She had never needed anyone before. Never ached for a man before. Until her latest mission put Apache pilot Akiva Redtail in the hot seat next to army officer Joe Calhoun. As they rode the thunderous skies, dodging danger at every turn, Akiva discovered a strength in Joe's arms, a fiery passion she was powerless to battle against. For only with this rugged soldier by her side could this Native American beauty fulfill the destiny she was born to. Only with Joe did she dare open her heart to love….

He loved a challenge You didn't go from being a poor kid in the hood to making millions on Wall Street unless you had a man-size desire to succeed. Will Coleman had all that–and good looks and a head-turning, hard-muscled body to match. So what if he taught ballroom dancing in his spare time? Will was all man. And all he needed was the perfect woman…. She danced to the beat of a different drum Then Melody Rush, a bodacious beauty with long, wavy hair down to her curvy behind–and an equally feisty attitude–walked into his dance studio. And suddenly Will was left wondering if she might be the one.

Though she wanted a family of her own, love seemed so unreliable to busy bakery owner Ava McKaslin. Baking and honoring her faith were all she had on her life's to-do list. Until she hired Brice Donovan as her contractor. And her best-laid plans flew out the window! He'd long adored Ava from afar. Now that she needed his help, Brice wanted to show her how joyful life could be when there was love. He–and he hoped, the Lord–had big plans to give this special woman all the happiness she deserved.

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.

Harness the power of Scala to program Spark and analyze tonnes of data in the blink of an eye! About This Book ? Learn Scala’s sophisticated type system that combines Functional Programming and object-oriented concepts ? Work on a wide array of applications, from simple batch jobs to stream processing and machine learning ? Explore the most common as well as some complex use-cases to perform large-scale data analysis with Spark Who This Book Is For Anyone who wishes to learn how to perform data analysis by harnessing the power of Spark will find this book extremely useful. No knowledge of Spark or Scala is assumed, although prior programming experience (especially with other JVM languages) will be useful to pick up concepts quicker. What You Will Learn ? Understand object-oriented & functional programming concepts of Scala ? In-depth understanding of Scala collection APIs ? Work with RDD and DataFrame to learn Spark’s core abstractions ? Analysing structured and unstructured data using SparkSQL and GraphX ? Scalable and fault-tolerant streaming application development using Spark structured streaming ? Learn machine-learning best practices for classification, regression, dimensionality reduction, and recommendation system to build predictive models with widely used algorithms in Spark MLlib & ML ? Build clustering models to cluster a vast amount of data ? Understand tuning, debugging, and monitoring Spark applications ? Deploy Spark applications on real clusters in Standalone, Mesos, and YARN In Detail Scala has been observing wide adoption over the past few years, especially in the field of data science and analytics. Spark, built on Scala, has gained a lot of recognition and is being used widely in productions. Thus, if you want to leverage the power of Scala and Spark to make sense of big data, this book is for you. The first part introduces you to Scala, helping you understand the object-oriented and functional programming concepts needed for Spark application development. It then moves on to Spark to cover the basic abstractions using RDD and DataFrame. This will help you develop scalable and fault-tolerant streaming applications by analyzing structured and unstructured data using SparkSQL, GraphX, and Spark structured streaming. Finally, the book moves on to some advanced topics, such as monitoring, configuration, debugging, testing, and deployment. You will also learn how to develop Spark applications using SparkR and PySpark APIs, interactive data analytics using Zeppelin, and in-memory data processing with Alluxio. By the end of this book, you will have a thorough understanding of Spark, and you will be able to perform full-stack data analytics with a feel that no amount of data is too big. Style and approach Filled with practical examples and use cases, this book will hot only help you get up and running with Spark, but will also take you farther down the road to becoming a data scientist.

Just after ‘Bring Up the Bodies’ author Hilary Mantel won the Man Booker for ‘Wolf Hall’, she fell gravely ill. This is her remarkable hospital diary. Originally published in the London Review of Books, this diary by the acclaimed author Hilary Mantel explores in forensic detail her loss of dignity, her determination, the concentration of the senses into an animalistic struggle to get through, and the attendant hallucinations she was plagued by during her stay in hospital. With her health now improved, and the acknowledgement of the Man Booker prize-winning follow-up to ‘Wolf Hall’, ‘Bring Up the Bodies’ as one of our greatest works of fiction, ‘Ink in the Blood’ remains a significant testament to the traumas of illness, and one of the most incredible and haunting essays published in a very long time.

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.

An unexpected night of passion at the magnificent Fortune ranch seemed the perfect antidote to Savannah Clark's bruised ego after a bad breakup.The serious schoolteacher had never done anything so reckless in her life, but horse trainer Cruz Perez had been a fantasy come true–and left Savannah with no regrets. Not even when she finds herself pregnant, fired from her job and with no option but to accept a job back at the Fortune ranch, resolving not to tell Cruz her secret. She doesn't need a shotgun husband by her side. Cruz suspects the truth, though, and longs to be a loving partner to Savannah and doting father to their child. But he's got a couple of big obstacles: a proud, stubborn woman, and a rival with the name Fortune.

Caroline's EX-boyfriend: That slimeball attorney who was two-timing her with his own ex-wife. Caroline's OH-boy: This forty-three-year-old career woman is pregnant! Life certainly hasn't gone according to Caroline Moore's carefully constructed plan. As the craziness of her situation begins spiraling out of control, she decides on a change of scenery. So off to a small lakeside cottage she goes. Soon she's shedding her designer shoes for barefoot walks, uncovering old family secrets and becoming best friends with Tori–a woman who is her total opposite. And thanks to a handsome neighbor, she might just be ready for romance, as well. But wait…Caroline's new oh-what-a-great-guy also happens to be Tori's ex-husband. Get ready for the shoes to fly!

Mike Bishop's latest assignment should have been simple–rescue a woman and the young boy in her care. But there was nothing simple about beautiful Ann Hamilton. Suddenly, Mike was thinking more and more about ways to mix business with pleasure. Lots of pleasure… Mike was a hazel-eyed, walking hunk of testosterone–and the last thing Ann needed. She wanted only to start a peaceful new life with her adopted son, but Mike had a way of inflaming much more than just her temper. He would protect her life, but what about her heart?

IT WAS LOVE AT FIRST KITE… From the moment Angus Calder's kite disrupted her beachfront nap, Kenzie Daniels was a goner. And the energetic seven-year old seemed just as smitten…unlike his heart-stopping, coolly conservative dad. Ross Calder obviously didn't want his son growing attached to Kenzie, so why was she still drawn to the vulnerable single father struggling to form a bond with the son he'd never known? The beach vacation was supposed to bring Ross and his unresponsive son closer, yet the free-spirited beauty was the one they were both forming an attachment to. While the levelheaded attorney couldn't deny his attraction, he wouldn't risk his son's heart breaking when they returned home and bid Kenzie goodbye. And Angus's heart was the only one at risk…wasn't it?

He'd finally gotten his revenge. Tough loner Max Cooper had been given the perfect opportunity to put his high-and-mighty partner, Kristina Fortune, in her place. The pampered princess had lost her memory and was depending on Max to fill in the gaps. While Max's head told him to make Kristina his personal slave, his heart had him questioning his motives. Was the brooding bachelor punishing Kristina for his overwhelming attraction…or denying himself a honeymoon to remember?

THE OLDER WOMAN The first time fortune found Sierra Carlton, she'd become a millionaire. The second time, Sam Jayce stood before her, a long, lean, young farmer hungry to make her flower ranch a reality. Trouble was, Sam made her hunger for more than success. But Sierra had let desire dictate once…and found herself a single mom. Well, wild horses couldn't spook Sam from her side…especially once they became lovers. But when word spread of the Puma Springs heiress and her studly partner mixing business with pleasure, Sam refused to let the scandal that dogged him dishonor Sierra. Only, Sierra didn't need defending. She needed Sam as their baby's daddy–and she needed his love.

The Annunaki, a power-hungry and hate-driven alien race, have returned to take over Earth. This time, permanently. And the hard-core human rebels who fought to repel these self-proclaimed gods have paid a terrible price. Just when they are needed most–as the post apocalyptic threat surges to terrifying new levels–the Cerberus operation lies broken, its key members missing. Ullikummis has chosen Earth as ground zero for a terrifying family reunion. A son born of cruelty, genetic manipulation and infinite power, for 4,000 years the stone god has waited, plotting his revenge against his father, Enlil, the most sadistic of the Annunaki. As father and child unleash their armies in a clash of titanic proportions, the bravest of the rebels, Kane, is humanity's last hope to halt this deadly war of the gods. Endgame has finally arrived…but who will be the winner?

EVERYONE KNOWS SISTERS LIKE THE SAMS GIRLS–three women trying their best to be good daughters, mothers and wives. LYDIA, married to Wayne, worked a dead-end job to make sure her daughter, Anna Claire, had the best in life. MADALAINE, the mother of two, struggled to get on with life after her husband's desertion and ELLIE…well, Ellie shuffled along, taking care of her parents and brother, while dreaming of Graceland. Life rolled along, routine, expected. Until one cataclysmic moment when everything changed…and the sisters had to uncover every shrouded secret, risk lifetime bonds, to ensure the survival of all they loved.

Jake Maitland, FBI agent and black sheep of the Maitland clan, had finally come home. And he had a whole lot of trouble on his tail…. Camille Eckart was Jake's latest assignment. He'd been chosen as her protector, to keep her and her newborn son safe from her mobster ex-husband. Only, little did Jake guess that Camille's main objective was to make him see her not as a case, but as a woman…. Jake's reputation as a loner had taken on legendary proportions–until Camille and little Jamie stole their way into his heart. But with kingpin Vince Eckart on the loose, Jake couldn't afford to get emotionally involved. Their lives depended on him. But as he spent time holed up with mother and son, he quickly discovered his life depended even more on them….

Ellie Waters usually juggled career, family and church commitments with ease. But when her mother fell ill, coping suddenly seemed overwhelmingly difficult. For help she looked to the past–and within her deepest self. Charlene Butler, wife, grandmother and businesswoman, was enjoying a bright, new chapter of her life. But her aunt Dorothy's medical crisis suddenly made Charlene wonder how solid the foundation of her world really was. On their journeys of discovery, these two very different women met, shared the burden of being caretakers, and in doing so they became best friends. Together they laughed, prayed and found new strength and new depths to their faith.

Members of the wedding party are starting to die. No one could believe that Thomas Beckham was the kind of man to leave a woman at the altar, but he couldn't marry his bride-to-be. Not after what he'd seen her do. His only choice was to leave and never look back–and to keep to himself everything he'd witnessed. After the wedding-that-wasn't, everyone, including Kelly Ralston, went on to other things. Or so it had always seemed. But ten years later, Kelly finds herself attending the funeral of another one of the bridesmaids–the third member of the wedding party to meet a tragic death. Kelly can't help but wonder if the deaths are a coincidence. Or are they linked? If so, who will be targeted next? Thomas Beckham may be her only chance to find the killer. Before the killer finds her…