Grasp machine learning concepts, techniques, and algorithms with the help of real-world examples using Python libraries such as TensorFlow and scikit-learn Key Features * Exploit the power of Python to explore the world of data mining and data analytics * Discover machine learning algorithms to solve complex challenges faced by data scientists today * Use Python libraries such as TensorFlow and Keras to create smart cognitive actions for your projects Book Description The surge in interest in machine learning (ML) is due to the fact that it revolutionizes automation by learning patterns in data and using them to make predictions and decisions. If you’re interested in ML, this book will serve as your entry point to ML. Python Machine Learning By Example begins with an introduction to important ML concepts and implementations using Python libraries. Each chapter of the book walks you through an industry adopted application. You’ll implement ML techniques in areas such as exploratory data analysis, feature engineering, and natural language processing (NLP) in a clear and easy-to-follow way. With the help of this extended and updated edition, you’ll understand how to tackle data-driven problems and implement your solutions with the powerful yet simple Python language and popular Python packages and tools such as TensorFlow, scikit-learn, gensim, and Keras. To aid your understanding of popular ML algorithms, the book covers interesting and easy-to-follow examples such as news topic modeling and classification, spam email detection, stock price forecasting, and more. By the end of the book, you’ll have put together a broad picture of the ML ecosystem and will be well-versed with the best practices of applying ML techniques to make the most out of new opportunities. What you will learn * Understand the important concepts in machine learning and data science * Use Python to explore the world of data mining and analytics * Scale up model training using varied data complexities with Apache Spark * Delve deep into text and NLP using Python libraries such NLTK and gensim * Select and build an ML model and evaluate and optimize its performance * Implement ML algorithms from scratch in Python, TensorFlow, and scikit-learn Who this book is for If you’re a machine learning aspirant, data analyst, or data engineer highly passionate about machine learning and want to begin working on ML assignments, this book is for you. Prior knowledge of Python coding is assumed and basic familiarity with statistical concepts will be beneficial although not necessary.

Explore Jira Software to manage your projects proficiently About This Book ? Plan and manage projects effortlessly with Jira Software by integrating it with other applications ? Improve your team's performance with Scrum and Kanban, together with agile methodology ? Easy-to-follow learning guide to install Jira Software and understand how it fits in with Atlassian Jira Who This Book Is For If you want to get started with Jira Software and learn how to run your Jira projects the agile way, then this is the perfect book for you. You will need to be familiar with the basics of Jira, both from an end user's and an administrator's perspective. Experience with workflows, custom fields, and other administrative functions of Jira will be useful. What You Will Learn ? Understand the basics and agile methodologies of Jira software ? Use Jira Software in a Scrum environment ? Manage and run Jira Software projects beyond the out of box Scrum and Kanban way ? Combine Scrum and Kanban and use other project management options beyond just agile ? Customize Jira Software’s various features and options as per your requirements ? Work with Jira Agile offline, and plan and forecast projects with agile portfolio ? Integrate Jira Agile with Confluence and Bitbucket In Detail Jira Software is an agile project management tool that supports any agile methodology, be it scrum, Kanban, or your own unique flavour. From agile boards to reports, you can plan, track, and manage all your agile software development projects from a single tool. Jira Software brings the power of agile methodology to Atlassian Jira. This second edition of JIRA Agile Essentials, will help you dive straight into the action, exploring critical agile terminologies and concepts in the context of Jira Software. You will learn how to plan, track, and release great software. This book will teach you how to install and run Jira Software and set it up to run with Scrum and Kanban. It will also teach you to use Jira Software your way and run projects beyond the out-of-box Scrum and Kanban way, including a hybrid approach of both the methodologies and other options that come with Jira Software. Later, you will learn how to integrate it with the tools you are already using and enhance Jira with add-ons such as Confluence. You will learn to stay connected with your team from anywhere to ensure great development. Jira Software has numerous deployment options in the cloud, on your own infrastructure, or at a massive scale. You will be introduced to Bitbucket, Atlassian’s distributed version control system, which integrates seamlessly with Jira, allowing your team to work within the two applications as one harmonious environment. With this practical guide, you will develop a great working knowledge of Jira Software and your project management will become much more efficient. Style and approach This practical book explains Jira Software with the help of detailed examples in a step-by- step manner.

Learn to use IPython and Jupyter Notebook for your data analysis and visualization work. About This Book ? Leverage the Jupyter Notebook for interactive data science and visualization ? Become an expert in high-performance computing and visualization for data analysis and scientific modeling ? A comprehensive coverage of scientific computing through many hands-on, example-driven recipes with detailed, step-by-step explanations Who This Book Is For This book is intended for anyone interested in numerical computing and data science: students, researchers, teachers, engineers, analysts, and hobbyists. A basic knowledge of Python/NumPy is recommended. Some skills in mathematics will help you understand the theory behind the computational methods. What You Will Learn ? Master all features of the Jupyter Notebook ? Code better: write high-quality, readable, and well-tested programs; profile and optimize your code; and conduct reproducible interactive computing experiments ? Visualize data and create interactive plots in the Jupyter Notebook ? Write blazingly fast Python programs with NumPy, ctypes, Numba, Cython, OpenMP, GPU programming (CUDA), parallel IPython, Dask, and more ? Analyze data with Bayesian or frequentist statistics (Pandas, PyMC, and R), and learn from actual data through machine learning (scikit-learn) ? Gain valuable insights into signals, images, and sounds with SciPy, scikit-image, and OpenCV ? Simulate deterministic and stochastic dynamical systems in Python ? Familiarize yourself with math in Python using SymPy and Sage: algebra, analysis, logic, graphs, geometry, and probability theory In Detail Python is one of the leading open source platforms for data science and numerical computing. IPython and the associated Jupyter Notebook offer efficient interfaces to Python for data analysis and interactive visualization, and they constitute an ideal gateway to the platform. IPython Interactive Computing and Visualization Cookbook, Second Edition contains many ready-to-use, focused recipes for high-performance scientific computing and data analysis, from the latest IPython/Jupyter features to the most advanced tricks, to help you write better and faster code. You will apply these state-of-the-art methods to various real-world examples, illustrating topics in applied mathematics, scientific modeling, and machine learning. The first part of the book covers programming techniques: code quality and reproducibility, code optimization, high-performance computing through just-in-time compilation, parallel computing, and graphics card programming. The second part tackles data science, statistics, machine learning, signal and image processing, dynamical systems, and pure and applied mathematics. Style and approach IPython Interactive Computing and Visualization Cookbook, Second Edition is a practical, hands-on book that will teach you how to analyze and visualize all kinds of data in the Jupyter Notebook.

Orchestrate your cloud infrastructure About This Book ? Recipe-based approach to install and configure cloud resources using Ansible ? Covers various cloud-related modules and their functionalities ? Includes deployment of a sample application to the cloud resources that we create ? Learn the best possible way to manage and automate your cloud infrastructure Who This Book Is For If you are a system administrator, infrastructure engineer, or a DevOps engineer who wants to obtain practical knowledge about Ansible and its cloud deliverables, then this book is for you. Recipes in this book are designed for people who would like to manage their cloud infrastructures efficiently using Ansible, which is regarded as one of the best tools for cloud management and automation. What You Will Learn ? Use Ansible Vault to protect secrets ? Understand how Ansible modules interact with cloud providers to manage resources ? Build cloud-based resources for your application ? Create resources beyond simple virtual machines ? Write tasks that can be reused to create resources multiple times ? Work with self-hosted clouds such as OpenStack and Docker ? Deploy a multi-tier application on various cloud providers In Detail Ansible has a large collection of inbuilt modules to manage various cloud resources. The book begins with the concepts needed to safeguard your credentials and explain how you interact with cloud providers to manage resources. Each chapter begins with an introduction and prerequisites to use the right modules to manage a given cloud provider. Learn about Amazon Web Services, Google Cloud, Microsoft Azure, and other providers. Each chapter shows you how to create basic computing resources, which you can then use to deploy an application. Finally, you will be able to deploy a sample application to demonstrate various usage patterns and utilities of resources. Style and approach This book will help readers get started with Ansible cloud modules. It has code snippets and diagrams along with real world examples that will help you move ahead easily. Using real world scenarios, you will learn to deploy an application to cloud resources.

Familiarize yourself with probabilistic graphical models through real-world problems and illustrative code examples in R About This Book Predict and use a probabilistic graphical models (PGM) as an expert system Comprehend how your computer can learn Bayesian modeling to solve real-world problems Know how to prepare data and feed the models by using the appropriate algorithms from the appropriate R package Who This Book Is For This book is for anyone who has to deal with lots of data and draw conclusions from it, especially when the data is noisy or uncertain. Data scientists, machine learning enthusiasts, engineers, and those who curious about the latest advances in machine learning will find PGM interesting. What You Will Learn Understand the concepts of PGM and which type of PGM to use for which problem Tune the model’s parameters and explore new models automatically Understand the basic principles of Bayesian models, from simple to advanced Transform the old linear regression model into a powerful probabilistic model Use standard industry models but with the power of PGM Understand the advanced models used throughout today's industry See how to compute posterior distribution with exact and approximate inference algorithms In Detail Probabilistic graphical models (PGM, also known as graphical models) are a marriage between probability theory and graph theory. Generally, PGMs use a graph-based representation. Two branches of graphical representations of distributions are commonly used, namely Bayesian networks and Markov networks. R has many packages to implement graphical models. We’ll start by showing you how to transform a classical statistical model into a modern PGM and then look at how to do exact inference in graphical models. Proceeding, we’ll introduce you to many modern R packages that will help you to perform inference on the models. We will then run a Bayesian linear regression and you’ll see the advantage of going probabilistic when you want to do prediction. Next, you’ll master using R packages and implementing its techniques. Finally, you’ll be presented with machine learning applications that have a direct impact in many fields. Here, we’ll cover clustering and the discovery of hidden information in big data, as well as two important methods, PCA and ICA, to reduce the size of big problems. Style and approach This book gives you a detailed and step-by-step explanation of each mathematical concept, which will help you build and analyze your own machine learning models and apply them to real-world problems. The mathematics is kept simple and each formula is explained thoroughly.

Unleash Python and take your small readers on an adventurous ride through the world of programming About This Book Learn to start using Python for some simple programming tasks such as doing easy mathematical calculations. Use logic and control loops to build a nice interesting game. Get to grips with working with data and, once you're comfortable with that, you'll be introduced to Pygame, which will help you wrap up the book with a cool game. Who This Book Is For This book is for kids (aged 10 and over). This is book is intended for absolute beginners who lack any knowledge of computing or programming languages and want to get started in the world of programming. What You Will Learn Start fiddling with Python's variables, build functions and interact with users Build your own calculator using the Math Library Train Python to make logical decisions Work with moving 2D objects on-screen Understand the Pygame Library and build your very own game! Write a cool program to manage inventories in your backpack In Detail Kids are always the most fast-paced and enthusiastic learners, and are naturally willing to build stuff that looks like magic at the end (when it works!). Programming can be one such magic. Being able to write a program that works helps them feel they've really achieved something. Kids today are very tech-savvy and cannot wait to enter the fast-paced digital world. Because Python is one of the most popular languages and has a syntax that is quite simple to understand, even kids are eager to use it as a stepping stone to learning programming languages. This book will cover projects that are simple and fun, and teach kids how to write Python code that works. The book will teach the basics of Python programming, installation, and so on and then will move on to projects. A total of three projects, with each and every step explained carefully, without any assumption of previous experience. Style and approach The book will take a light approach in guiding the little readers through the world of Python. The main idea is to teach by example and let the readers have as much exercises to do, so that they learn faster and can apply their own ideas to the existing examples. The book should get them thinking, by the end, on where they can go next with such a powerful tool at their disposal.

Harness the power of multiple computers using Python through this fast-paced informative guide About This Book You'll learn to write data processing programs in Python that are highly available, reliable, and fault tolerant Make use of Amazon Web Services along with Python to establish a powerful remote computation system Train Python to handle data-intensive and resource hungry applications Who This Book Is For This book is for Python developers who have developed Python programs for data processing and now want to learn how to write fast, efficient programs that perform CPU-intensive data processing tasks. What You Will Learn Get an introduction to parallel and distributed computing See synchronous and asynchronous programming Explore parallelism in Python Distributed application with Celery Python in the Cloud Python on an HPC cluster Test and debug distributed applications In Detail CPU-intensive data processing tasks have become crucial considering the complexity of the various big data applications that are used today. Reducing the CPU utilization per process is very important to improve the overall speed of applications. This book will teach you how to perform parallel execution of computations by distributing them across multiple processors in a single machine, thus improving the overall performance of a big data processing task. We will cover synchronous and asynchronous models, shared memory and file systems, communication between various processes, synchronization, and more. Style and Approach This example based, step-by-step guide will show you how to make the best of your hardware configuration using Python for distributing applications.

Explore the power of React components for cutting-edge web development About This Book Learn to build better websites by creating a variety of different components in React Conceptualize the design and build maintainable web apps with the help of components A fast-paced guide to help you learn about component-based development in React Who This Book Is For This book is ideal for developers who are familiar with the basics of React and are looking for a guide to building a wide range of components as well as develop component-driven UIs. What You Will Learn How to structure an app into components Working with nested components Work with nested components Set up communication across components Style the existing components Work with Material Design as a component Render components on the server Make the best of design patterns Make the app pluggable In Detail The reader will learn how to use React and its component-based architecture in order to develop modern user interfaces. A new holistic way of thinking about UI development will establish throughout this book and the reader will discover the power of React components with many examples. After reading the book and following the example application, the reader has built a small to a mid-size application with React using a component based UI architecture. The book will take the reader through a journey to discover the benefits of component-based user interfaces over the classical MVC architecture. Throughout the book, the reader will develop a wide range of components and then bring them together to build a component-based UI. By the end of this book, readers would have learned several techniques to build powerful components and how the component-based development is beneficial over regular web development. Style and approach This book is a compact, example-driven guide that provides a step-by-step approach.

Create high availability clusters to enhance system performance using CentOS 7About This BookMaster the concepts of high performance and high availability to eliminate performance bottlenecksMaximize the uptime of services running in a CentOS 7 clusterA step-by-step guide that will provide knowledge of methods and approaches to optimize the performance of CentOS clustersWho This Book Is ForThis book is targeted at system administrators: those who want a detailed, step-by-step guide to learn how to set up a high-availability CentOS 7 cluster, and those who are looking for a reference book to help them learn or refresh the necessary skills to ensure their systems and respective resources are utilized optimally. No previous knowledge of high-availability systems is needed, though the reader is expected to have at least some degree of familiarity with any spin-off of the Fedora family of Linux distributions, preferably CentOS.What You Will LearnInstall a CentOS 7 cluster and network infrastructureConfigure firewall, networking, and clustering services and settingsSet up and test a HAC (high-availability cluster) to host an Apache web server and a MariaDB database serverMonitor performance and availabilityIdentify bottlenecks and troubleshoot issuesImprove performance and ensure high availabilityIn DetailCentOS is the enterprise level Linux OS, which is 100% binary compatible to Red Hat Enterprise Linux (RHEL). It acts as a free alternative to RedHat's commercial Linux offering, with only a change in the branding. A high performance cluster consists in a group of computers that work together as one set parallel, hence minimizing or eliminating the downtime of critical services and enhancing the performance of the application.Starting with the basic principles of clustering, you will learn the necessary steps to install a cluster with two CentOS 7 servers. We will then set up and configure the basic required network infrastructure and clustering services. Further, you will learn how to take a proactive approach to the split-brain issue by configuring the failover and fencing of the cluster as a whole and the quorum of each node individually. Further, we will be setting up HAC and HPC clusters as a web server and a database server. You will also master the art of monitoring performance and availability, identifying bottlenecks, and exploring troubleshooting techniques.At the end of the book, you’ll review performance-tuning techniques for the recently installed cluster, test performance using a payload simulation, and learn the necessary skills to ensure that the systems, and the corresponding resources and services, are being utilized to their best capacity.Style and approachAn easy-to-follow and step-by-step guide with hands-on instructions to set up real-world simple cluster scenarios that will start you on the path to building more complex applications on your own.

This book is a mini tutorial with plenty of code examples and strategies to give you many options when building your own applications.This book is meant for readers who are familiar with C/C++ programming and want to write simple programs with Kinect. The standard template library can also be used as it is simple enough to understand.

If you are a professional, student, or educator who wants to learn to use IPython Notebook as a tool for technical and scientific computing, visualization, and data analysis, this is the book for you. This book will prove valuable for anyone that needs to do computations in an agile environment.

If you are an iOS developer with experience in Objective-C, and wish to develop applications with Swift, then this book is ideal for you. Familiarity with the fundamentals of Swift is an added advantage but not a necessity.

This practical and easy-to-understand learning tutorial is one big exciting exercise for students and engineers that are always short on their schedules and want to regain some lost time with the help of Simulink.This book is aimed at students and engineers who need a quick start with Simulink. Though it's not required in order to understand how Simulink works, knowledge of physics will help the reader to understand the exercises described.

KNIME Essentials is a practical guide aimed at getting the results you want, as quickly as possible."Knime Essentials" is written for data analysts looking to quickly get up to speed using the market leader in data processing tools, KNIME. No knowledge of KNIME is required, but we will assume that you have some background in data processing.

into the world of Kivy.This book is aimed at Python developers who are familiar with Python and have a good understanding of concepts like inheritance, classes, and instances. No previous experience of Kivy is required, though some knowledge of event handling, scheduling, and user interfaces, in general, would boost your learning.

A step-by-step tutorial to help you master computer vision and mobile app development.This book is for Java developers who are new to computer vision and who would like to learn about how it is used in relation to application development. It is assumed that you have previous experience in Java, but not necessarily Android. A basic understanding of image data (for example pixels and color channels) would be helpful too. You are expected to have a mobile device running Android 2.2 (Froyo) or greater and it must have a camera

If you are an IT professional with a basic knowledge of Microsoft Azure and want to learn Azure Storage services, then this book is for you.

Get a complete walkthrough of the many interfaces available in Jenkins with the help of real-world examples to take you to the next level with Jenkins About This Book Find out how to interact with Jenkins from within Eclipse, NetBeans, and IntelliJ IDEA Develop custom solutions that act upon Jenkins information in real time A step-by-step, practical guide to help you learn about extension points in existing plugins and how to build your own plugin Who This Book Is For This book is aimed primarily at developers and administrators who are interested in taking their interaction and usage of Jenkins to the next level. The book assumes you have a working knowledge of Jenkins and programming in general, and an interest in learning about the different approaches to customizing and extending Jenkins so it fits your requirements and your environment perfectly. What You Will Learn Retrieve and act upon Jenkins information in real time Find out how to interact with Jenkins through a variety of IDEs Develop your own Form and Input validation and customization Explore how Extension points work, and develop your own Jenkins plugin See how to use the Jenkins API and command-line interface Get to know how to remotely update your Jenkins configuration Design and develop your own Information Radiator Discover how Jenkins customization can help improve quality and reduce costs In Detail Jenkins CI is the leading open source continuous integration server. It is written in Java and has a wealth of plugins to support the building and testing of virtually any project. Jenkins supports multiple Software Configuration Management tools such as Git, Subversion, and Mercurial. This book explores and explains the many extension points and customizations that Jenkins offers its users, and teaches you how to develop your own Jenkins extensions and plugins. First, you will learn how to adapt Jenkins and leverage its abilities to empower DevOps, Continuous Integration, Continuous Deployment, and Agile projects. Next, you will find out how to reduce the cost of modern software development, increase the quality of deliveries, and thereby reduce the time to market. We will also teach you how to create your own custom plugins using Extension points. Finally, we will show you how to combine everything you learned over the course of the book into one real-world scenario. Style and approach Extending Jenkins explores and explains advanced Jenkins functionality from a practical point of view, teaching you real-world skills that will help you get more from this powerful software. Each key topic is explained clearly with a practical example, and in sufficient detail so you understand the concepts and can then develop your own solutions using your preferred software and languages.

An in-depth tutorial that teaches you the basics of data-driven applications, and how to design and implement them using Ext JS.If you are an intermediate in Sencha Ext JS, "Ext JS Data-Driven Application Design" is the tutorial for you. You need to be familiar with JavaScript and have basic operational knowledge of MySQL. If you want to be able to systematically construct an application from the first step to implementation, this book will be useful for you.

This is a step-by-step tutorial that covers the basics of working with the MicroStrategy platform.If you are a BI developer who would like to use MicroStrategy to build BI apps, this book is ideal for you. This book is also for mid-management executives who need to analyze data and Excel files that are too complicated to manage. A basic concept of BI is assumed.

A practical guide, packed with illustrations, that will help you become proficient with Hudson and able to utilize it how you want.If you are a Java developer or administrator who would to like automate some of the mundane work required to build and test software and improve software quality, this is the book for you. If you are a development manager or tester, you can also benefit from learning how Hudson works by gaining some insight into test results and historical trends.