Biznes IT
Silas Toms, Paul Crickard, Eric van Rees
Python comes with a host of open source libraries and tools that help you work on professional geoprocessing tasks without investing in expensive tools. This book will introduce Python developers, both new and experienced, to a variety of new code libraries that have been developed to perform geospatial analysis, statistical analysis, and data management. This book will use examples and code snippets that will help explain how Python 3 differs from Python 2, and how these new code libraries can be used to solve age-old problems in geospatial analysis.You will begin by understanding what geoprocessing is and explore the tools and libraries that Python 3 offers. You will then learn to use Python code libraries to read and write geospatial data. You will then learn to perform geospatial queries within databases and learn PyQGIS to automate analysis within the QGIS mapping suite. Moving forward, you will explore the newly released ArcGIS API for Python and ArcGIS Online to perform geospatial analysis and create ArcGIS Online web maps. Further, you will deep dive into Python Geospatial web frameworks and learn to create a geospatial REST API.
Mastering Hadoop 3. Big data processing at scale to unlock unique business insights
Timothy Wong, Chanchal Singh, Manish Kumar
Apache Hadoop is one of the most popular big data solutions for distributed storage and for processing large chunks of data. With Hadoop 3, Apache promises to provide a high-performance, more fault-tolerant, and highly efficient big data processing platform, with a focus on improved scalability and increased efficiency.With this guide, you’ll understand advanced concepts of the Hadoop ecosystem tool. You’ll learn how Hadoop works internally, study advanced concepts of different ecosystem tools, discover solutions to real-world use cases, and understand how to secure your cluster. It will then walk you through HDFS, YARN, MapReduce, and Hadoop 3 concepts. You’ll be able to address common challenges like using Kafka efficiently, designing low latency, reliable message delivery Kafka systems, and handling high data volumes. As you advance, you’ll discover how to address major challenges when building an enterprise-grade messaging system, and how to use different stream processing systems along with Kafka to fulfil your enterprise goals.By the end of this book, you’ll have a complete understanding of how components in the Hadoop ecosystem are effectively integrated to implement a fast and reliable data pipeline, and you’ll be equipped to tackle a range of real-world problems in data pipelines.
Mastering IOT. Build modern IoT solutions that secure and monitor your IoT infrastructure
Colin Dow, Perry Lea
The Internet of Things (IoT) is the fastest growing technology market. Industries are embracing IoT technologies to improve operational expenses, product life, and people's well-being.We’ll begin our journey with an introduction to Raspberry Pi and quickly jump right into Python programming. We’ll learn all concepts through multiple projects, and then reinforce our learnings by creating an IoT robot car. We’ll examine modern sensor systems and focus on what their power and functionality can bring to our system. We’ll also gain insight into cloud and fog architectures, including the OpenFog standards. The Learning Path will conclude by discussing three forms of prevalent attacks and ways to improve the security of our IoT infrastructure.By the end of this Learning Path, we will have traversed the entire spectrum of technologies needed to build a successful IoT system, and will have the confidence to build, secure, and monitor our IoT infrastructure.This Learning Path includes content from the following Packt products:Internet of Things Programming Projects by Colin DowInternet of Things for Architects by Perry Lea
Mastering JIRA 7. Become an expert at using JIRA 7 through this one-stop guide! - Second Edition
Ravi Sagar
Atlassian JIRA 7 is an enterprise issue tracker system. One of its key strengths is its ability to adapt to the needs of an organization, ranging from building software products to managing your support issues.This book provides a comprehensive explanation covering all three components of JIRA 7, such as JIRA Software, JIRA Core, and Jira Service Desk. It shows you how to master the key functionalities of JIRA and its customizations and useful add-ons, and is packed with real-world examples and use cases. You will first learn how to plan for a JIRA 7 installation and fetch data. We cover JIRA reports in detail, which will help you analyze your data effectively. You can add additional features to your JIRA application by choosing one of the already built-in add-ons or building a new one to suit your needs. Then you'll find out about implementing Agile methodologies in JIRA by creating Scrum and Kanban boards. We'll teach you how to integrate your JIRA Application with other tools such as Confluence, SVN, Git, and more, which will help you extend your application. Finally, we'll explore best practices and troubleshooting techniques to help you find out what went wrong and understand how to fix it.
Giuseppe Bonaccorso
Mastering Machine Learning Algorithms, Second Edition helps you harness the real power of machine learning algorithms in order to implement smarter ways of meeting today's overwhelming data needs. This newly updated and revised guide will help you master algorithms used widely in semi-supervised learning, reinforcement learning, supervised learning, and unsupervised learning domains.You will use all the modern libraries from the Python ecosystem – including NumPy and Keras – to extract features from varied complexities of data. Ranging from Bayesian models to the Markov chain Monte Carlo algorithm to Hidden Markov models, this machine learning book teaches you how to extract features from your dataset, perform complex dimensionality reduction, and train supervised and semi-supervised models by making use of Python-based libraries such as scikit-learn. You will also discover practical applications for complex techniques such as maximum likelihood estimation, Hebbian learning, and ensemble learning, and how to use TensorFlow 2.x to train effective deep neural networks.By the end of this book, you will be ready to implement and solve end-to-end machine learning problems and use case scenarios.
Giuseppe Bonaccorso
Machine learning is a subset of AI that aims to make modern-day computer systems smarter and more intelligent. The real power of machine learning resides in its algorithms, which make even the most difficult things capable of being handled by machines. However, with the advancement in the technology and requirements of data, machines will have to be smarter than they are today to meet the overwhelming data needs; mastering these algorithms and using them optimally is the need of the hour.Mastering Machine Learning Algorithms is your complete guide to quickly getting to grips with popular machine learning algorithms. You will be introduced to the most widely used algorithms in supervised, unsupervised, and semi-supervised machine learning, and will learn how to use them in the best possible manner. Ranging from Bayesian models to the MCMC algorithm to Hidden Markov models, this book will teach you how to extract features from your dataset and perform dimensionality reduction by making use of Python-based libraries such as scikit-learn v0.19.1. You will also learn how to use Keras and TensorFlow 1.x to train effective neural networks.If you are looking for a single resource to study, implement, and solve end-to-end machine learning problems and use-cases, this is the book you need.
Giuseppe Bonaccorso
Machine learning is a subset of AI that aims to make modern-day computer systems smarter and more intelligent. The real power of machine learning resides in its algorithms, which make even the most difficult things capable of being handled by machines. However, with the advancement in the technology and requirements of data, machines will have to be smarter than they are today to meet the overwhelming data needs; mastering these algorithms and using them optimally is the need of the hour.Mastering Machine Learning Algorithms is your complete guide to quickly getting to grips with popular machine learning algorithms. You will be introduced to the most widely used algorithms in supervised, unsupervised, and semi-supervised machine learning, and will learn how to use them in the best possible manner. Ranging from Bayesian models to the MCMC algorithm to Hidden Markov models, this book will teach you how to extract features from your dataset and perform dimensionality reduction by making use of Python-based libraries such as scikit-learn v0.19.1. You will also learn how to use Keras and TensorFlow 1.x to train effective neural networks.If you are looking for a single resource to study, implement, and solve end-to-end machine learning problems and use-cases, this is the book you need.
Chiheb Chebbi
Cyber security is crucial for both businesses and individuals. As systems are getting smarter, we now see machine learning interrupting computer security. With the adoption of machine learning in upcoming security products, it’s important for pentesters and security researchers to understand how these systems work, and to breach them for testing purposes. This book begins with the basics of machine learning and the algorithms used to build robust systems. Once you’ve gained a fair understanding of how security products leverage machine learning, you'll dive into the core concepts of breaching such systems. Through practical use cases, you’ll see how to find loopholes and surpass a self-learning security system. As you make your way through the chapters, you’ll focus on topics such as network intrusion detection and AV and IDS evasion. We’ll also cover the best practices when identifying ambiguities, and extensive techniques to breach an intelligent system.By the end of this book, you will be well-versed with identifying loopholes in a self-learning security system and will be able to efficiently breach a machine learning system.
Dr. Saket S.R. Mengle , Maximo Gurmendez
Amazon Web Services (AWS) is constantly driving new innovations that empower data scientists to explore a variety of machine learning (ML) cloud services. This book is your comprehensive reference for learning and implementing advanced ML algorithms in AWS cloud.As you go through the chapters, you’ll gain insights into how these algorithms can be trained, tuned, and deployed in AWS using Apache Spark on Elastic Map Reduce (EMR), SageMaker, and TensorFlow. While you focus on algorithms such as XGBoost, linear models, factorization machines, and deep nets, the book will also provide you with an overview of AWS as well as detailed practical applications that will help you solve real-world problems. Every application includes a series of companion notebooks with all the necessary code to run on AWS. In the next few chapters, you will learn to use SageMaker and EMR Notebooks to perform a range of tasks, right from smart analytics and predictive modeling through to sentiment analysis. By the end of this book, you will be equipped with the skills you need to effectively handle machine learning projects and implement and evaluate algorithms on AWS.
Cory Lesmeister
Given the growing popularity of the R-zerocost statistical programming environment, there has never been a better time to start applying ML to your data. This book will teach you advanced techniques in ML ,using? the latest code in R 3.5. You will delve into various complex features of supervised learning, unsupervised learning, and reinforcement learning algorithms to design efficient and powerful ML models. This newly updated edition is packed with fresh examples covering a range of tasks from different domains. Mastering Machine Learning with R starts by showing you how to quickly manipulate data and prepare it for analysis. You will explore simple and complex models and understand how to compare them. You’ll also learn to use the latest library support, such as TensorFlow and Keras-R, for performing advanced computations. Additionally, you’ll explore complex topics, such as natural language processing (NLP), time series analysis, and clustering, which will further refine your skills in developing applications. Each chapter will help you implement advanced ML algorithms using real-world examples. You’ll even be introduced to reinforcement learning, along with its various use cases and models. In the concluding chapters, you’ll get a glimpse into how some of these blackbox models can be diagnosed and understood. By the end of this book, you’ll be equipped with the skills to deploy ML techniques in your own projects or at work.
Cory Lesmeister
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.
Gavin Hackeling
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.
Andrea Sacca
Written in a step-by-step, tutorial style with a lot of code snippets and hands-on examples to create an advanced Magento theme from scratch, this book is tailor-made 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.
Harris M Silverman
The way you choose to interact with your employees is a critical influence on your success as a manager, as well as determining the quality of your employees’ work and the tone of your office. Your superiors will make note of how you handle matters of management, and so will your employees. Many managers, especially when they are new to the role, can find themselves struggling and reacting blindly to situations rather than calmly choosing the correct management style. It’s essential that you be well equipped to handle your role as a manager.This handy guide takes you through the various elements of management style, and shows you how to decide on the best approach to take in a variety of situations and with different types of employee. Drawing on years of management expertise, it will enable you to bring out the best in your employees.Mastering Management Styles looks at the various components of management style and shows you how to combine them in the way that best suits each type of situation you’ll face. When should you be consultative with your employees? When should you be directive? How much coaching should you offer them, and how should you do it? How do you balance the interests of your employer with those of your employees? How do you distinguish between different types of employee? All of these topics are covered in this practical instruction manual for managers, providing you with a go-to set of analytical tools and hands-on strategies that will make you a much more effective and successful manager.
Harris M Silverman
The way you choose to interact with your employees is a critical influence on your success as a manager, as well as determining the quality of your employees’ work and the tone of your office. Your superiors will make note of how you handle matters of management, and so will your employees. Many managers, especially when they are new to the role, can find themselves struggling and reacting blindly to situations rather than calmly choosing the correct management style. It’s essential that you be well equipped to handle your role as a manager.This handy guide takes you through the various elements of management style, and shows you how to decide on the best approach to take in a variety of situations and with different types of employee. Drawing on years of management expertise, it will enable you to bring out the best in your employees.Mastering Management Styles looks at the various components of management style and shows you how to combine them in the way that best suits each type of situation you’ll face. When should you be consultative with your employees? When should you be directive? How much coaching should you offer them, and how should you do it? How do you balance the interests of your employer with those of your employees? How do you distinguish between different types of employee? All of these topics are covered in this practical instruction manual for managers, providing you with a go-to set of analytical tools and hands-on strategies that will make you a much more effective and successful manager.
Deepesh Somani
Microsoft Dynamics 365 is an all-in-one business management solution that's easy to use and adapt. It helps you connect your finances, sales, service, and operations to streamline business processes, improve customer interactions, and enable growth. This book gives you all the information you need to become an expert in MS Dynamics 365.This book starts with a brief overview of the functional features of Dynamics 365. You will learn how to create Word and Excel templates using CRM data to enable customized data analysis for your organization. This book helps you understand how to use Dynamics 365 as an XRM Framework, gain a deep understanding of client-side scripting in Dynamics 365, and create client-side applications using JavaScript and the Web API.In addition to this, you will discover how to customize Dynamics 365, and quickly move on to grasp the app structure, which helps you customize Dynamics 365 better. You will also learn how Dynamics 365 can be seamlessly embedded into various productivity tools to customize them for machine learning and contextual guidance.By the end of this book, you will have mastered utilizing Dynamics 365 features through real-world scenarios.
Deepesh Somani
Microsoft Dynamics CRM is the most trusted name in enterprise-level customer relationship management. The latest version of Dynamics CRM 2016 comes with some exciting extra features guaranteed to make your life easier with Dynamics CRM. This book provides a comprehensive coverage of Dynamics CRM 2016 and helps you make your tasks much simpler while elevating you to the level of an expert.The book starts with a brief overview of the functional features and then introduces the latest features of Dynamics CRM 2016. You will learn to create Word and Excel templates, using CRM data that will enable you to provide customized data analysis for your organization. You will understand how to utilize Dynamics CRM as an XRM Framework, gain a deep understanding about client-side scripting in Dynamics CRM, and learn creating client-side applications using JavaScript and Web API. We then introduce visual control frameworks for Dynamics CRM 2016 mobile and tablet applications. Business Process Flows, Business Rules, and their enhancements are introduced. By the end of this book, you will have mastered utilizing Dynamics CRM 2016 features through real-world scenarios.
Mastering MongoDB 3.x. An expert's guide to building fault-tolerant MongoDB applications
Alex Giamas
MongoDB has grown to become the de facto NoSQL database with millions of users—from small startups to Fortune 500 companies. Addressing the limitations of SQL schema-based databases, MongoDB pioneered a shift of focus for DevOps and offered sharding and replication maintainable by DevOps teams. The book is based on MongoDB 3.x and covers topics ranging from database querying using the shell, built in drivers, and popular ODM mappers to more advanced topics such as sharding, high availability, and integration with big data sources.You will get an overview of MongoDB and how to play to its strengths, with relevant use cases. After that, you will learn how to query MongoDB effectively and make use of indexes as much as possible. The next part deals with the administration of MongoDB installations on-premise or in the cloud. We deal with database internals in the next section, explaining storage systems and how they can affect performance. The last section of this book deals with replication and MongoDB scaling, along with integration with heterogeneous data sources. By the end this book, you will be equipped with all the required industry skills and knowledge to become a certified MongoDB developer and administrator.