Experience the unforgettable, heartbreaking love story set in post-World War II North Carolina about a young socialite and the boy who once stole her heart -- coming to Broadway as a musical in February 2024.Every so often a love story so captures our hearts that it becomes more than a story -- it becomes an experience to remember forever. The Notebook is such a book. It is a celebration of how passion can be ageless and timeless, a tale that moves us to laughter and tears and makes us believe in true love all over again . . .At thirty-one, Noah Calhoun, back in coastal North Carolina after World War II, is haunted by images of the girl he lost more than a decade earlier. At twenty-nine, socialite Allie Nelson is about to marry a wealthy lawyer, but she cannot stop thinking about the boy who long ago stole her heart. Thus begins the story of a love so enduring and deep it can turn tragedy into triumph, and may even have the power to create a miracle . . .

A high school rebel and a minister's daughter find strength in each other in this star-crossed tale of "young but everlasting love" (Chicago Sun-Times).There was a time when the world was sweeter....when the women in Beaufort, North Carolina, wore dresses, and the men donned hats.... Every April, when the wind smells of both the sea and lilacs, Landon Carter remembers 1958, his last year at Beaufort High. Landon had dated a girl or two, and even once sworn that he'd been in love. Certainly the last person he thought he'd fall for was Jamie, the shy, almost ethereal daughter of the town's Baptist minister....Jamie, who was destined to show him the depths of the human heart-and the joy and pain of living. The inspiration for this novel came from Nicholas Sparks's sister: her life and her courage. From the internationally bestselling author Nicholas Sparks, comes his most moving story yet....

From the author of A Walk to Remember comes a moving tale of redemption and first love when a rebellious teenager decides to spend the summer with her estranged father in a North Carolina beach town.Seventeen year old Veronica "Ronnie" Miller's life was turned upside-down when her parents divorced and her father moved from New York City to Wilmington, North Carolina. Three years later, she remains angry and alienated from her parents, especially her father...until her mother decides it would be in everyone's best interest if she spent the summer in Wilmington with him. Ronnie's father, a former concert pianist and teacher, is living a quiet life in the beach town, immersed in creating a work of art that will become the centerpiece of a local church.The tale that unfolds is an unforgettable story of love on many levels--first love, love between parents and children -- that demonstrates, as only a Nicholas Sparks novel can, the many ways that love can break our hearts . . . and heal them.

From the author of The Longest Ride and The Return comes a #1 New York Times bestselling novel about the enduring legacy of first love, and the decisions that haunt us forever.1996 was the year that changed everything for Maggie Dawes. Sent away at sixteen to live with an aunt she barely knew in Ocracoke, a remote village on North Carolina’s Outer Banks, she could think only of the friends and family she left behind . . . until she met Bryce Trickett, one of the few teenagers on the island. Handsome, genuine, and newly admitted to West Point, Bryce showed her how much there was to love about the wind-swept beach town—and introduced her to photography, a passion that would define the rest of her life.By 2019, Maggie is a renowned travel photographer. She splits her time between running a successful gallery in New York and photographing remote locations around the world. But this year she is unexpectedly grounded over Christmas, struggling to come to terms with a sobering medical diagnosis. Increasingly dependent on a young assistant, she finds herself becoming close to him.As they count down the last days of the season together, she begins to tell him the story of another Christmas, decades earlier—and the love that set her on a course she never could have imagined.

Apache Spark is a fast, scalable, and flexible open source distributed processing engine for big data systems and is one of the most active open source big data projects to date. In just 24 lessons of one hour or less, Sams Teach Yourself Apache Spark in 24 Hours helps you build practical Big Data solutions that leverage Spark’s amazing speed, scalability, simplicity, and versatility.This book’s straightforward, step-by-step approach shows you how to deploy, program, optimize, manage, integrate, and extend Spark–now, and for years to come. You’ll discover how to create powerful solutions encompassing cloud computing, real-time stream processing, machine learning, and more. Every lesson builds on what you’ve already learned, giving you a rock-solid foundation for real-world success. Whether you are a data analyst, data engineer, data scientist, or data steward, learning Spark will help you to advance your career or embark on a new career in the booming area of Big Data.Learn how to• Discover what Apache Spark does and how it fits into the Big Data landscape• Deploy and run Spark locally or in the cloud• Interact with Spark from the shell• Make the most of the Spark Cluster Architecture• Develop Spark applications with Scala and functional Python• Program with the Spark API, including transformations and actions• Apply practical data engineering/analysis approaches designed for Spark• Use Resilient Distributed Datasets (RDDs) for caching, persistence, and output• Optimize Spark solution performance• Use Spark with SQL (via Spark SQL) and with NoSQL (via Cassandra)• Leverage cutting-edge functional programming techniques• Extend Spark with streaming, R, and Sparkling Water• Start building Spark-based machine learning and graph-processing applications• Explore advanced messaging technologies, including Kafka• Preview and prepare for Spark’s next generation of innovations\nInstructions walk you through common questions, issues, and tasks; Q-and-As, Quizzes, and Exercises build and test your knowledge; "Did You Know?" tips offer insider advice and shortcuts; and "Watch Out!" alerts help you avoid pitfalls. By the time you're finished, you'll be comfortable using Apache Spark to solve a wide spectrum of Big Data problems.

#1 NEW YORK TIMES BESTSELLER * A twist you won't see coming. A love story you'll never forget. From the acclaimed author of The Notebook comes a powerful novel about risking everything for a dream--and whether it's possible to leave the past behind.   We don't always get to choose our paths in life; sometimes they choose us. ONE OF THE BEST BOOKS OF THE YEAR: PopSugar After fleeing an abusive husband with her six-year-old son, Tommie, Beverly is attempting to create a new life for them in a small town off the beaten track. Despite their newfound freedom, Beverly is constantly on guard: she creates a fake backstory, wears a disguise around town, and buries herself in DIY projects to stave off anxiety. But her stress only rises when Tommie insists he'd been hearing someone walking on the roof and calling his name late at night. With money running out and danger seemingly around every corner, she makes a desperate decision that will rewrite everything she knows to be true. . . .   Meanwhile, Colby Mills is on a heart-pounding journey of another kind. A failed musician, he now heads a small family farm in North Carolina. Seeking a rare break from his duties at home, he spontaneously takes a gig playing in a bar in St. Pete Beach, Florida, where he meets Morgan Lee--and his whole life is turned upside-down.   The daughter of affluent Chicago doctors, Morgan has graduated from a prestigious college music program with the ambition to move to Nashville and become a star. Romantically and musically, she and Colby complete each other in a way that neither has ever known.   In the course of a single unforgettable week, two young people will navigate the exhilarating heights and heartbreak of first love. Hundreds of miles away, Beverly will put her love for her young son to the test. And fate will draw all three people together in a web of life-altering connections . . . forcing each to wonder whether the dream of a better life can ever survive the weight of the past.

Gain expertise in processing and storing data by using advanced techniques with Apache SparkAbout This Book\nExplore the integration of Apache Spark with third party applications such as H20, Databricks and Titan\nEvaluate how Cassandra and Hbase can be used for storage\nAn advanced guide with a combination of instructions and practical examples to extend the most up-to date Spark functionalities\nWho This Book Is ForIf you are a developer with some experience with Spark and want to strengthen your knowledge of how to get around in the world of Spark, then this book is ideal for you. Basic knowledge of Linux, Hadoop and Spark is assumed. Reasonable knowledge of Scala is expected.What You Will Learn\nExtend the tools available for processing and storage\nExamine clustering and classification using MLlib\nDiscover Spark stream processing via Flume, HDFS\nCreate a schema in Spark SQL, and learn how a Spark schema can be populated with data\nStudy Spark based graph processing using Spark GraphX\nCombine Spark with H20 and deep learning and learn why it is useful\nEvaluate how graph storage works with Apache Spark, Titan, HBase and Cassandra\nUse Apache Spark in the cloud with Databricks and AWS\nIn DetailApache Spark is an in-memory cluster based parallel processing system that provides a wide range of functionality like graph processing, machine learning, stream processing and SQL. It operates at unprecedented speeds, is easy to use and offers a rich set of data transformations.\nThis book aims to take your limited knowledge of Spark to the next level by teaching you how to expand Spark functionality. The book commences with an overview of the Spark eco-system. You will learn how to use MLlib to create a fully working neural net for handwriting recognition. You will then discover how stream processing can be tuned for optimal performance and to ensure parallel processing. The book extends to show how to incorporate H20 for machine learning, Titan for graph based storage, Databricks for cloud-based Spark. Intermediate Scala based code examples are provided for Apache Spark module processing in a CentOS Linux and Databricks cloud environment.Style and approachThis book is an extensive guide to Apache Spark modules and tools and shows how Spark's functionality can be extended for real-time processing and storage with worked examples.

Speed up the design and implementation of deep learning solutions using Apache Spark Key Features Explore the world of distributed deep learning with Apache Spark Train neural networks with deep learning libraries such as BigDL and TensorFlow Develop Spark deep learning applications to intelligently handle large and complex datasets Book Description Deep learning is a subset of machine learning where datasets with several layers of complexity can be processed. Hands-On Deep Learning with Apache Spark addresses the sheer complexity of technical and analytical parts and the speed at which deep learning solutions can be implemented on Apache Spark. The book starts with the fundamentals of Apache Spark and deep learning. You will set up Spark for deep learning, learn principles of distributed modeling, and understand different types of neural nets. You will then implement deep learning models, such as convolutional neural networks (CNNs), recurrent neural networks (RNNs), and long short-term memory (LSTM) on Spark. As you progress through the book, you will gain hands-on experience of what it takes to understand the complex datasets you are dealing with. During the course of this book, you will use popular deep learning frameworks, such as TensorFlow, Deeplearning4j, and Keras to train your distributed models. By the end of this book, you'll have gained experience with the implementation of your models on a variety of use cases. What you will learn Understand the basics of deep learning Set up Apache Spark for deep learning Understand the principles of distribution modeling and different types of neural networks Obtain an understanding of deep learning algorithms Discover textual analysis and deep learning with Spark Use popular deep learning frameworks, such as Deeplearning4j, TensorFlow, and Keras Explore popular deep learning algorithms Who this book is for If you are a Scala developer, data scientist, or data analyst who wants to learn how to use Spark for implementing efficient deep learning models, Hands-On Deep Learning with Apache Spark is for you. Knowledge of the core machine learning concepts and some exposure to Spark will be helpful.

A solution-based guide to put your deep learning models into production with the power of Apache SparkKey Features\n Discover practical recipes for distributed deep learning with Apache Spark\n Learn to use libraries such as Keras and TensorFlow \n Solve problems in order to train your deep learning models on Apache Spark\nBook DescriptionWith deep learning gaining rapid mainstream adoption in modern-day industries, organizations are looking for ways to unite popular big data tools with highly efficient deep learning libraries. As a result, this will help deep learning models train with higher efficiency and speed. \nWith the help of the Apache Spark Deep Learning Cookbook, you’ll work through specific recipes to generate outcomes for deep learning algorithms, without getting bogged down in theory. From setting up Apache Spark for deep learning to implementing types of neural net, this book tackles both common and not so common problems to perform deep learning on a distributed environment. In addition to this, you’ll get access to deep learning code within Spark that can be reused to answer similar problems or tweaked to answer slightly different problems. You will also learn how to stream and cluster your data with Spark. Once you have got to grips with the basics, you’ll explore how to implement and deploy deep learning models, such as Convolutional Neural Networks (CNN) and Recurrent Neural Networks (RNN) in Spark, using popular libraries such as TensorFlow and Keras.\nBy the end of the book, you'll have the expertise to train and deploy efficient deep learning models on Apache Spark.What you will learn\n Set up a fully functional Spark environment\n Understand practical machine learning and deep learning concepts \n Apply built-in machine learning libraries within Spark\n Explore libraries that are compatible with TensorFlow and Keras\n Explore NLP models such as Word2vec and TF-IDF on Spark\n Organize dataframes for deep learning evaluation\n Apply testing and training modeling to ensure accuracy\n Access readily available code that may be reusable\nWho this book is forIf you’re looking for a practical and highly useful resource for implementing efficiently distributed deep learning models with Apache Spark, then the Apache Spark Deep Learning Cookbook is for you. Knowledge of the core machine learning concepts and a basic understanding of the Apache Spark framework is required to get the best out of this book. Additionally, some programming knowledge in Python is a plus.Table of Contents\nSetting Up Spark for Deep Learning Development\nCreating a Neural Network in Spark\nPain Points of Convolutional Neural Networks\nPain Points of Recurrent Neural Networks\nPredicting Fire Department Calls with Spark ML\nUsing LSTMs in Generative Networks\nNatural Language Processing with TF-IDF\n Real Estate Value Prediction using XGBoost\nPredicting Apple Stock Market Cost with LSTM\nFace Recognition using Deep Convolutional Networks\nCreating and Visualizing Word Vectors Using Word2Vec\n Creating a Movie Recommendation Engine with Keras\nImage Classification with TensorFlow on Spark \n

Simplify machine learning model implementations with SparkAbout This Book\nSolve the day-to-day problems of data science with Spark\nThis unique cookbook consists of exciting and intuitive numerical recipes\nOptimize your work by acquiring, cleaning, analyzing, predicting, and visualizing your data\nWho This Book Is ForThis book is for Scala developers with a fairly good exposure to and understanding of machine learning techniques, but lack practical implementations with Spark. A solid knowledge of machine learning algorithms is assumed, as well as hands-on experience of implementing ML algorithms with Scala. However, you do not need to be acquainted with the Spark ML libraries and ecosystem.What You Will Learn\nGet to know how Scala and Spark go hand-in-hand for developers when developing ML systems with Spark\nBuild a recommendation engine that scales with Spark\nFind out how to build unsupervised clustering systems to classify data in Spark\nBuild machine learning systems with the Decision Tree and Ensemble models in Spark\nDeal with the curse of high-dimensionality in big data using Spark\nImplement Text analytics for Search Engines in Spark\nStreaming Machine Learning System implementation using Spark\nIn DetailMachine learning aims to extract knowledge from data, relying on fundamental concepts in computer science, statistics, probability, and optimization. Learning about algorithms enables a wide range of applications, from everyday tasks such as product recommendations and spam filtering to cutting edge applications such as self-driving cars and personalized medicine. You will gain hands-on experience of applying these principles using Apache Spark, a resilient cluster computing system well suited for large-scale machine learning tasks.\nThis book begins with a quick overview of setting up the necessary IDEs to facilitate the execution of code examples that will be covered in various chapters. It also highlights some key issues developers face while working with machine learning algorithms on the Spark platform. We progress by uncovering the various Spark APIs and the implementation of ML algorithms with developing classification systems, recommendation engines, text analytics, clustering, and learning systems. Toward the final chapters, we’ll focus on building high-end applications and explain various unsupervised methodologies and challenges to tackle when implementing with big data ML systems.Style and approachThis book is packed with intuitive recipes supported with line-by-line explanations to help you understand how to optimize your work flow and resolve problems when working with complex data modeling tasks and predictive algorithms. This is a valuable resource for data scientists and those working on large scale data projects.

Perform real-time analytics using Spark in a fast, distributed, and scalable way About This Book\nDevelop a machine learning system with Spark's MLlib and scalable algorithms\nDeploy Spark jobs to various clusters such as Mesos, EC2, Chef, YARN, EMR, and so on\nThis is a step-by-step tutorial that unleashes the power of Spark and its latest features\nWho This Book Is ForFast Data Processing with Spark - Second Edition is for software developers who want to learn how to write distributed programs with Spark. It will help developers who have had problems that were too big to be dealt with on a single computer. No previous experience with distributed programming is necessary. This book assumes knowledge of either Java, Scala, or Python.What You Will Learn\nInstall and set up Spark on your cluster Prototype distributed applications with Spark's interactive shell Learn different ways to interact with Spark's distributed representation of data (RDDs) Query Spark with a SQL-like query syntax Effectively test your distributed software Recognize how Spark works with big data Implement machine learning systems with highly scalable algorithms In DetailSpark is a framework used for writing fast, distributed programs. Spark solves similar problems as Hadoop MapReduce does, but with a fast in-memory approach and a clean functional style API. With its ability to integrate with Hadoop and built-in tools for interactive query analysis (Spark SQL), large-scale graph processing and analysis (GraphX), and real-time analysis (Spark Streaming), it can be interactively used to quickly process and query big datasets.\nFast Data Processing with Spark - Second Edition covers how to write distributed programs with Spark. The book will guide you through every step required to write effective distributed programs from setting up your cluster and interactively exploring the API to developing analytics applications and tuning them for your purposes.