learn about containerization, microservices, and cloud-native architecture. You will learn about Kubernetes fundamentals and container orchestration. The book also sheds light on cloud-native application delivery and observability. It focuses on the KCNA exam domains and competencies, which can be applied to the sample test included in the book. Put your knowledge to the test and enhance your skills with the all-encompassing topic coverage.Upon completion, you will begin your journey to get the best roles, projects, and organizations with this exam-oriented book.
Gineesh Madapparambath, Russ McKendrick, Ed Price
Kubernetes has become the go-to orchestration platform for containerized applications. As a Kubernetes user, you know firsthand how powerful yet complex this tool can be. The Kubernetes Bible cuts through the complexity, offering hands-on examples and expert advice to conquer containerization challengesWith this new edition, you will master cutting edge security practices, deploy seamlessly and scale effortlessly, ensuring unwavering service availability. You will gain the expertise to craft production-grade applications, secure development environments, navigate complex deployments with ease, and become a security maestro. You will be able to optimize network communication and data management across major cloud platforms. Additionally, this book dives deep into these challenges, offering solutions such as multi-container Pods, advanced security techniques, and expert networking guidance. You will also explore persistent storage advancements, cloud-specific cluster management updates, and best practices for traffic routingBy the end of this comprehensive guide, you will possess the skills and knowledge to orchestrate your containerized applications with precision, ensuring their optimal performance and scalability. Stop settling for basic container management. Order your copy today and orchestrate your containers to greatness.
Nassim Kebbani, Piotr Tylenda, Russ McKendrick
With its broad adoption across various industries, Kubernetes is helping engineers with the orchestration and automation of container deployments on a large scale, making it the leading container orchestration system and the most popular choice for running containerized applications.This Kubernetes book starts with an introduction to Kubernetes and containerization, covering the setup of your local development environment and the roles of the most important Kubernetes components. Along with covering the core concepts necessary to make the most of your infrastructure, this book will also help you get acquainted with the fundamentals of Kubernetes. As you advance, you'll learn how to manage Kubernetes clusters on cloud platforms, such as Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform (GCP), and develop and deploy real-world applications in Kubernetes using practical examples. Additionally, you'll get to grips with managing microservices along with best practices.By the end of this book, you'll be equipped with battle-tested knowledge of advanced Kubernetes topics, such as scheduling of Pods and managing incoming traffic to the cluster, and be ready to work with Kubernetes on cloud platforms.
Nigel Poulton, Pushkar Joglekar
Kubernetes is a powerful container orchestration platform that enables efficient application deployment, scaling, and management. This book begins with foundational concepts, explaining Kubernetes architecture, control planes, worker nodes, and the declarative model. Readers will learn how to set up a Kubernetes environment using tools like Docker Desktop and cloud-based solutions.The book then covers core operational topics, including Pods, Deployments, Namespaces, and Services, providing hands-on exercises to reinforce learning. Networking, storage, and security are explored in depth, with real-world examples of managing applications, configuring RBAC, and using ConfigMaps and Secrets. Advanced topics such as StatefulSets, the Kubernetes API, and service discovery offer insights into optimizing and securing Kubernetes workloads.Security is a key focus, with chapters dedicated to API security, threat modeling, and real-world Kubernetes security practices. Readers will gain practical knowledge on securing clusters, managing access controls, and mitigating common threats. By the end, they will be equipped with the skills to deploy, scale, and secure Kubernetes environments effectively.
The Kubernetes Book. Navigate the world of Kubernetes with expertise - Second Edition
Nigel Poulton, Pushkar Joglekar
Containers transformed how we package and deploy applications, but they came with inherent challenges. Kubernetes is a platform for deploying and managing containerized applications at scale. It also abstracts underlying infrastructure, making it easier to deploy and manage applications across heterogenous clouds and on-premises environments. The Kubernetes Book offers a beginner-friendly approach to mastering Kubernetes architecture and core concepts such as Pods, Deployments, Services, StatefulSets, Ingress, & ConfigMaps. It also demystifies the Kubernetes API, teaches you how to secure Kubernetes, and brings you up to speed with important cloud-native concepts such as microservices, declarative configuration, desired state, & reconciliation. The book also serves as a comprehensive guide for software developers, systems administrators, cloud engineers, and architects to help them master Kubernetes. It offers the most precise explanations and is full of practical examples to help develop applications on a laptop and then deploy them to real-world Kubernetes environments. The Kubernetes Book is updated annually, meaning it's always up to date with the latest and greatest in the Kubernetes and cloud-native ecosystems.
The Kubernetes Book. The fastest way to get your head around Kubernetes
Nigel Poulton, Pushkar Joglekar
Kubernetes is the leading orchestrator of cloud-native apps. With knowledge of how to work with Kubernetes, you can easily deploy and manage applications on the cloud or in your on-premises data center. The book begins by introducing you to Kubernetes and showing you how to install it. You’ll learn how to use Kubernetes Services and bring stable and reliable networking to apps that are deployed on Kubernetes. You'll delve deep into the powerful storage subsystem of Kubernetes and learn how to leverage the variety of external storage backends in your applications. As the book progresses, it shows you how to use features such as DaemonSets, Helm, and RBAC to enhance your Kubernetes applications. You'll explore the six categories of identifying vulnerabilities and look at a few ways to prevent and mitigate them. You'll also look at ways to secure the software delivery pipeline by discussing some image-related best practices. The book ends by sharing with you some resources that’ll help take your Kubernetes knowledge to the next level.By the end of the book, you’ll have the confidence and skills to leverage all the features of Kubernetes to develop scalable applications.
Michael Dame
From incomplete collections of knowledge and varying design approaches to technical knowledge barriers, Kubernetes users face various challenges when developing their own operators. Knowing how to write, deploy, and pack operators makes cluster management automation much easier – and that's what this book is here to teach you.Beginning with operators and Operator Framework fundamentals, the book delves into how the different components of Operator Framework (such as the Operator SDK, Operator Lifecycle Manager, and OperatorHub.io) are used to build operators. You’ll learn how to write a basic operator, interact with a Kubernetes cluster in code, and distribute that operator to users. As you advance, you’ll be able to develop a sample operator in the Go programming language using Operator SDK tools before running it locally with Operator Lifecycle Manager, and also learn how to package an operator bundle for distribution. The book covers best practices as well as sample applications and case studies based on real-world operators to help you implement the concepts you’ve learned.By the end of this Kubernetes book, you’ll be able to build and add application-specific operational logic to a Kubernetes cluster, making it easier to automate complex applications and augment the platform.
The Kubernetes Workshop. Learn how to build and run highly scalable workloads on Kubernetes
Zachary Arnold, Sahil Dua, Wei Huang, Faisal...
Thanks to its extensive support for managing hundreds of containers that run cloud-native applications, Kubernetes is the most popular open source container orchestration platform that makes cluster management easy. This workshop adopts a practical approach to get you acquainted with the Kubernetes environment and its applications.Starting with an introduction to the fundamentals of Kubernetes, you’ll install and set up your Kubernetes environment. You’ll understand how to write YAML files and deploy your first simple web application container using Pod. You’ll then assign human-friendly names to Pods, explore various Kubernetes entities and functions, and discover when to use them. As you work through the chapters, this Kubernetes book will show you how you can make full-scale use of Kubernetes by applying a variety of techniques for designing components and deploying clusters. You’ll also get to grips with security policies for limiting access to certain functions inside the cluster. Toward the end of the book, you’ll get a rundown of Kubernetes advanced features for building your own controller and upgrading to a Kubernetes cluster without downtime.By the end of this workshop, you’ll be able to manage containers and run cloud-based applications efficiently using Kubernetes.
The Lean-Agile Way. Unleash business results in the digital era with value stream management
Cecil 'Gary' Rupp, Richard Knaster, Steve Pereira,...
In today’s fast-paced business landscape, efficiency is essential. Authored by industry experts Cecil ‘Gary’ Rupp, a Lean-Agile consultant with over three decades of executive experience; Richard Knaster, a SAFe® Fellow and transformation leader; Steve Pereira, a value stream consultant and board advisor; and Al Shalloway, creator of FLEX and PMI’s Disciplined Agile Value Stream Consultant workshop, the book offers proven strategies to streamline processes, enhance products, and improve service delivery. You’ll start with an introduction to foundational Lean and Agile practices, recognizing the significance of digital enhancements in modernizing business processes. As you progress, you'll learn VSM techniques to identify and prioritize work and investments to provide maximum value to customers. Moreover, you'll grasp Lean-Agile practices aimed at promoting collaboration among teams and ensuring the continuous flow of product-oriented deliveries tailored to address customer needs. Finally, you'll gain executive-level insights on how organizations must access timely information for decision-making and foster a culture of continuous business transformation. Armed with this knowledge and a robust toolkit, you'll be empowered to drive meaningful change, optimize resources, and stay ahead in the rapidly evolving marketplace.
Damian Wojsław, Grzegorz Adamowicz
The Linux DevOps Handbook is a comprehensive resource that caters to both novice and experienced professionals, ensuring a strong foundation in Linux. This book will help you understand how Linux serves as a cornerstone of DevOps, offering the flexibility, stability, and scalability essential for modern software development and operations.You’ll begin by covering Linux distributions, intermediate Linux concepts, and shell scripting to get to grips with automating tasks and streamlining workflows. You’ll then progress to mastering essential day-to-day tools for DevOps tasks. As you learn networking in Linux, you’ll be equipped with connection establishment and troubleshooting skills. You’ll also learn how to use Git for collaboration and efficient code management.The book guides you through Docker concepts for optimizing your DevOps workflows and moves on to advanced DevOps practices, such as monitoring, tracing, and distributed logging. You’ll work with Terraform and GitHub to implement continuous integration (CI)/continuous deployment (CD) pipelines and employ Atlantis for automated software delivery. Additionally, you’ll identify common DevOps pitfalls and strategies to avoid them.By the end of this book, you’ll have built a solid foundation in Linux fundamentals, practical tools, and advanced practices, all contributing to your enhanced Linux skills and successful DevOps implementation.
David Ping
When equipped with a highly scalable machine learning (ML) platform, organizations can quickly scale the delivery of ML products for faster business value realization. There is a huge demand for skilled ML solutions architects in different industries, and this handbook will help you master the design patterns, architectural considerations, and the latest technology insights you’ll need to become one.You’ll start by understanding ML fundamentals and how ML can be applied to solve real-world business problems. Once you've explored a few leading problem-solving ML algorithms, this book will help you tackle data management and get the most out of ML libraries such as TensorFlow and PyTorch.Using open source technology such as Kubernetes/Kubeflow to build a data science environment and ML pipelines will be covered next, before moving on to building an enterprise ML architecture using Amazon Web Services (AWS). You’ll also learn about security and governance considerations, advanced ML engineering techniques, and how to apply bias detection, explainability, and privacy in ML model development. And finally, you'll get acquainted with AWS AI services and their applications in real-world use cases.By the end of this audiobook, you’ll be able to design and build an ML platform to support common use cases and architecture patterns like a true professional.
David Ping
When equipped with a highly scalable machine learning (ML) platform, organizations can quickly scale the delivery of ML products for faster business value realization. There is a huge demand for skilled ML solutions architects in different industries, and this handbook will help you master the design patterns, architectural considerations, and the latest technology insights you’ll need to become one. You’ll start by understanding ML fundamentals and how ML can be applied to solve real-world business problems. Once you've explored a few leading problem-solving ML algorithms, this book will help you tackle data management and get the most out of ML libraries such as TensorFlow and PyTorch. Using open source technology such as Kubernetes/Kubeflow to build a data science environment and ML pipelines will be covered next, before moving on to building an enterprise ML architecture using Amazon Web Services (AWS). You’ll also learn about security and governance considerations, advanced ML engineering techniques, and how to apply bias detection, explainability, and privacy in ML model development. And finally, you'll get acquainted with AWS AI services and their applications in real-world use cases.By the end of this book, you’ll be able to design and build an ML platform to support common use cases and architecture patterns like a true professional.
David Ping
David Ping, Head of GenAI and ML Solution Architecture for global industries at AWS, provides expert insights and practical examples to help you become a proficient ML solutions architect, linking technical architecture to business-related skills.You'll learn about ML algorithms, cloud infrastructure, system design, MLOps , and how to apply ML to solve real-world business problems. David explains the generative AI project lifecycle and examines Retrieval Augmented Generation (RAG), an effective architecture pattern for generative AI applications. You’ll also learn about open-source technologies, such as Kubernetes/Kubeflow, for building a data science environment and ML pipelines before building an enterprise ML architecture using AWS. As well as ML risk management and the different stages of AI/ML adoption, the biggest new addition to the handbook is the deep exploration of generative AI.By the end of this book , you’ll have gained a comprehensive understanding of AI/ML across all key aspects, including business use cases, data science, real-world solution architecture, risk management, and governance. You’ll possess the skills to design and construct ML solutions that effectively cater to common use cases and follow established ML architecture patterns, enabling you to excel as a true professional in the field.