With their straightforward style, Suresh Krishna and TC Fenstermaker have put their years of experience and motivation into this practical guide that assists in finding an integrated approach to increased team productivity. The numerous tips, notes, and suggestions strengthen your grasp of fundamentals and the foundation upon which you are ready to build your customized Rational Team Concert application. Ample screenshots make sure that you get the configurations correct the first time. A real-world Book Manager Application walks you through all the core features of the Rational Team Concert during different phases of development and release. If you are a Project Manager or a Team Member, who would like to find an integrated approach to deal with modern software development challenges, you should read this book. Or if you are someone who likes to stay one step ahead in team management, you have got the right choice here.

This book is built on recipes written in an easy-to-follow manner accompanied by diagrams and crucial insights and knowledge on what they mean in the real world. This book is ideal for musicians and producers who want to take their music creation skills to the next level, learn tips and tricks, and understand the key elements and nuances in building inspirational music. It’s good to have some knowledge about music production, but if you have creativity and a good pair of ears, you are already ahead of the curve and well on your way.

This book provides an overview of the kill chain approach to penetration testing, and then focuses on using Kali Linux to provide examples of how this methodology is applied in the real world. After describing the underlying concepts, step-by-step examples are provided that use selected tools to demonstrate the techniques.If you are an IT professional or a security consultant who wants to maximize the success of your network testing using some of the advanced features of Kali Linux, then this book is for you. This book will teach you how to become an expert in the pre-engagement, management, and documentation of penetration testing by building on your understanding of Kali Linux and wireless concepts.

Written in a stepbystep, tutorial style with a lot of code snippets and handson examples to create an advanced Magento theme from scratch, this book is tailormade for web designers and developers. This book is great for developers and web designers who are looking to get a good grounding in how to create custom, responsive, and advanced Magento themes. Readers must have some experience with HTML, PHP, CSS, and Magento theme design. This book will be useful for anybody who already has knowledge of the Magento frontend structure.

A comprehensive practical guide that walks you through the multiple stages of data management in enterprise and gives you numerous design patterns with appropriate code examples to solve frequent problems in each of these stages. The chapters are organized to mimick the sequential data flow evidenced in Analytics platforms, but they can also be read independently to solve a particular group of problems in the Big Data life cycle. If you are an experienced developer who is already familiar with Pig and is looking for a use case standpoint where they can relate to the problems of data ingestion, profiling, cleansing, transforming, and egressing data encountered in the enterprises. Knowledge of Hadoop and Pig is necessary for readers to grasp the intricacies of Pig design patterns better.

Master machine learning techniques with R to deliver insights for complex projectsAbout This BookGet to grips with the application of Machine Learning methods using an extensive set of R packagesUnderstand the benefits and potential pitfalls of using machine learning methodsImplement the numerous powerful features offered by R with this comprehensive guide to building an independent R-based ML system Who This Book Is For If you want to learn how to use R's machine learning capabilities to solve complex business problems, then this book is for you. Some experience with R and a working knowledge of basic statistical or machine learning will prove helpful.What You Will LearnGain deep insights to learn the applications of machine learning tools to the industryManipulate data in R efficiently to prepare it for analysisMaster the skill of recognizing techniques for effective visualization of dataUnderstand why and how to create test and training data sets for analysisFamiliarize yourself with fundamental learning methods such as linear and logistic regressionComprehend advanced learning methods such as support vector machinesRealize why and how to apply unsupervised learning methods In Detail Machine learning is a field of Artificial Intelligence to build systems that learn from data. Given the growing prominence of R—a cross-platform, zero-cost statistical programming environment—there has never been a better time to start applying machine learning to your data. The book starts with introduction to Cross-Industry Standard Process for Data Mining. It takes you through Multivariate Regression in detail. Moving on, you will also address Classification and Regression trees. You will learn a couple of “Unsupervised techniques”. Finally, the book will walk you through text analysis and time series. The book will deliver practical and real-world solutions to problems and variety of tasks such as complex recommendation systems. By the end of this book, you will gain expertise in performing R machine learning and will be able to build complex ML projects using R and its packages.Style and approach This is a book explains complicated concepts with easy to follow theory and real-world, practical applications. It demonstrates the power of R and machine learning extensively while highlighting the constraints.

Generate effective results in a variety of visually appealing charts using the plotting packages in PythonAbout This BookExplore various tools and their strengths while building meaningful representations that can make it easier to understand dataPacked with computational methods and algorithms in diverse fields of scienceWritten in an easy-to-follow categorical style, this book discusses some niche techniques that will make your code easier to work with and reuse Who This Book Is For If you are a Python developer who performs data visualization and wants to develop existing knowledge about Python to build analytical results and produce some amazing visual display, then this book is for you. A basic knowledge level and understanding of Python libraries is assumed.What You Will LearnGather, cleanse, access, and map data to a visual frameworkRecognize which visualization method is applicable and learn best practices for data visualizationGet acquainted with reader-driven narratives and author-driven narratives and the principles of perceptionUnderstand why Python is an effective tool to be used for numerical computation much like MATLAB, and explore some interesting data structures that come with itExplore with various visualization choices how Python can be very useful in computation in the field of finance and statisticsGet to know why Python is the second choice after Java, and is used frequently in the field of machine learningCompare Python with other visualization approaches using Julia and a JavaScript-based framework such as D3.jsDiscover how Python can be used in conjunction with NoSQL such as Hive to produce results efficiently in a distributed environment In Detail Python has a handful of open source libraries for numerical computations involving optimization, linear algebra, integration, interpolation, and other special functions using array objects, machine learning, data mining, and plotting. Pandas have a productive environment for data analysis. These libraries have a specific purpose and play an important role in the research into diverse domains including economics, finance, biological sciences, social science, health care, and many more. The variety of tools and approaches available within Python community is stunning, and can bolster and enhance visual story experiences. This book offers practical guidance to help you on the journey to effective data visualization. Commencing with a chapter on the data framework, which explains the transformation of data into information and eventually knowledge, this book subsequently covers the complete visualization process using the most popular Python libraries with working examples. You will learn the usage of Numpy, Scipy, IPython, MatPlotLib, Pandas, Patsy, and Scikit-Learn with a focus on generating results that can be visualized in many different ways. Further chapters are aimed at not only showing advanced techniques such as interactive plotting; numerical, graphical linear, and non-linear regression; clustering and classification, but also in helping you understand the aesthetics and best practices of data visualization. The book concludes with interesting examples such as social networks, directed graph examples in real-life, data structures appropriate for these problems, and network analysis. By the end of this book, you will be able to effectively solve a broad set of data analysis problems.Style and approach The approach of this book is not step by step, but rather categorical. The categories are based on fields such as bioinformatics, statistical and machine learning, financial computation, and linear algebra. This approach is beneficial for the community in many different fields of work and also helps you learn how one approach can make sense across many fields

This book will help beginners to create stylish and professional looking dashboards in no time. It is also intended for BI developers who want to use SAP BO to facilitate BI in their organizations. No prior knowledge is required, however, you must have a basic knowledge of MS Excel and some analytical skills to build expressive business charts.

If you are a data analyst with basic knowledge of Big Data analysis but no knowledge of Splunk, then this book will help you get started with Splunk. The book assumes that you have access to a copy of Splunk, ideally not in production, and many examples also assume you have administrator rights.

Throughout the book, we will follow a fictional company, the case study will help you in implementing FIM 2010 R2. All the examples in the book will relate to this fictive company and you will be taken from design, to installation, to configuration of FIM 2010 R2. If you are implementing and managing FIM 2010 R2 in your business, then this book is for you. You will need to have a basic understanding of Microsoft based infrastructure using Active Directory. If you are new to Forefront Identity Management, the case-study approach of this book will help you to understand the concepts and implement them.

This is a practical guide providing comprehensive solutions for SQL query problems, and is full of concrete real-world examples to help you create and troubleshoot your SQL queries in SAP Business One. If you are a system administrator who uses SQL query as your tool of choice for solving specific problems throughout SAP Business One, then this book is for you. It may also be useful if you are a developer or consultant using this technology, and can benefit end users by improving your search for important business information. A rudimentary knowledge of SAP Business One and SQL Server is required to use this book efficiently. Examples covered are relevant to SBO 2007A users, for which the 8.8 release is mostly compatible. All SQL query examples within the book are verified under SQL Server 2005, so they are guaranteed to run under this release, in addition to SQL Server 2008. Non-SAP Business One users can also gain knowledge from the many examples throughout the book. It is hard to find another book with so many SQL query examples.

This book is written in a clear conversational style, which emphasizes a practical learn-by-doing approach. This step by step guide has illustrative examples to implement Ext JS library features in your Oracle APEX applications If you are an Oracle APEX application developer who wants to take APEX applications to the next level by taking advantage of Ext JS features, this book is for you. Prior knowledge of Oracle APEX is required, however, no prior knowledge of Ext JS is required.

A practical tutorial containing clear, step-by-step explanations of all the concepts required to understand the technology involved in virtualizing your application infrastructure. Each chapter uses real-world scenarios so that the readers can put into practice what they learn immediately and with the right guidance. Each topic is written defining a common need and developing the process to solve it using Microsoft App-V. This book is for system administrators or consultants who want to master and dominate App-V, and gain a deeper understanding of the technology in order to optimize App V implementations. Even though the book does not include basic steps like installing App-V components or sequencing simple applications; application virtualization beginners will receive a comprehensive look into App-V before jumping into the technical process of each chapter.

Gain sharp insights into your data and solve real-world data science problems with R—from data munging to modeling and visualization About This Book Handle your data with precision and care for optimal business intelligence Restructure and transform your data to inform decision-making Packed with practical advice and tips to help you get to grips with data mining Who This Book Is For If you are a data scientist or R developer who wants to explore and optimize your use of R’s advanced features and tools, this is the book for you. A basic knowledge of R is required, along with an understanding of database logic. What You Will Learn Connect to and load data from R’s range of powerful databases Successfully fetch and parse structured and unstructured data Transform and restructure your data with efficient R packages Define and build complex statistical models with glm Develop and train machine learning algorithms Visualize social networks and graph data Deploy supervised and unsupervised classification algorithms Discover how to visualize spatial data with R In Detail R is an essential language for sharp and successful data analysis. Its numerous features and ease of use make it a powerful way of mining, managing, and interpreting large sets of data. In a world where understanding big data has become key, by mastering R you will be able to deal with your data effectively and efficiently. This book will give you the guidance you need to build and develop your knowledge and expertise. Bridging the gap between theory and practice, this book will help you to understand and use data for a competitive advantage. Beginning with taking you through essential data mining and management tasks such as munging, fetching, cleaning, and restructuring, the book then explores different model designs and the core components of effective analysis. You will then discover how to optimize your use of machine learning algorithms for classification and recommendation systems beside the traditional and more recent statistical methods. Style and approach Covering the essential tasks and skills within data science, Mastering Data Analysis provides you with solutions to the challenges of data science. Each section gives you a theoretical overview before demonstrating how to put the theory to work with real-world use cases and hands-on examples.

Design, build and simulate complex robots using Robot Operating System and master its out-of-the-box functionalities About This Book Develop complex robotic applications using ROS for interfacing robot manipulators and mobile robots with the help of high end robotic sensors Gain insights into autonomous navigation in mobile robot and motion planning in robot manipulators Discover the best practices and troubleshooting solutions everyone needs when working on ROS Who This Book Is For If you are a robotics enthusiast or researcher who wants to learn more about building robot applications using ROS, this book is for you. In order to learn from this book, you should have a basic knowledge of ROS, GNU/Linux, and C++ programming concepts. The book will also be good for programmers who want to explore the advanced features of ROS. What You Will Learn Create a robot model of a Seven-DOF robotic arm and a differential wheeled mobile robot Work with motion planning of a Seven-DOF arm using MoveIt! Implement autonomous navigation in differential drive robots using SLAM and AMCL packages in ROS Dig deep into the ROS Pluginlib, ROS nodelets, and Gazebo plugins Interface I/O boards such as Arduino, Robot sensors, and High end actuators with ROS Simulation and motion planning of ABB and Universal arm using ROS Industrial Explore the ROS framework using its latest version In Detail The area of robotics is gaining huge momentum among corporate people, researchers, hobbyists, and students. The major challenge in robotics is its controlling software. The Robot Operating System (ROS) is a modular software platform to develop generic robotic applications.This book discusses the advanced concepts in robotics and how to program using ROS. It starts with deep overview of the ROS framework, which will give you a clear idea of how ROS really works. During the course of the book, you will learn how to build models of complex robots, and simulate and interface the robot using the ROS MoveIt motion planning library and ROS navigation stacks.After discussing robot manipulation and navigation in robots, you will get to grips with the interfacing I/O boards, sensors, and actuators of ROS. One of the essential ingredients of robots are vision sensors, and an entire chapter is dedicated to the vision sensor, its interfacing in ROS, and its programming.You will discuss the hardware interfacing and simulation of complex robot to ROS and ROS Industrial (Package used for interfacing industrial robots).Finally, you will get to know the best practices to follow when programming using ROS.Style and approach This is a simplified guide to help you learn and master advanced topics in ROS using hands-on examples.

Load, wrangle, and analyze your data using the world's most powerful statistical programming language About This Book Load, manipulate and analyze data from different sources Gain a deeper understanding of fundamentals of applied statistics A practical guide to performing data analysis in practice Who This Book Is For Whether you are learning data analysis for the first time, or you want to deepen the understanding you already have, this book will prove to an invaluable resource. If you are looking for a book to bring you all the way through the fundamentals to the application of advanced and effective analytics methodologies, and have some prior programming experience and a mathematical background, then this is for you. What You Will Learn Navigate the R environment Describe and visualize the behavior of data and relationships between data Gain a thorough understanding of statistical reasoning and sampling Employ hypothesis tests to draw inferences from your data Learn Bayesian methods for estimating parameters Perform regression to predict continuous variables Apply powerful classification methods to predict categorical data Handle missing data gracefully using multiple imputation Identify and manage problematic data points Employ parallelization and Rcpp to scale your analyses to larger data Put best practices into effect to make your job easier and facilitate reproducibility In Detail Frequently the tool of choice for academics, R has spread deep into the private sector and can be found in the production pipelines at some of the most advanced and successful enterprises. The power and domain-specificity of R allows the user to express complex analytics easily, quickly, and succinctly. With over 7,000 user contributed packages, it’s easy to find support for the latest and greatest algorithms and techniques. Starting with the basics of R and statistical reasoning, Data Analysis with R dives into advanced predictive analytics, showing how to apply those techniques to real-world data though with real-world examples. Packed with engaging problems and exercises, this book begins with a review of R and its syntax. From there, get to grips with the fundamentals of applied statistics and build on this knowledge to perform sophisticated and powerful analytics. Solve the difficulties relating to performing data analysis in practice and find solutions to working with “messy data”, large data, communicating results, and facilitating reproducibility. This book is engineered to be an invaluable resource through many stages of anyone’s career as a data analyst. Style and approach Learn data analysis using engaging examples and fun exercises, and with a gentle and friendly but comprehensive "learn-by-doing" approach.

Design, implement, and deliver successful streaming applications, machine learning pipelines and graph applications using Spark SQL API About This Book ? Learn about the design and implementation of streaming applications, machine learning pipelines, deep learning, and large-scale graph processing applications using Spark SQL APIs and Scala. ? Learn data exploration, data munging, and how to process structured and semi-structured data using real-world datasets and gain hands-on exposure to the issues and challenges of working with noisy and "dirty" real-world data. ? Understand design considerations for scalability and performance in web-scale Spark application architectures. Who This Book Is For If you are a developer, engineer, or an architect and want to learn how to use Apache Spark in a web-scale project, then this is the book for you. It is assumed that you have prior knowledge of SQL querying. A basic programming knowledge with Scala, Java, R, or Python is all you need to get started with this book. What You Will Learn ? Familiarize yourself with Spark SQL programming, including working with DataFrame/Dataset API and SQL ? Perform a series of hands-on exercises with different types of data sources, including CSV, JSON, Avro, MySQL, and MongoDB ? Perform data quality checks, data visualization, and basic statistical analysis tasks ? Perform data munging tasks on publically available datasets ? Learn how to use Spark SQL and Apache Kafka to build streaming applications ? Learn key performance-tuning tips and tricks in Spark SQL applications ? Learn key architectural components and patterns in large-scale Spark SQL applications In Detail In the past year, Apache Spark has been increasingly adopted for the development of distributed applications. Spark SQL APIs provide an optimized interface that helps developers build such applications quickly and easily. However, designing web-scale production applications using Spark SQL APIs can be a complex task. Hence, understanding the design and implementation best practices before you start your project will help you avoid these problems. This book gives an insight into the engineering practices used to design and build real-world, Spark-based applications. The book's hands-on examples will give you the required confidence to work on any future projects you encounter in Spark SQL. It starts by familiarizing you with data exploration and data munging tasks using Spark SQL and Scala. Extensive code examples will help you understand the methods used to implement typical use-cases for various types of applications. You will get a walkthrough of the key concepts and terms that are common to streaming, machine learning, and graph applications. You will also learn key performance-tuning details including Cost Based Optimization (Spark 2.2) in Spark SQL applications. Finally, you will move on to learning how such systems are architected and deployed for a successful delivery of your project. Style and approach This book is a hands-on guide to designing, building, and deploying Spark SQL-centric production applications at scale.

Create robust and maintainable Java applications using the functional style of programmingAbout This BookExplore how you can blend object-oriented and functional programming styles in JavaUse lambda expressions to write flexible and succinct codeA tutorial that strengthens your fundamentals in functional programming techniques to enhance your applications Who This Book Is For If you are a Java developer with object-oriented experience and want to use a functional programming approach in your applications, then this book is for you. All you need to get started is familiarity with basic Java object-oriented programming concepts.What You Will LearnUse lambda expressions to simplyfy codeUse function composition to achieve code fluencyApply streams to simply implementations and achieve parallelismIncorporate recursion to support an application’s functionalityProvide more robust implementations using OptionalsImplement design patterns with less codeRefactor object-oriented code to create a functional solutionUse debugging and testing techniques specific to functional programs In Detail Functional programming is an increasingly popular technology that allows you to simplify many tasks that are often cumbersome and awkward using an object-oriented approach. It is important to understand this approach and know how and when to apply it. Functional programming requires a different mindset, but once mastered it can be very rewarding. This book simplifies the learning process as a problem is described followed by its implementation using an object-oriented approach and then a solution is provided using appropriate functional programming techniques. Writing succinct and maintainable code is facilitated by many functional programming techniques including lambda expressions and streams. In this book, you will see numerous examples of how these techniques can be applied starting with an introduction to lambda expressions. Next, you will see how they can replace older approaches and be combined to achieve surprisingly elegant solutions to problems. This is followed by the investigation of related concepts such as the Optional class and monads, which offer an additional approach to handle problems. Design patterns have been instrumental in solving common problems. You will learn how these are enhanced with functional techniques. To transition from an object-oriented approach to a functional one, it is useful to have IDE support. IDE tools to refactor, debug, and test functional programs are demonstrated through the chapters. The end of the book brings together many of these functional programming techniques to create a more comprehensive application. You will find this book a very useful resource to learn and apply functional programming techniques in Java.Style and approach In this tutorial, each chapter starts with an introduction to the terms and concepts covered in that chapter. It quickly progresses to contrast an object-oriented approach with a functional approach using numerous code examples.

Leverage the power of Scala with different tools to build scalable, robust data science applicationsAbout This BookA complete guide for scalable data science solutions, from data ingestion to data visualizationDeploy horizontally scalable data processing pipelines and take advantage of web frameworks to build engaging visualizationsBuild functional, type-safe routines to interact with relational and NoSQL databases with the help of tutorials and examples providedWho This Book Is ForIf you are a Scala developer or data scientist, or if you want to enter the field of data science, then this book will give you all the tools you need to implement data science solutions.What You Will LearnTransform and filter tabular data to extract features for machine learningImplement your own algorithms or take advantage of MLLib’s extensive suite of models to build distributed machine learning pipelinesRead, transform, and write data to both SQL and NoSQL databases in a functional mannerWrite robust routines to query web APIsRead data from web APIs such as the GitHub or Twitter APIUse Scala to interact with MongoDB, which offers high performance and helps to store large data sets with uncertain query requirementsCreate Scala web applications that couple with JavaScript libraries such as D3 to create compelling interactive visualizationsDeploy scalable parallel applications using Apache Spark, loading data from HDFS or HiveIn DetailScala is a multi-paradigm programming language (it supports both object-oriented and functional programming) and *ing language used to build applications for the JVM. Languages such as R, Python, Java, and so on are mostly used for data science. It is particularly good at analyzing large sets of data without any significant impact on performance and thus Scala is being adopted by many developers and data scientists. Data scientists might be aware that building applications that are truly scalable is hard. Scala, with its powerful functional libraries for interacting with databases and building scalable frameworks will give you the tools to construct robust data pipelines.This book will introduce you to the libraries for ingesting, storing, manipulating, processing, and visualizing data in Scala.Packed with real-world examples and interesting data sets, this book will teach you to ingest data from flat files and web APIs and store it in a SQL or NoSQL database. It will show you how to design scalable architectures to process and modelling your data, starting from simple concurrency constructs such as parallel collections and futures, through to actor systems and Apache Spark. As well as Scala’s emphasis on functional structures and immutability, you will learn how to use the right parallel construct for the job at hand, minimizing development time without compromising scalability. Finally, you will learn how to build beautiful interactive visualizations using web frameworks.This book gives tutorials on some of the most common Scala libraries for data science, allowing you to quickly get up to speed with building data science and data engineering solutions.Style and approachA tutorial with complete examples, this book will give you the tools to start building useful data engineering and data science solutions straightaway

Learn Database design, development,and administration using the feature-rich SQL Developer 4.1 interfaceAbout This BookExplore all the SQL Developer 4.1 features useful for Oracle database developers, architects, and administratorsUnderstand how this free tool from Oracle has evolved over the years and has become a complete tool that makes life easy for Oracle and third-party database usersThe author, Ajith Narayanan, has a total of 10+ years of work experience as an Oracle [APPS] DBAWho This Book Is ForThis book is intended for Oracle developers who are responsible for database management. You are expected to have programming knowledge of SQL and PL/SQL, and must be familiar with basic Oracle database concepts.What You Will LearnInstall and navigate through all the advanced features of SQL Developer that were introduced in version 4.1Browse, create, edit, and delete (drop) database objectsUse the SQL worksheet to run SQL statements and *s, edit and debug PL/SQL code, manipulate and export (unload) dataCarry out all DBA-related activities such as exporting/importing, tuning, and analyzing database performance issuesQuickly analyze, create, and edit the data model using data modelerExtend the SQL developer capabilities by exploring the APEX related pages, enabling and working with RESTful servicesUse the available reports and create new custom reports with custom *sGrasp how to connect to third-party databases and work smoothly with themIn DetailAt times, DBAs support 100s of databases at work. In such scenarios, using a command-line tool like putty adds to the difficulty, while SQL Developer makes the life of a developer, DBA, or DB architect easier by providing a graphical user interface equipped with features that can bolster and enhance the user experience and boost efficiency. Features such as DBA panel, Reports, Data Modeler, and Data Miner are just a few examples of its rich features, and its support for APEX, REST Services, timesten, and third-party database drivers demonstrate its extensibility.You may be a newbie to databases or a seasoned database expert, either way this book will help you understand the database structure and the different types of objects that organize enterprise data in an efficient manner. This book introduces the features of the SQL Developer 4.1 tool in an incremental fashion, starting with installing them, making the database connections, and using the different panels. By sequentially walking through the steps in each chapter, you will quickly master SQL Developer 4.1.Style and approachThis book follows a step-by-step approach and is in a conversational and easy-to-follow style. Screenshots , and detailed explanations of the basic and advanced features of SQL Developer 4.1 that will make your work and life easy.

Master the art of machine learning with .NET and gain insight into real-world applications About This Book Based on .NET framework 4.6.1, includes examples on ASP.NET Core 1.0 Set up your business application to start using machine learning techniques Familiarize the user with some of the more common .NET libraries for machine learning Implement several common machine learning techniques Evaluate, optimize and adjust machine learning models Who This Book Is For This book is targeted at .Net developers who want to build complex machine learning systems. Some basic understanding of data science is required. What You Will Learn Write your own machine learning applications and experiments using the latest .NET framework, including .NET Core 1.0 Set up your business application to start using machine learning. Accurately predict the future using regressions. Discover hidden patterns using decision trees. Acquire, prepare, and combine datasets to drive insights. Optimize business throughput using Bayes Classifier. Discover (more) hidden patterns using KNN and Na?ve Bayes. Discover (even more) hidden patterns using K-Means and PCA. Use Neural Networks to improve business decision making while using the latest ASP.NET technologies. Explore “Big Data”, distributed computing, and how to deploy machine learning models to IoT devices – making machines self-learning and adapting Along the way, learn about Open Data, Bing maps, and MBrace In Detail .Net is one of the widely used platforms for developing applications. With the meteoric rise of Machine learning, developers are now keen on finding out how can they make their .Net applications smarter. Also, .NET developers are interested into moving into the world of devices and how to apply machine learning techniques to, well, machines. This book is packed with real-world examples to easily use machine learning techniques in your business applications. You will begin with introduction to F# and prepare yourselves for machine learning using .NET framework. You will be writing a simple linear regression model using an example which predicts sales of a product. Forming a base with the regression model, you will start using machine learning libraries available in .NET framework such as Math.NET, Numl.NET and Accord.NET with the help of a sample application. You will then move on to writing multiple linear regressions and logistic regressions. You will learn what is open data and the awesomeness of type providers. Next, you are going to address some of the issues that we have been glossing over so far and take a deep dive into obtaining, cleaning, and organizing our data. You will compare the utility of building a KNN and Naive Bayes model to achieve best possible results. Implementation of Kmeans and PCA using Accord.NET and Numl.NET libraries is covered with the help of an example application. We will then look at many of issues confronting creating real-world machine learning models like overfitting and how to combat them using confusion matrixes, scaling, normalization, and feature selection. You will now enter into the world of Neural Networks and move your line of business application to a hybrid scientific application. After you have covered all the above machine learning models, you will see how to deal with very large datasets using MBrace and how to deploy machine learning models to Internet of Thing (IoT) devices so that the machine can learn and adapt on the fly. Style and approach This book will guide you in learning everything about how to tackle the flood of data being encountered these days in your .NET applications with the help of popular machine learning libraries offered by the .NET framework.