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Nauki przyrodnicze
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Nauki społeczne
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Popularnonaukowe i akademickie
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Poradniki
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Psychologia
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Religia
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Sport, fitness, diety
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Technika i mechanika
Kursy video
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Big Data
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Dla dzieci
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Microsoft Office
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Urządzenia mobilne
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Zarządzanie
Podcasty
Python Social Media Analytics. Analyze and visualize data from Twitter, YouTube, GitHub, and more
Siddhartha Chatterjee, Michal Krystyanczuk
Social Media platforms such as Facebook, Twitter, Forums, Pinterest, and YouTube have become part of everyday life in a big way. However, these complex and noisy data streams pose a potent challenge to everyone when it comes to harnessing them properly and benefiting from them. This book will introduce you to the concept of social media analytics, and how you can leverage its capabilities to empower your business.Right from acquiring data from various social networking sources such as Twitter, Facebook, YouTube, Pinterest, and social forums, you will see how to clean data and make it ready for analytical operations using various Python APIs. This book explains how to structure the clean data obtained and store in MongoDB using PyMongo. You will also perform web scraping and visualize data using Scrappy and Beautifulsoup. Finally, you will be introduced to different techniques to perform analytics at scale for your social data on the cloud, using Python and Spark. By the end of this book, you will be able to utilize the power of Python to gain valuable insights from social media data and use them to enhance your business processes.
Data Analysis with Python. A Modern Approach
Data Analysis with Python offers a modern approach to data analysis so that you can work with the latest and most powerful Python tools, AI techniques, and open source libraries. Industry expert David Taieb shows you how to bridge data science with the power of programming and algorithms in Python. You'll be working with complex algorithms, and cutting-edge AI in your data analysis. Learn how to analyze data with hands-on examples using Python-based tools and Jupyter Notebook. You'll find the right balance of theory and practice, with extensive code files that you can integrate right into your own data projects.Explore the power of this approach to data analysis by then working with it across key industry case studies. Four fascinating and full projects connect you to the most critical data analysis challenges you’re likely to meet in today. The first of these is an image recognition application with TensorFlow – embracing the importance today of AI in your data analysis. The second industry project analyses social media trends, exploring big data issues and AI approaches to natural language processing. The third case study is a financial portfolio analysis application that engages you with time series analysis - pivotal to many data science applications today. The fourth industry use case dives you into graph algorithms and the power of programming in modern data science. You'll wrap up with a thoughtful look at the future of data science and how it will harness the power of algorithms and artificial intelligence.
With the increasing threats of breaches and attacks on critical infrastructure, system administrators and architects can use Kali Linux 2.0 to ensure their infrastructure is secure by finding out known vulnerabilities and safeguarding their infrastructure against unknown vulnerabilities.This practical cookbook-style guide contains chapters carefully structured in three phases – information gathering, vulnerability assessment, and penetration testing for the web, and wired and wireless networks. It's an ideal reference guide if you’re looking for a solution to a specific problem or learning how to use a tool. We provide hands-on examples of powerful tools/scripts designed for exploitation.In the final section, we cover various tools you can use during testing, and we help you create in-depth reports to impress management. We provide system engineers with steps to reproduce issues and fix them.
Building Applications with Spring 5 and Vue.js 2, with its practical approach, helps you become a full-stack web developer. As well as knowing how to write frontend and backend code, a developer has to tackle all problems encountered in the application development life cycle – starting from the simple idea of an application, to the UI and technical designs, and all the way to implementation, testing, production deployment, and monitoring. With the help of this book, you'll get to grips with Spring 5 and Vue.js 2 as you learn how to develop a web application. From the initial structuring to full deployment, you’ll be guided at every step of developing a web application from scratch with Vue.js 2 and Spring 5. You’ll learn how to create different components of your application as you progress through each chapter, followed by exploring different tools in these frameworks to expedite your development cycle. By the end of this book, you’ll have gained a complete understanding of the key design patterns and best practices that underpin professional full-stack web development.
Prabhanjan Narayanachar Tattar
Statistical Analysis involves collecting and examining data to describe the nature of data that needs to be analyzed. It helps you explore the relation of data and build models to make better decisions.This book explores statistical concepts along with R and Python, which are well integrated from the word go. Almost every concept has an R code going with it which exemplifies the strength of R and applications. The R code and programs have been further strengthened with equivalent Python programs. Thus, you will first understand the data characteristics, descriptive statistics and the exploratory attitude, which will give you firm footing of data analysis. Statistical inference will complete the technical footing of statistical methods. Regression, linear, logistic modeling, and CART, builds the essential toolkit. This will help you complete complex problems in the real world.You will begin with a brief understanding of the nature of data and end with modern and advanced statistical models like CART. Every step is taken with DATA and R code, and further enhanced by Python.The data analysis journey begins with exploratory analysis, which is more than simple, descriptive, data summaries. You will then apply linear regression modeling, and end with logistic regression, CART, and spatial statistics.By the end of this book you will be able to apply your statistical learning in major domains at work or in your projects.
Learning Redux. Write maintainable, consistent, and easy-to-test web applications
The book starts with a short introduction to the principles and the ecosystem of Redux, then moves on to show how to implement the basic elements of Redux and put them together. Afterward, you are going to learn how to integrate Redux with other frameworks, such as React and Angular.Along the way, you are going to develop a blog application. To practice developing growing applications with Redux, we are going to start from nothing and keep adding features to our application throughout the book. You are going to learn how to integrate and use Redux DevTools to debug applications, and access external APIs with Redux. You are also going to get acquainted with writing tests for all elements of a Redux application. Furthermore, we are going to cover important concepts in web development, such as routing, user authentication, and communication with a backend serverAfter explaining how to use Redux and how powerful its ecosystem can be, the book teaches you how to make your own abstractions on top of Redux, such as higher-order reducers and middleware.By the end of the book, you are going to be able to develop and maintain Redux applications with ease. In addition to learning about Redux, you are going be familiar with its ecosystem, and learn a lot about JavaScript itself, including best practices and patterns.
The Spring framework provides great flexibility for Java development, which also results in tedious configuration work. Spring Boot addresses the configuration difficulties of Spring and makes it easy to create standalone, production-grade Spring-based applications.This practical guide makes the existing development process more efficient. Spring Boot Cookbook 2.0 Second Edition smartly combines all the skills and expertise to efficiently develop, test, deploy, and monitor applications using Spring Boot on premise and in the cloud. We start with an overview of the important Spring Boot features you will learn to create a web application for a RESTful service. Learn to fine-tune the behavior of a web application by learning about custom routes and asset paths and how to modify routing patterns. Address the requirements of a complex enterprise application and cover the creation of custom Spring Boot starters.This book also includes examples of the new and improved facilities available to create various kinds of tests introduced in Spring Boot 1.4 and 2.0, and gain insights into Spring Boot DevTools. Explore the basics of Spring Boot Cloud modules and various Cloud starters to make applications in “Cloud Native” and take advantage of Service Discovery and Circuit Breakers.
Python Network Programming. Conquer all your networking challenges with the powerful Python language
Abhishek Ratan, Eric Chou, Pradeeban Kathiravelu, Dr. M. O. Faruque Sarker
This Learning Path highlights major aspects of Python network programming such as writing simple networking clients, creating and deploying SDN and NFV systems, and extending your network with Mininet. You’ll also learn how to automate legacy and the latest network devices. As you progress through the chapters, you’ll use Python for DevOps and open source tools to test, secure, and analyze your network. Toward the end, you'll develop client-side applications, such as web API clients, email clients, SSH, and FTP, using socket programming.By the end of this Learning Path, you will have learned how to analyze a network's security vulnerabilities using advanced network packet capture and analysis techniques. This Learning Path includes content from the following Packt products:• Practical Network Automation by Abhishek Ratan • Mastering Python Networking by Eric Chou • Python Network Programming Cookbook, Second Edition by Pradeeban Kathiravelu, Dr. M. O. Faruque Sarker