《白光》是现代文学家鲁迅于1922年创作的短篇小说，作者通过讲述在科举考试中一个屡屡落第的文人陈士成，听信祖宗传言，受白光的启示在院子里挖银子未果，精神迷幻，到大山里寻宝却坠湖而死的故事，批判了封建社会病态的科考制度，揭示了十年苦读反而无用的读书人的悲惨命运。全书为日文版。难词标注假名，供日语学习者学习使用。

《幸福的家庭》主要讲的是在旧社会一知识分子，为赚稿费养家糊口，于是便打算投稿写一篇符合大众口味的文章。以描写知识分子想象中的幸福家庭的模样及生活方式。知识分子虚构了一个接受了民主思想的恩爱夫妻，过着浪漫、幸福的婚姻生活。与虚构小说情节鲜明对比的是：该知识分子生活困顿，过着为三餐温饱、柴米油盐而烦恼的生活。全书为日文版。难词标注假名，供日语学习者学习使用。

本故事为鲁迅创作的作品之一。村里撑船的七斤，革命时进城，被人剪去了辫子。这天他在城里的咸亨酒店听说皇帝坐了龙庭，要辫子，这消息让他烦心，更让他妻子惶恐。跟七斤有过节的赵七爷特意来恐吓七斤一家，说没了辫子就是要杀头。十多天后，七斤夫妇看出了破绽，于是七斤渐渐在村里恢复了被尊重的地位，一家的生活也回到常态。全书为日文版。难词标注假名，供日语学习者学习使用。

本故事为鲁迅创作的作品之一。这篇小说取材于女娲造人和补天的神话。小说开篇写女娲从梦中惊醒，烦闷、懊恼，自然界则是一片春回大地的绚烂景象。和风吹拂，女娲百无聊赖，心神不安，青春焕发，精力饱满而无处发泄。她走向海边，无意识捏弄软泥，于是创造了人。女娲因生命力受压抑而发挥了劳动创造精神，创造了人类，补好了崩裂的天。这是作者对封建思想意识礼教道德的勇敢挑战和彻底否定，体现了强烈的反封建精神。全书为日文版。难词标注假名，供日语学习者学习使用。

The first entry in a clever, lighthearted mystery series set in modern Provence—a delightful blend of Agatha Christie and Peter Mayle—featuring the irrepressible Penelope Kite, a young-at-heart divorcee with a knack for stumbling across dead bodies.It’s love at first sight when Penelope Kite sees Le Chant d’Eau—The Song of Water—the stone farmhouse tucked high in the hills above the Luberon valley, complete with a garden, swimming pool, and sweeping mountain vistas. For years, Penelope put her unfaithful ex-husband and her ungrateful stepchildren first. Since taking early retirement from her job in forensics at the Home Office in England, she’s been an unpaid babysitter and chauffeur for her grandchildren. Now, she’s going to start living for herself. Though her dream house needs major renovations, Penelope impulsively buys the property and moves to St. Merlot. But Penelope’s daydreams of an adventurous life in Provence didn’t include finding a corpse floating face down in her swimming pool. The discovery of the dead man plunges her headlong into a Provençal stew of intrigue and lingering resentments simmering beneath the deceptively sunny village. Having worked in the forensics office, Penelope knows a thing or two about murder investigations. To find answers, she must carefully navigate between her seemingly ubiquitous, supercilious (and enviably chic) estate agent, the disdainful chief of police, and the devilishly handsome mayor—even as she finds herself tempted by all the delicacies the region has to offer. Thank goodness her old friend Frankie is just a flight away . . . and that Penelope is not quite as naïve as her new neighbors in St. Merlot believe.Set against the exquisite backdrop of Provence, steeped in history, atmosphere, and secrets, Death in Provence introduces an irresistible heroine and a delightful new mystery series.

The intriguing futuristic dystopian story begun with The Lost Puzzler continues in this expansive speculative science fiction adventure.There is nothing out of the ordinary in waking up . . . unless you’re dead.Sent on a dangerous mission with little hope of succeeding, the man known as “Twinkle Eyes” has beaten the odds and found the key that could save civilization: Rafik, a teenage boy with the power to unlock the invaluable Tarakan technology that can restart their world. But the world might not be ready for what is unleashed, and now Twinkle Eyes must find a needle in a haystack in order to save himself . . . and perhaps the world.This time, though, he will not go it alone. And while his companions—from the fiery Vincha to the laconic Galinak—have their own motivations, each will be vital in solving the last grand puzzle. One that could bring prosperity and progress to the world or destroy humanity’s last hope for ascension.Now, a lone assassin from another era, two old friends, a dead man, a ruthless rogue mercenary, and a vicious warlord are all hunting for the ultimate prize. But what will happen when the final secret is unlocked, and technology long since buried once again finds its way into the hands of mankind?

Now a National Bestseller!What if the Russians really are colluding with Americans...on the left?#1 New York Times bestselling author Newt Gingrich makes his return to political fiction with this rollicking tale of high-stakes international intrigue—the first book in a new, contemporary series, filled with adventure, betrayal, and politics—that captures the tensions and divides of America and the world today. Valerie Mayberry is the FBI’s counterintelligence expert on domestic terrorism.Brett Garrett is a dishonorably discharged ex-Navy SEAL, now a gun for hire, working as a security contractor in Eastern Europe. When a high ranking Kremlin official must be smuggled out of Russia, Mayberry and Garrett are thrown together to exfiltrate him and preempt a deadly poisonous strike.As these unlikely partners work to protect their human asset, their mission is threatened by domestic politics: leftist protests, congressional infighting, and a culture riven by hatred. Collusion raises many of the most significant issues facing America in real life today. How big a threat is Russia? Are American leftist activists susceptible to influence from abroad? How far will our enemies go to disrupt our politics and weaken the nation? Can we trust the media to differentiate between the good guys and the bad guys? Newt Gingrich and Pete Earley have entertained and educated readers with three previous works. From its explosive opening through several twists and turns to its heart-stopping end, Collusion is their most timely and powerful novel yet.

Fans of Danielle Paige, Marissa Meyer, and Alex Flinn will devour New York Times bestselling author Meagan Spooner’s next fierce fairy tale-inspired story, which Illuminae author Amie Kaufman calls “a kick-ass, gender-flipped feminist retelling.”Robin of Locksley is dead. Maid Marian doesn’t know how she’ll go on, but the people of Locksley town, persecuted by the Sheriff of Nottingham, need a protector. And the dreadful Guy of Gisborne, the Sheriff’s right hand, wishes to step into Robin’s shoes as Lord of Locksley and Marian’s fiancé. Who is there to stop them? Marian never meant to tread in Robin’s footsteps—never intended to stand as a beacon of hope to those awaiting his triumphant return. But with a sweep of his green cloak and the flash of her sword, Marian makes the choice to become her own hero: Robin Hood.

Discover interesting recipes to help you understand the concepts of object detection, image processing, and facial detection Key Features * Explore the latest features and APIs in OpenCV 4 and build computer vision algorithms * Develop effective, robust, and fail-safe vision for your applications * Build computer vision algorithms with machine learning capabilities Book Description OpenCV is an image and video processing library used for all types of image and video analysis. Throughout the book, you'll work through recipes that implement a variety of tasks, such as facial recognition and detection. With 70 self-contained tutorials, this book examines common pain points and best practices for computer vision (CV) developers. Each recipe addresses a specific problem and offers a proven, best-practice solution with insights into how it works, so that you can copy the code and configuration files and modify them to suit your needs. This book begins by setting up OpenCV, and explains how to manipulate pixels. You'll understand how you can process images with classes and count pixels with histograms. You'll also learn detecting, describing, and matching interest points. As you advance through the chapters, you'll get to grips with estimating projective relations in images, reconstructing 3D scenes, processing video sequences, and tracking visual motion. In the final chapters, you'll cover deep learning concepts such as face and object detection. By the end of the book, you'll be able to confidently implement a range to computer vision algorithms to meet the technical requirements of your complex CV projects What you will learn * Install and create a program using the OpenCV library * Segment images into homogenous regions and extract meaningful objects * Apply image filters to enhance image content * Exploit image geometry to relay different views of a pictured scene * Calibrate the camera from different image observations * Detect people and objects in images using machine learning techniques * Reconstruct a 3D scene from images * Explore face detection using deep learning Who this book is for If you’re a CV developer or professional who already uses or would like to use OpenCV for building computer vision software, this book is for you. You’ll also find this book useful if you’re a C++ programmer looking to extend your computer vision skillset by learning OpenCV.

Learn dynamic programming with Julia to build apps for data analysis, visualization, machine learning, and the web Key Features * Leverage Julia's high speed and efficiency to build fast, efficient applications * Perform supervised and unsupervised machine learning and time series analysis * Tackle problems concurrently and in a distributed environment Book Description Julia offers the high productivity and ease of use of Python and R with the lightning-fast speed of C++. There’s never been a better time to learn this language, thanks to its large-scale adoption across a wide range of domains, including fintech, biotech and artificial intelligence (AI). You will begin by learning how to set up a running Julia platform, before exploring its various built-in types. This Learning Path walks you through two important collection types: arrays and matrices. You’ll be taken through how type conversions and promotions work, and in further chapters you'll study how Julia interacts with operating systems and other languages. You’ll also learn about the use of macros, what makes Julia suitable for numerical and scientific computing, and how to run external programs. Once you have grasped the basics, this Learning Path goes on to how to analyze the Iris dataset using DataFrames. While building a web scraper and a web app, you’ll explore the use of functions, methods, and multiple dispatches. In the final chapters, you'll delve into machine learning, where you'll build a book recommender system. By the end of this Learning Path, you’ll be well versed with Julia and have the skills you need to leverage its high speed and efficiency for your applications. This Learning Path includes content from the following Packt products: * Julia 1.0 Programming - Second Edition by Ivo Balbaert * Julia Programming Projects by Adrian Salceanu What you will learn * Create your own types to extend the built-in type system * Visualize your data in Julia with plotting packages * Explore the use of built-in macros for testing and debugging * Integrate Julia with other languages such as C, Python, and MATLAB * Analyze and manipulate datasets using Julia and DataFrames * Develop and run a web app using Julia and the HTTP package * Build a recommendation system using supervised machine learning Who this book is for If you are a statistician or data scientist who wants a quick course in the Julia programming language while building big data applications, this Learning Path is for you. Basic knowledge of mathematics and programming is a must.

Leverage the power of Python and statistical modeling techniques for building accurate predictive models Key Features * Get introduced to Python's rich suite of libraries for statistical modeling * Implement regression, clustering and train neural networks from scratch * Includes real-world examples on training end-to-end machine learning systems in Python Book Description Python's ease of use and multi-purpose nature has led it to become the choice of tool for many data scientists and machine learning developers today. Its rich libraries are widely used for data analysis, and more importantly, for building state-of-the-art predictive models. This book takes you through an exciting journey, of using these libraries to implement effective statistical models for predictive analytics. You’ll start by diving into classical statistical analysis, where you will learn to compute descriptive statistics using pandas. You will look at supervised learning, where you will explore the principles of machine learning and train different machine learning models from scratch. You will also work with binary prediction models, such as data classification using k-nearest neighbors, decision trees, and random forests. This book also covers algorithms for regression analysis, such as ridge and lasso regression, and their implementation in Python. You will also learn how neural networks can be trained and deployed for more accurate predictions, and which Python libraries can be used to implement them. By the end of this book, you will have all the knowledge you need to design, build, and deploy enterprise-grade statistical models for machine learning using Python and its rich ecosystem of libraries for predictive analytics. What you will learn * Understand the importance of statistical modeling * Learn about the various Python packages for statistical analysis * Implement algorithms such as Naive Bayes, random forests, and more * Build predictive models from scratch using Python's scikit-learn library * Implement regression analysis and clustering * Learn how to train a neural network in Python Who this book is for If you are a data scientist, a statistician or a machine learning developer looking to train and deploy effective machine learning models using popular statistical techniques, then this book is for you. Knowledge of Python programming is required to get the most out of this book.

Design and implement professional-level programs by leveraging modern data structures and algorithms in Rust Key Features * Improve your productivity by writing more simple and easy code in Rust * Discover the functional and reactive implementations of traditional data structures * Delve into new domains of Rust, including WebAssembly, networking, and command-line tools Book Description Rust is a powerful language with a rare combination of safety, speed, and zero-cost abstractions. This Learning Path is filled with clear and simple explanations of its features along with real-world examples, demonstrating how you can build robust, scalable, and reliable programs. You’ll get started with an introduction to Rust data structures, algorithms, and essential language constructs. Next, you will understand how to store data using linked lists, arrays, stacks, and queues. You’ll also learn to implement sorting and searching algorithms, such as Brute Force algorithms, Greedy algorithms, Dynamic Programming, and Backtracking. As you progress, you’ll pick up on using Rust for systems programming, network programming, and the web. You’ll then move on to discover a variety of techniques, right from writing memory-safe code, to building idiomatic Rust libraries, and even advanced macros. By the end of this Learning Path, you’ll be able to implement Rust for enterprise projects, writing better tests and documentation, designing for performance, and creating idiomatic Rust code. This Learning Path includes content from the following Packt products: * Mastering Rust - Second Edition by Rahul Sharma and Vesa Kaihlavirta * Hands-On Data Structures and Algorithms with Rust by Claus Matzinger What you will learn * Design and implement complex data structures in Rust * Create and use well-tested and reusable components with Rust * Understand the basics of multithreaded programming and advanced algorithm design * Explore application profiling based on benchmarking and testing * Study and apply best practices and strategies in error handling * Create efficient web applications with the Actix-web framework * Use Diesel for type-safe database interactions in your web application Who this book is for If you are already familiar with an imperative language and now want to progress from being a beginner to an intermediate-level Rust programmer, this Learning Path is for you. Developers who are already familiar with Rust and want to delve deeper into the essential data structures and algorithms in Rust will also find this Learning Path useful.

Teach your machine to think for itself! Key Features * Delve into supervised learning and grasp how a machine learns from data * Implement popular machine learning algorithms from scratch, developing a deep understanding along the way * Explore some of the most popular scientific and mathematical libraries in the Python language Book Description Supervised machine learning is used in a wide range of sectors (such as finance, online advertising, and analytics) because it allows you to train your system to make pricing predictions, campaign adjustments, customer recommendations, and much more while the system self-adjusts and makes decisions on its own. As a result, it's crucial to know how a machine “learns” under the hood. This book will guide you through the implementation and nuances of many popular supervised machine learning algorithms while facilitating a deep understanding along the way. You’ll embark on this journey with a quick overview and see how supervised machine learning differs from unsupervised learning. Next, we explore parametric models such as linear and logistic regression, non-parametric methods such as decision trees, and various clustering techniques to facilitate decision-making and predictions. As we proceed, you'll work hands-on with recommender systems, which are widely used by online companies to increase user interaction and enrich shopping potential. Finally, you’ll wrap up with a brief foray into neural networks and transfer learning. By the end of this book, you’ll be equipped with hands-on techniques and will have gained the practical know-how you need to quickly and powerfully apply algorithms to new problems. What you will learn * Crack how a machine learns a concept and generalize its understanding to new data * Uncover the fundamental differences between parametric and non-parametric models * Implement and grok several well-known supervised learning algorithms from scratch * Work with models in domains such as ecommerce and marketing * Expand your expertise and use various algorithms such as regression, decision trees, and clustering * Build your own models capable of making predictions * Delve into the most popular approaches in deep learning such as transfer learning and neural networks Who this book is for This book is for aspiring machine learning developers who want to get started with supervised learning. Intermediate knowledge of Python programming—and some fundamental knowledge of supervised learning—are expected.

Design clever algorithms that can uncover interesting structures and hidden relationships in unstructured, unlabeled data Key Features * Learn how to select the most suitable Python library to solve your problem * Compare k-Nearest Neighbor (k-NN) and non-parametric methods and decide when to use them * Delve into the applications of neural networks using real-world datasets Book Description Unsupervised learning is a useful and practical solution in situations where labeled data is not available. Applied Unsupervised Learning with Python guides you on the best practices for using unsupervised learning techniques in tandem with Python libraries and extracting meaningful information from unstructured data. The course begins by explaining how basic clustering works to find similar data points in a set. Once you are well versed with the k-means algorithm and how it operates, you’ll learn what dimensionality reduction is and where to apply it. As you progress, you’ll learn various neural network techniques and how they can improve your model. While studying the applications of unsupervised learning, you will also understand how to mine topics that are trending on Twitter and Facebook and build a news recommendation engine for users. You will complete the course by challenging yourself through various interesting activities such as performing a Market Basket Analysis and identifying relationships between different merchandises. By the end of this course, you will have the skills you need to confidently build your own models using Python. What you will learn * Understand the basics and importance of clustering * Build k-means, hierarchical, and DBSCAN clustering algorithms from scratch with built-in packages * Explore dimensionality reduction and its applications * Use scikit-learn (sklearn) to implement and analyse principal component analysis (PCA)on the Iris dataset * Employ Keras to build autoencoder models for the CIFAR-10 dataset * Apply the Apriori algorithm with machine learning extensions (Mlxtend) to study transaction data Who this book is for This course is designed for developers, data scientists, and machine learning enthusiasts who are interested in unsupervised learning. Some familiarity with Python programming along with basic knowledge of mathematical concepts including exponents, square roots, means, and medians will be beneficial.

Delve into the world of Kotlin and learn to build powerful Android and web applications Key Features * Learn the fundamentals of Kotlin to write high-quality code * Test and debug your applications with the different unit testing frameworks in Kotlin * Explore Kotlin's interesting features such as null safety, reflection, and annotations Book Description Kotlin is a general-purpose programming language used for developing cross-platform applications. Complete with a comprehensive introduction and projects covering the full set of Kotlin programming features, this book will take you through the fundamentals of Kotlin and get you up to speed in no time. Learn Kotlin Programming covers the installation, tools, and how to write basic programs in Kotlin. You'll learn how to implement object-oriented programming in Kotlin and easily reuse your program or parts of it. The book explains DSL construction, serialization, null safety aspects, and type parameterization to help you build robust apps. You'll learn how to destructure expressions and write your own. You'll then get to grips with building scalable apps by exploring advanced topics such as testing, concurrency, microservices, coroutines, and Kotlin DSL builders. Furthermore, you'll be introduced to the kotlinx.serialization framework, which is used to persist objects in JSON, Protobuf, and other formats. By the end of this book, you'll be well versed with all the new features in Kotlin and will be able to build robust applications skillfully. What you will learn * Explore the latest Kotlin features in order to write structured and readable object-oriented code * Get to grips with using lambdas and higher-order functions * Write unit tests and integrate Kotlin with Java code * Create real-world apps in Kotlin in the microservices style * Use Kotlin extensions with the Java collections library * Uncover destructuring expressions and find out how to write your own * Understand how Java-nullable code can be integrated with Kotlin features Who this book is for If you’re a beginner or intermediate programmer who wants to learn Kotlin to build applications, this book is for you. You’ll also find this book useful if you’re a Java developer interested in switching to Kotlin.

Explore the aspects of financial modeling with the help of clear and easy-to-follow instructions and a variety of Excel features, functions, and productivity tips Key Features * A non data professionals guide to exploring Excel's financial functions and pivot tables * Learn to prepare various models for income and cash flow statements, and balance sheets * Learn to perform valuations and identify growth drivers with real-world case studies Book Description 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 examines various definitions and relates them to the key features of financial modeling with the help of Excel. This book will help you understand financial modeling concepts using Excel, and 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 of Excel 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, along with best practices and practical use cases. By the end of this book, you will have examined the data from various use cases, and you will have the skills you need to build financial models to extract the information required to make informed business decisions. What you will learn * Identify the growth drivers derived from processing historical data in Excel * Use discounted cash flow (DCF) for efficient investment analysis * Build a financial model by projecting balance sheets, profit, and loss * Apply a Monte Carlo simulation to derive key assumptions for your financial model * Prepare detailed asset and debt schedule models in Excel * Discover the latest and advanced features of Excel 2019 * Calculate profitability ratios using various profit parameters Who this book is for This book is for data professionals, analysts, traders, business owners, and students, who want to implement and develop a high in-demand skill of financial modeling in their finance, analysis, trading, and valuation work. This book will also help individuals that have and don't have any experience in data and stats, to get started with building financial models. The book assumes working knowledge with Excel.

A collection of in-depth conversations with leading developer advocates that reveal the world of developer relations today Key Features * Top developer advocates reveal the work they’re doing at the center of their tech communities and the impact their advocacy is having on the tech industry as a whole * Discover the best practices of developer advocacy and get the inside story on working at some of the world’s largest tech companies * Features contributions from noted developer advocates, including Scott Hanselman, Sally Eaves, Venkat Subramaniam, Jono Bacon, Ted Neward, and more Book Description What exactly is a developer advocate, and how do they connect developers and companies around the world? Why is the area of developer relations set to explode? Can anybody with a passion for tech become a developer advocate? What are the keys to success on a global scale? How does a developer advocate maintain authenticity when balancing the needs of their company and their tech community? What are the hot topics in areas including Java, JavaScript, "tech for good," artificial intelligence, blockchain, the cloud, and open source? These are just a few of the questions addressed by developer advocate and author Geertjan Wielenga in Developer, Advocate!. 32 of the industry's most prominent developer advocates, from companies including Oracle, Microsoft, Google, and Amazon, open up about what it's like to turn a lifelong passion for knowledge sharing about tech into a rewarding career. These advocates run the gamut from working at large software vendors to small start-ups, along with independent developer advocates who work within organizations or for themselves. In Developer, Advocate!, readers will see how developer advocates are actively changing the world, not only for developers, but for individuals and companies navigating the fast-changing tech landscape. More importantly, Developer, Advocate! serves as a rallying cry to inspire and motivate tech enthusiasts and burgeoning developer advocates to get started and take their first steps within their tech community. What you will learn * Discover how developer advocates are putting developer interests at the heart of the software industry in companies including Microsoft and Google * Gain the confidence to use your voice in the tech community * Immerse yourself in developer advocacy techniques * Understand and overcome the challenges and obstacles facing developer advocates today * Hear predictions from the people at the cutting edge of tech * Explore your career options in developer advocacy Who this book is for Anybody interested in developer advocacy, the impact it is having, and how to build developer advocacy capabilities

“Reading Scratched gave me the feeling of standing very close to a blazing fire. It is that brilliant, that intense, and one of the finest explorations I know of what it means to be a woman and an artist.”—Sigrid Nunez, author of The Friend and Winner of the National Book Award for FictionIn a bold and brilliant memoir that reinvents the form, the acclaimed author of the novel Museum Pieces and the collection Mendocino Fire explores the ferocious desire for perfection which has shaped her writing life as well as her rich, dramatic, and constantly surprising personal life.Scratched is an intimate account of the uses a child, and the adult she becomes, will find for perfectionism and the role it will play in every part of her life. Elizabeth Tallent’s story begins in a hospital in mid-1950s suburban Washington, D.C., when her mother refuses to hold her newborn daughter, shocking behavior that baffles the nurses. Imagining her own mother’s perfectionist ideal at this critical moment, Elizabeth moves back and forth in time, juxtaposing moments in the past with the present in this innovative and spellbinding narrative.Elizabeth traces her journey from her early years in which she perceived herself as “the child whose flaws let disaster into an otherwise perfect family,” to her adulthood, when perfectionism came to affect everything. In the decade between 27 and 37, she publishes five literary books with Knopf and her short stories appear in The New Yorker. But this extraordinary start to her career is followed by twenty-two years of silence. She wrote, or rather published, nothing at all. Why? Scratched is the remarkable response to that question.Elizabeth’s early publications secure her a coveted teaching job at Stanford University. As she toggles between Palo Alto and the Mendocino coast where she lives, raises her son Gabriel, and pursues an important psychoanalysis, Elizabeth grapples with the perfectionism that has always been home to her. Eventually, she finds love and acceptance in the most unlikely place, and finally accepts an “as is” relationship with herself and others. Her final triumph is the writing of this memoir, filled with wit, humor, and heart, and unlike any other you will read. Scratched is a brave book that repeatedly searches for the emotional truth beneath the conventional surface of existence.

前《星期日泰晤士报》专栏作家多利 · 奥尔德顿处女作，这本回忆录讲述了成长、变老过程中渐渐学会如何处理工作、爱情、友谊、得失。作者真诚、幽默、充满智慧，她细腻和极具洞察力的描述会引起各个年龄段女性的共鸣，仿佛在看真实版的《BJ单身日记》 "There is no writer quite like Dolly Alderton working today and very soon the world will know it.”--Lisa Taddeo, author of #1 New York Times bestseller Three Women“Dolly Alderton has always been a sparkling Roman candle of talent. She is funny, smart, and explosively engaged in the wonders and weirdness of the world. But what makes this memoir more than mere entertainment is the mature and sophisticated evolution that Alderton describes in these pages. It’s a beautifully told journey and a thoughtful, important book. I loved it.”--Elizabeth Gilbert, New York Times bestselling author of Eat, Pray, Love and City of GirlsThe wildly funny, occasionally heartbreaking internationally bestselling memoir about growing up, growing older, and learning to navigate friendships, jobs, loss, and love along the rideWhen it comes to the trials and triumphs of becoming an adult, journalist and former Sunday Times columnist Dolly Alderton has seen and tried it all. In her memoir, she vividly recounts falling in love, finding a job, getting drunk, getting dumped, realizing that Ivan from the corner shop might just be the only reliable man in her life, and that absolutely no one can ever compare to her best girlfriends. Everything I Know About Love is about bad dates, good friends and—above all else— realizing that you are enough. Glittering with wit and insight, heart and humor, Dolly Alderton’s unforgettable debut weaves together personal stories, satirical observations, a series of lists, recipes, and other vignettes that will strike a chord of recognition with women of every age—making you want to pick up the phone and tell your best friends all about it. Like Bridget Jones’ Diary but all true, Everything I Know About Love is about the struggles of early adulthood in all its terrifying and hopeful uncertainty.

Twenty-five beautifully written stories, penned in exile, evocatively depicting life on a manor in feudal Russia and examining the conflicts between serfs and landlordsA Sportsman’s Notebook, Ivan Turgenev’s first literary masterpiece, is a sweeping portrayal of the magnificent nineteenth–century Russian countryside and the harsh lives of those who inhabited it. In a powerful and gripping series of sketches, a hunter wanders through the vast landscape of steppe and forest in search of game, encountering a varied cast of peasants, landlords, bailiffs, overseers, horse traders, and merchants. He witnesses both feudal tyranny and the submission of the tyrannized, against a backdrop of the sublime and pitiless terrain of rural Russia.These exquisitely rendered stories, now with a stirring introduction from Daniyal Mueenuddin, were not only universally popular with the reading public but, through the influence they exerted on important members of the Tsarist bureaucracy, contributed to the major political event of mid–nineteenth–century Russia: the Great Emancipation of the serfs in 1861. Rarely has a book that offers such undiluted literary pleasure also been so strong a force for significant social change, one that continues to speak to readers centuries later.

An engrossing debut novel that cannily reimagines the extraordinary life and mysterious death of bohemian Georgetown socialite Mary Pinchot Meyer— secret lover of JFK, ex-wife of a CIA chief, sexual adventurer, LSD explorer and early feminist living by her own rules.She was a longtime lover of JFK.She was the ex-wife of a CIA chief. She was the sister-in-law of the Washington Post’s Ben Bradlee.She believed in mind expansion and took LSD with Timothy Leary. She was a painter, a socialite and a Bohemian in Georgetown during the Cold War.And she ended up dead in an unsolved murder a year after JFK’s assassination.The diary she kept was never found.Until now. . . .