Develop deep neural networks in Theano with practical code examples for image classification, machine translation, reinforcement agents, or generative models. About This Book ? Learn Theano basics and evaluate your mathematical expressions faster and in an efficient manner ? Learn the design patterns of deep neural architectures to build efficient and powerful networks on your datasets ? Apply your knowledge to concrete fields such as image classification, object detection, chatbots, machine translation, reinforcement agents, or generative models. Who This Book Is For This book is indented to provide a full overview of deep learning. From the beginner in deep learning and artificial intelligence, to the data scientist who wants to become familiar with Theano and its supporting libraries, or have an extended understanding of deep neural nets. Some basic skills in Python programming and computer science will help, as well as skills in elementary algebra and calculus. What You Will Learn ? Get familiar with Theano and deep learning ? Provide examples in supervised, unsupervised, generative, or reinforcement learning. ? Discover the main principles for designing efficient deep learning nets: convolutions, residual connections, and recurrent connections. ? Use Theano on real-world computer vision datasets, such as for digit classification and image classification. ? Extend the use of Theano to natural language processing tasks, for chatbots or machine translation ? Cover artificial intelligence-driven strategies to enable a robot to solve games or learn from an environment ? Generate synthetic data that looks real with generative modeling ? Become familiar with Lasagne and Keras, two frameworks built on top of Theano In Detail This book offers a complete overview of Deep Learning with Theano, a Python-based library that makes optimizing numerical expressions and deep learning models easy on CPU or GPU. The book provides some practical code examples that help the beginner understand how easy it is to build complex neural networks, while more experimented data scientists will appreciate the reach of the book, addressing supervised and unsupervised learning, generative models, reinforcement learning in the fields of image recognition, natural language processing, or game strategy. The book also discusses image recognition tasks that range from simple digit recognition, image classification, object localization, image segmentation, to image captioning. Natural language processing examples include text generation, chatbots, machine translation, and question answering. The last example deals with generating random data that looks real and solving games such as in the Open-AI gym. At the end, this book sums up the best -performing nets for each task. While early research results were based on deep stacks of neural layers, in particular, convolutional layers, the book presents the principles that improved the efficiency of these architectures, in order to help the reader build new custom nets. Style and approach It is an easy-to-follow example book that teaches you how to perform fast, efficient computations in Python. Starting with the very basics-NumPy, installing Theano, this book will take you to the smooth journey of implementing Theano for advanced computations for machine learning and deep learning.

From the Booker Prize-winning author of ‘Offshore’, ‘The Blue Flower’ and ‘Innocence’ comes this Booker Prize-shortlisted tale of a troubled Moscow printworks . Frank Reid had been born and brought up in Moscow. His father had emigrated there in the 1870s and started a print-works which, by 1913, had shrunk from what it was when Frank inherited it. In that same year, to add to his troubles, Frank’s wife Nellie caught the train back home to England, without explanation. How is a reasonable man like Frank to cope? How should he keep his house running? Should he consult the Anglican chaplain’s wife? Should he listen to the Tolstoyan advice of his chief book-keeper? How do people live together, and what happens when, sometimes, they don’t?

The whole of the magnificent Riftwar Cycle by bestselling author Raymond E. Feist, master of magic and adventure, now available in ebook Jimmy the Hand, boy thief of Krondor, lived in the shadows of the city. The sewers were his byways and a flea-ridden, rat-infested cellar his home. Although gifted beyond his peers, he was still but a nimble street urchin, a pickpocket with potential. Until the day he met Prince Arutha. Aiding the Prince in his rescue of Princess Anita from imprisonment by Duke Guy du Bas-Tyra, Jimmy runs afoul of Black Guy's secret police. Given the choice of disappearing on his own or in a weighted barrel at the bottom of Krondor's harbor, Jimmy flees the only home he's ever known, venturing south to the relatively safe haven of Land's End. Suspecting that the rural villagers have never encountered a lad with his talent and nose for finding wealth—other people's wealth—he's fairly optimistic about his broadening horizons. But Jimmy is completely unprepared for what greets him. For Land's End is home to others who tread the crooked path, and more, to a much darker secret: a dangerous presence unknown even to the local thieves and smugglers. And Jimmy's youthful bravado and courage will plunge him deep into the maw of chaos and even—if he isn't careful—death.

Winner of the Gold Dagger Award for Best Crime Novel of the Year…’Reginald Hill is on stunning form…the climax is devastating’ Marcel Berlins, The Times When Detective Superintendent Andy Dalziel witnesses a bizarre murder across the street from his own back garden, he is quite sure who the culprit is. After all, he’s got to believe what he sees with his own eyes. But what exactly does he see? And is he mistaken? Peter Pascoe thinks so. Dalziel senses the doubters around him, which only strengthens his resolve. To make matters worse, he’s being pestered by an anonymous letter-writer, threatening suicide. Worse still, Pascoe seems intent on reminding him of the fact. Meanwhile, the effervescent Eileen Chung is directing the Mystery Plays. And who does she have in mind for God? Daziel, of course. He shouldn’t have too much difficulty acting the part…

‘Humour and topicality along a cold enigmatic trail of murder’ Observer Life is on the up for Patrick Aldermann: his Great Aunt Florence has collapsed into her rose bed leaving him Rosemont House with its splendid gardens. But when his boss, ‘Dandy’ Dick Elgood, suggests to Peter Pascoe that Aldermann is a murderer – then later retracts the accusation – the detective inspector is left with a thorny problem. Not only have the police already dug up some interesting information about Aldermann’s beautiful wife; it also appears that his rapid promotion has been helped by the convenient deaths of some of his colleagues…

‘One of the modern masters of the police procedural’ Sunday Telegraph Peter Pascoe is in shock. A weekend in the country with old friends turns into a nightmare when he finds three of them dead and the missing fourth a prime suspect in the eyes of the local police. They want his cooperation, but Superintendent Dalziel needs him back in Yorkshire where a string of unsolved burglaries looks like turning nasty. As events unfold, though, the two cases seem to be getting entwined…

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.

A single father who yearns to be a family man, Logan O'Donnell is determined to create the perfect Christmas for his son, Charlie. The entire O’Donnell clan arrives to spend the holidays in Avalon, a postcard-pretty town on the shores of Willow Lake, a place for the family to reconnect and rediscover the special gifts of the season. One of the guests is a newcomer to Willow Lake–Darcy Fitzgerald. Sharp-witted, independent and intent on guarding her heart, she’s the last person Logan can see himself falling for. And Darcy is convinced that a relationship is the last thing she needs this Christmas. Yet between the snowy silence of the winter woods, and toasty moments by a crackling fire, their two lonely hearts collide. The magic of the season brings them each a gift neither ever expected–a love to last a lifetime.

Vaughn Donnelly's work has taken him to many different villages over the years, and he's never regretted saying goodbye to anyone in them. Until he promises to help Darcy Keegan rescue an orphaned boy from prison. Darcy dreams of a family, a home, a husband… But can Vaughn offer Darcy what she needs?

Man trouble! The second time Morgan met Richard Kavanagh she was supposed to be helping charm the television heartthrob into giving her sister a job. Unfortunately, Morgan suspected that careering into Richard's car wasn't exactly the "good impression" that Elaine had had in mind! Worse, Richard thought it was an elaborate plan to get an autograph. She didn't even like the man! He was rude, opinionated and far too sexy for his own good–and hers! And if he ever remembered the first time they had met, Morgan would really be heading for trouble!

The marriage deadline Tessa is on a mission of mercy. She can barely afford the visit to England to check that her newly orphaned nephew will be all right with his grandmother. Then she plans to return to Australia and her fiancé. But it all goes awry as soon as she steps onto the plane and meets Charles Cameron. He's an Australian farmer who's just become the thirteenth Earl of Dalston, and he has an inheritance to protect, for others more than himself. He needs a bride by Friday–his thirtieth birthday–and Tessa fits the bill….

He had no memory of her It hurt that there was not the faintest recognition in Ben Congreve's eyes when Ellie Osborne met him again after seven long years. Had there been so many women in his life that he didn't remember their fleeting holiday romance? Ellie was tempted to exact retribution for the way Ben had sailed out of her life, leaving her totally alone–and pregnant. It had been a battle to overcome the odds, but she had ultimately made a success of her life. So perhaps she owed it to her precious young daughter to keep the past well hidden from Charlie's dad….

MERGER IN THE MAKING…? Powerful CEO Philip Ambercroft prized efficiency, order–and no temptation in the office. So when he needed a temporary assistant, he decided to hire a no-nonsense, matronly type. But then he met the most qualified candidate…. All-too-appealing Madalyn Wier had impeccable references and years of experience–and she soon had her handsome executive boss falling for her womanly charms. But Philip was determined to deny the attraction between them, especially since Madalyn was a single mother who had a daughter to consider. And the confirmed bachelor wasn't prepared to propose a marriage merger…was he?

FAMILY MATTERS THE LAWMAN AND THE LADY Hallie Cates's biological clock was ticking, but there was nary a husband on the horizon. Then she returned to her hometown and discovered Cam Osborne–a gorgeous small-town sheriff straight out of her dreams. He was everything she wanted in a man, but he'd sworn off commitment. And although she tried to steer clear of the handsome lawman, Cam was impossible to resist. Avowed loner Cam liked his bachelor life-style–until he butted heads with the lovely schoolteacher over her law-breaking grandmother. Sweet Hallie with her down-home values was a lady worth chasing. Only problem was, Hallie was the kind of woman a man married, and Cam wasn't looking for a wife…was he? Kisses, kids, cuddles and kin. The best things in life are found in families!

A convenient wife? Nicole wasn't looking for a temporary affair–and this was all loner Dr. Alexander Strathallen seemed prepared to offer. So she resisted her attraction to him…. Until he confessed that he needed an heir and suggested a marriage of convenience! Nicole told herself she could live with being a wife in name only if it meant her young son would have a father figure. Only on her wedding night–in the heat of the desert–she found herself wanting much more….

A Kind of Magic Part-time witch, full-time glamorous high-flyer Esme Mcleod rubs shoulders with celebrities for a living, has a sort-of-boyfriend …and just enough magic in her fingertips to solve life’s little irritations; why shouldn’t she cast a little spell to catch the busy barman’s attention, or to summon a latte to aid her all-nighters? Called back to her small Scottish home town and meddling family, stiletto-clad Esme is way out of her comfort zone… But Esme must embrace her abilities as a witch, or watch her family lose their beloved café. Except Esme has never claimed to be a whizz at witchcraft, and her charms are starting to go awry – she certainly never meant to cast a love spell on her ex-boyfriend Jamie! It’s time for urgent lessons in magic as well as love – it seems there’s only so much that muttering a few words over cupcake batter will fix… Don't miss the Could It Be Magic series: 1 – Bewitched, Bothered & Bewildered 2 – I Put a Spell on You 3 – Baby It's Cold Outside 4 – I’ll Be There For You 5 – A Spoonful of Sugar (novella) What readers are saying about Kerry Barrett 'I was absorbed from the first page' – Pass The Gin 'It was just lovely! I loved the plot, I loved the spells and the magic, I loved the characters and I loved the writing. Kerry Barrett is a talented writer and I’m so pleased I got the chance to review her debut novel and here’s hoping there will be many more!' – Chick Lit Reviews and News 'This is a story filled with heart-warming characters full of family loyalty, a little romance … sprinkled with magic and humour throughout which will leave you, like me wanting to find out what happen next for Esme and her family.’ – That Thing She Reads

Sometimes love needs a rewrite The stunning romantic comedy from David Solomans, Winner of the 2016 Waterstones Children’s Book Prize With her debut novel, Happy Ending, JANE LOCKHART pulled off that rare double – critical acclaim and mainstream success. But now, with just the last chapter of the follow-up book to write, she encounters crippling writer’s block. She has no idea how her story ends… This is not good news for her publisher, TOM DUVAL. His company is up against the wall financially and the only thing that will save him is a massive hit, in the form of Jane’s next novel. When he discovers that his most important author is blocked, Tom realises that he has to unblock her or he’s finished. Everyone knows that you have to be unhappy to be really creative, so Tom decides that the only way he’s going to get her to complete the novel is to make her life a misery… Set within the Scottish publishing industry, and filmed against a stunning backdrop of both romantic and hip Glasgow locations, Not Another Happy Ending is perfect for fans of One Day. “Engagingly watchable” – Mark Adams, Screen Daily “…has more heart than most Hollywood rom-coms…an entertaining diversion and an example of mainstream Scottish cinema that easily holds its own” – Rob Dickie, Sight On Sound About the author David Solomons is the BAFTA-shortlisted screen screenwriter of The Great Ghost Rescue, The Fabulous Bagel Boys and Five Children and It. He lives in Dorset with his wife, Natasha Solomons, and their young son. Not Another Happy Ending is his first novel.