The Girl from the Honeysuckle Farm by Jessica Steele Phinn Hawkins isn't fooled by eligible bachelor Ty Allardyce’s good-looks. Ty is the hot-shot London financier who bought her beloved Honeysuckle Farm. So imagine Phinn’s horror when Ty offers her a much-needed home and job – at his manor! One Dance with the Cowboy by Donna Alward Cool-headed cowboy Drew Laramie left Larch Valley, promising Jen O’Keefe he’d return. When he didn't, she moved on. Now the childhood sweetheart Jen had stopped waiting for is back! And he’s asking her for one last dance...

Cinderella on His Doorstep：AND Accidentally Expecting (Mills & Boon Romance)

Ever since Fiona Donner breezed into Brent MacKay's office with her sunny smile, bouncy enthusiasm and infectious laughter she's turned his ordered world topsy-turvy.The attraction zings between them, and Brent believes that Fiona may be the woman to finally release his fears--and the secret he's lived with his whole life. "Only then can he put a sparkly ring on her finger..."

HIS MAJESTY REQUESTS YOUR COMPANY FOR BANQUETS, BALLROOM DANCING ... AND A LITTLE BOMBSHELL? Stepping into Prince Aleks's turreted castle is like going back in time. Five years ago he didn't tell Sara he was a prince, now he's wearing a crown! Sara once loved Aleks with all her heart, and she feels like the center of his world again. Yet she can't help feeling that there are more secrets to be revealed ...

He needs a cowgirl to show him the ropes... Injured out of the army, soldier Dillon Farraday is stunned to discover he's a dad. He can handle a battlefield -- but not a bouncing baby boy! Rodeo queen Colleen Applegate is the only one who can show him the ropes. When Dillon's son was left on her porch, she became stand-in mom to the boy. Now Dillon's got three weeks to pass daddy school with flying colors...

Here – at last! – was my new boss, lounging in the doorway and smiling an irresistibly lop-sided smile. You know how it feels when a million butterflies are fluttering inside you? Well, that’s what it felt like the first time I, Summer Curtis, laid eyes on Phin Gibson…

A rollicking magical adventure story as King Midas sets out to find a cure for his magic touch so that he can turn his daughter back from gold. Witches, dragons, wizards and a host of amazing characters feature in this spell-binding tale from a supreme storyteller.

Will she stay in Vegas long enough to walk up the aisle?Alex Lowell has come to Las Vegas to have fun with her three best friends. She's given up on love and finding Prince Charming--the only date she wants is one at the spa with the girls! Alex's R & R is cut short when the hotel concierge goes into labor and she spontaneously jumps in to help, landing a job offer from hotel owner Wyatt McKendrick. Wyatt is cool, sexy and tempts Alex to open her heart again....

Carlita Santaro has never felt like a "proper" princess, and she's finally escaped the palace for the small town of Winter Haven.Daniel is an award-winning journalist, but now, as a single dad, he's working on a gossip show--better hours but rock-bottom morals. His boss orders Daniel to test suspiciously down-to-earth Carlita--is she really royal, or just posing as a princess? Carlita captivates Daniel, but soon he'll have to choose：Should he follow the headlines, or his heart?

Who’s that guy? There was a time when the devastatingly sexy Ethan Chandler left Marigold Chance blushing and tongue-tied, but thankfully that’s all in the past. Now that the ice-cool international yachtsman has sailed smoothly back into her life, she’s determined to show him that the ugly duckling’s become a thoroughly modern swan – a beautiful, driven businesswoman with no time for him! Yet Ethan seems equally determined to ruffle her perfectly groomed feathers and show her what she’s been missing out on – it’s time to let go and live for the future!

THE NEW HIGGINS HAS LANDED! One man with the key to Armageddon. One chance for Sean Dillon to find him. The hunt is on, in the mesmerizing new Sean Dillon thriller of murder, terrorism and revenge from the Sunday Times bestselling author.

CREAM TEAS! SCHOOL DINNERS! SATANIC SURFERS! Join our heroes as they follow up a Norfolk Mystery with a bad case of … DEATH IN DEVON. Swanton Morley, the People’s Professor, sets off for Devon to continue his history of England, The County Guides. Morley’s daughter Miriam and his assistant Stephen Sefton pack up the Lagonda for a trip to the English Riviera. Morley has been invited to give the Founder’s Day speech at All Souls School in Rousdon. But when the trio arrive they discover that a boy has died in mysterious circumstances. Was it an accident or was it – murder? Join Morley, Sefton and Miram on another adventure into the dark heart of 1930s England.

From the fields of France… Miss Sophie Vallois's looks and grace make her an instant hit with London Society. No one would know that the French beauty is a mere farmer's daughter, with no interest in marriage whatsoever…. To the drawing rooms of London! Except Robert Silverton, who has other reasons for staying away from Sophie. Yet her spirit and compassion intrigue him…. Rather than keeping her at arm's length, Robert soon wants the delectable Miss Vallois well and truly in his arms!

Determined to overthrow a notorious smuggling operation, gentleman thief-taker Sir Ashley Saunders will let nothing stand in his way! Until he runs up against spirited Pippa Kingslake, who's just as determined to protect her own interests…. With a string of demanding mistresses in his past, Ash thinks he'll handle Pippa with ease. Still unsure where her loyalties lie, Ash vows to keep her safe. But could Pippa's fierce independence end Ash's case—and his rakish ways?

Will You Love Me can either be read as a full-length eBook or in 3 serialised eBook-only parts. This is PART 3 of 3 (Chapters 17-27 of 27). You can read Part 3 on release of the full-length eBook and paperback. The eleventh memoir and latest title from the internationally bestselling author and foster carer Cathy Glass. This book tells the true story of Cathy’s adopted daughter Lucy. Lucy was born to a single mother who had been abused and neglected for most of her own childhood. Right from the beginning Lucy’s mother couldn’t cope, but it wasn’t until Lucy reached eight years old that she was finally taken into permanent foster care. By the time Lucy is brought to live with Cathy she is eleven years old and severely distressed after being moved from one foster home to another. Withdrawn, refusing to eat and three years behind in her schooling, it is thought that the damage Lucy has suffered is irreversible. But Cathy and her two children bond with Lucy quickly, and break through to Lucy in a way no-one else has been able to, finally showing her the loving home she never believed existed. Cathy and Lucy believe they were always destined to be mother and daughter – it just took them a little while to find each other.

WINNER OF THE COSTA BOOK OF THE YEAR 2013 ‘I’ll tell you what happened because it will be a good way to introduce my brother. His name’s Simon. I think you’re going to like him. I really do. But in a couple of pages he’ll be dead. And he was never the same after that.’ It is recommended readers use the Publisher's Fonts. There are books you can’t stop reading, which keep you up all night. There are books which let us into the hidden parts of life and make them vividly real. There are books which, because of the sheer skill with which every word is chosen, linger in your mind for days. The Shock of the Fall is all of these books. The Shock of the Fall is an extraordinary portrait of one man’s descent into mental illness. It is a brave and groundbreaking novel from one of the most exciting new voices in fiction.

Become an advanced practitioner with this progressive set of master classes on application-oriented machine learning About This Book ? Comprehensive coverage of key topics in machine learning with an emphasis on both the theoretical and practical aspects ? More than 15 open source Java tools in a wide range of techniques, with code and practical usage. ? More than 10 real-world case studies in machine learning highlighting techniques ranging from data ingestion up to analyzing the results of experiments, all preparing the user for the practical, real-world use of tools and data analysis. Who This Book Is For This book will appeal to anyone with a serious interest in topics in Data Science or those already working in related areas: ideally, intermediate-level data analysts and data scientists with experience in Java. Preferably, you will have experience with the fundamentals of machine learning and now have a desire to explore the area further, are up to grappling with the mathematical complexities of its algorithms, and you wish to learn the complete ins and outs of practical machine learning. What You Will Learn ? Master key Java machine learning libraries, and what kind of problem each can solve, with theory and practical guidance. ? Explore powerful techniques in each major category of machine learning such as classification, clustering, anomaly detection, graph modeling, and text mining. ? Apply machine learning to real-world data with methodologies, processes, applications, and analysis. ? Techniques and experiments developed around the latest specializations in machine learning, such as deep learning, stream data mining, and active and semi-supervised learning. ? Build high-performing, real-time, adaptive predictive models for batch- and stream-based big data learning using the latest tools and methodologies. ? Get a deeper understanding of technologies leading towards a more powerful AI applicable in various domains such as Security, Financial Crime, Internet of Things, social networking, and so on. In Detail Java is one of the main languages used by practicing data scientists; much of the Hadoop ecosystem is Java-based, and it is certainly the language that most production systems in Data Science are written in. If you know Java, Mastering Machine Learning with Java is your next step on the path to becoming an advanced practitioner in Data Science. This book aims to introduce you to an array of advanced techniques in machine learning, including classification, clustering, anomaly detection, stream learning, active learning, semi-supervised learning, probabilistic graph modeling, text mining, deep learning, and big data batch and stream machine learning. Accompanying each chapter are illustrative examples and real-world case studies that show how to apply the newly learned techniques using sound methodologies and the best Java-based tools available today. On completing this book, you will have an understanding of the tools and techniques for building powerful machine learning models to solve data science problems in just about any domain. Style and approach A practical guide to help you explore machine learning—and an array of Java-based tools and frameworks—with the help of practical examples and real-world use cases.

Build scalable, reliable, and cost-effective applications with a serverless architecture About This Book ? Design a real-world serverless application from scratch ? Learn about AWS Lambda function and how to use Lambda functions to glue other AWS Services ? Use the Java programming language and well-known design patterns. Although Java is used for the examples in this book, the concept is applicable across all languages ? Learn to migrate your JAX-RS application to AWS Lambda and API Gateway Who This Book Is For This book is for developers and software architects who are interested in designing on the back end. Since the book uses Java to teach concepts, knowledge of Java is required. What You Will Learn ? Learn to form microservices from bigger Softwares ? Orchestrate and scale microservices ? Design and set up the data flow between cloud services and custom business logic ? Get to grips with cloud provider’s APIs, limitations, and known issues ? Migrate existing Java applications to a serverless architecture ? Acquire deployment strategies ? Build a highly available and scalable data persistence layer ? Unravel cost optimization techniques In Detail Over the past years, all kind of companies from start-ups to giant enterprises started their move to public cloud providers in order to save their costs and reduce the operation effort needed to keep their shops open. Now it is even possible to craft a complex software system consisting of many independent micro-functions that will run only when they are needed without needing to maintain individual servers. The focus of this book is to design serverless architectures, and weigh the advantages and disadvantages of this approach, along with decision factors to consider. You will learn how to design a serverless application, get to know that key points of services that serverless applications are based on, and known issues and solutions. The book addresses key challenges such as how to slice out the core functionality of the software to be distributed in different cloud services and cloud functions. It covers basic and advanced usage of these services, testing and securing the serverless software, automating deployment, and more. By the end of the book, you will be equipped with knowledge of new tools and techniques to keep up with this evolution in the IT industry. Style and approach The book takes a pragmatic approach, showing you all the examples you need to build efficient serverless applications.

A practical guide to help you undertand the ability of Apache jMeter to load and performance test various server types in a more efficient way. About This Book ? Use jMeter to create and run tests to improve the performance of your webpages and applications ? Learn to build a test plan for your websites and analyze the results ? Unleash the power of various features and changes introduced in Apache jMeter 3.0 Who This Book Is For This book is for software professionals who want to understand and improve the performance of their applications with Apache jMeter. What You Will Learn ? See why performance testing is necessary and learn how to set up JMeter ? Record and test with JMeter ? Handle various form inputs in JMeter and parse results during testing ? Manage user sessions in web applications in the context of a JMeter test ? Monitor JMeter results in real time ? Perform distributed testing with JMeter ? Get acquainted with helpful tips and best practices for working with JMeter In Detail JMeter is a Java application designed to load and test performance for web application. JMeter extends to improve the functioning of various other static and dynamic resources. This book is a great starting point to learn about JMeter. It covers the new features introduced with JMeter 3 and enables you to dive deep into the new techniques needed for measuring your website performance. The book starts with the basics of performance testing and guides you through recording your first test scenario, before diving deeper into JMeter. You will also learn how to configure JMeter and browsers to help record test plans. Moving on, you will learn how to capture form submission in JMeter, dive into managing sessions with JMeter and see how to leverage some of the components provided by JMeter to handle web application HTTP sessions. You will also learn how JMeter can help monitor tests in real-time. Further, you will go in depth into distributed testing and see how to leverage the capabilities of JMeter to accomplish this. You will get acquainted with some tips and best practices with regard to performance testing. By the end of the book, you will have learned how to take full advantage of the real power behind Apache JMeter. Style and approach The book is a practical guide starting with introducing the readers to the importance of automated testing. It will then be a beginner’s journey from getting introduced to Apache jMeter to an in-detail discussion of more advanced features and possibilities with it.

Build Machine Learning models with a sound statistical understanding. About This Book ? Learn about the statistics behind powerful predictive models with p-value, ANOVA, and F- statistics. ? Implement statistical computations programmatically for supervised and unsupervised learning through K-means clustering. ? Master the statistical aspect of Machine Learning with the help of this example-rich guide to R and Python. Who This Book Is For This book is intended for developers with little to no background in statistics, who want to implement Machine Learning in their systems. Some programming knowledge in R or Python will be useful. What You Will Learn ? Understand the Statistical and Machine Learning fundamentals necessary to build models ? Understand the major differences and parallels between the statistical way and the Machine Learning way to solve problems ? Learn how to prepare data and feed models by using the appropriate Machine Learning algorithms from the more-than-adequate R and Python packages ? Analyze the results and tune the model appropriately to your own predictive goals ? Understand the concepts of required statistics for Machine Learning ? Introduce yourself to necessary fundamentals required for building supervised & unsupervised deep learning models ? Learn reinforcement learning and its application in the field of artificial intelligence domain In Detail Complex statistics in Machine Learning worry a lot of developers. Knowing statistics helps you build strong Machine Learning models that are optimized for a given problem statement. This book will teach you all it takes to perform complex statistical computations required for Machine Learning. You will gain information on statistics behind supervised learning, unsupervised learning, reinforcement learning, and more. Understand the real-world examples that discuss the statistical side of Machine Learning and familiarize yourself with it. You will also design programs for performing tasks such as model, parameter fitting, regression, classification, density collection, and more. By the end of the book, you will have mastered the required statistics for Machine Learning and will be able to apply your new skills to any sort of industry problem. Style and approach This practical, step-by-step guide will give you an understanding of the Statistical and Machine Learning fundamentals you'll need to build models.

Use scikit-learn to apply machine learning to real-world problems About This Book ? Master popular machine learning models including k-nearest neighbors, random forests, logistic regression, k-means, naive Bayes, and artificial neural networks ? Learn how to build and evaluate performance of efficient models using scikit-learn ? Practical guide to master your basics and learn from real life applications of machine learning Who This Book Is For This book is intended for software engineers who want to understand how common machine learning algorithms work and develop an intuition for how to use them, and for data scientists who want to learn about the scikit-learn API. Familiarity with machine learning fundamentals and Python are helpful, but not required. What You Will Learn ? Review fundamental concepts such as bias and variance ? Extract features from categorical variables, text, and images ? Predict the values of continuous variables using linear regression and K Nearest Neighbors ? Classify documents and images using logistic regression and support vector machines ? Create ensembles of estimators using bagging and boosting techniques ? Discover hidden structures in data using K-Means clustering ? Evaluate the performance of machine learning systems in common tasks In Detail Machine learning is the buzzword bringing computer science and statistics together to build smart and efficient models. Using powerful algorithms and techniques offered by machine learning you can automate any analytical model. This book examines a variety of machine learning models including popular machine learning algorithms such as k-nearest neighbors, logistic regression, naive Bayes, k-means, decision trees, and artificial neural networks. It discusses data preprocessing, hyperparameter optimization, and ensemble methods. You will build systems that classify documents, recognize images, detect ads, and more. You will learn to use scikit-learn’s API to extract features from categorical variables, text and images; evaluate model performance, and develop an intuition for how to improve your model’s performance. By the end of this book, you will master all required concepts of scikit-learn to build efficient models at work to carry out advanced tasks with the practical approach. Style and approach This book is motivated by the belief that you do not understand something until you can describe it simply. Work through toy problems to develop your understanding of the learning algorithms and models, then apply your learnings to real-life problems.