Informatyka
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Abhishek Agarwal
QlikView is one of the market leaders when it comes to building effective Business Intelligence solutions. This book will show how you can leverage its power to build your own dashboards to tell your own data story.The book starts with showing you how to connect your data to QlikView and create your own QlikView application. You will learn how to add data from multiple sources, create a data model by joining data, and then review it on the front end. You will work with QlikView components such as charts, list boxes, input boxes, and text objects to create stunning visualizations that help give actionable business insights. You will also learn how to perform analysis on your data in QlikView and master the various types of security measures to be taken in QlikView.By the end of this book, you will have all the essential knowledge required for insightful data storytelling and creating useful BI dashboards using QlikView.
Chris Beeley
Although vanilla Shiny applications look attractive with some layout flexibility, you may still want to have more control over how the interface is laid out to produce a dashboard. Hands-On Dashboard Development with Shiny helps you incorporate this in your applications.The book starts by guiding you in producing an application based on the diamonds dataset included in the ggplot2 package. You’ll create a single application, but the interface will be reskinned and rebuilt throughout using different methods to illustrate their uses and functions using HTML, CSS, and JavaScript. You will also learn to develop an application that creates documents and reports using R Markdown. Furthermore, the book demonstrates the use of HTML templates and the Bootstrap framework. Moving along, you will learn how to produce dashboards using the Shiny command and dashboard package. Finally, you will learn how to lay out applications using a wide range of built-in functions.By the end of the book, you will have an understanding of the principles that underpin layout in Shiny applications, including sections of HTML added to a vanilla Shiny application, HTML interfaces written from scratch, dashboards, navigation bars, and interfaces.
Frank Kane
Join Frank Kane, who worked on Amazon and IMDb’s machine learning algorithms, as he guides you on your first steps into the world of data science. Hands-On Data Science and Python Machine Learning gives you the tools that you need to understand and explore the core topics in the field, and the confidence and practice to build and analyze your own machine learning models. With the help of interesting and easy-to-follow practical examples, Frank Kane explains potentially complex topics such as Bayesian methods and K-means clustering in a way that anybody can understand them.Based on Frank’s successful data science course, Hands-On Data Science and Python Machine Learning empowers you to conduct data analysis and perform efficient machine learning using Python. Let Frank help you unearth the value in your data using the various data mining and data analysis techniques available in Python, and to develop efficient predictive models to predict future results. You will also learn how to perform large-scale machine learning on Big Data using Apache Spark. The book covers preparing your data for analysis, training machine learning models, and visualizing the final data analysis.
Yoon Hyup Hwang
Regardless of company size, the adoption of data science and machine learning for marketing has been rising in the industry. With this book, you will learn to implement data science techniques to understand the drivers behind the successes and failures of marketing campaigns. This book is a comprehensive guide to help you understand and predict customer behaviors and create more effectively targeted and personalized marketing strategies.This is a practical guide to performing simple-to-advanced tasks, to extract hidden insights from the data and use them to make smart business decisions. You will understand what drives sales and increases customer engagements for your products. You will learn to implement machine learning to forecast which customers are more likely to engage with the products and have high lifetime value. This book will also show you how to use machine learning techniques to understand different customer segments and recommend the right products for each customer. Apart from learning to gain insights into consumer behavior using exploratory analysis, you will also learn the concept of A/B testing and implement it using Python and R.By the end of this book, you will be experienced enough with various data science and machine learning techniques to run and manage successful marketing campaigns for your business.
Dr. Basant Agarwal, Benjamin Baka
Data structures allow you to store and organize data efficiently. They are critical to any problem, provide a complete solution, and act like reusable code. Hands-On Data Structures and Algorithms with Python teaches you the essential Python data structures and the most common algorithms for building easy and maintainable applications.This book helps you to understand the power of linked lists, double linked lists, and circular linked lists. You will learn to create complex data structures, such as graphs, stacks, and queues. As you make your way through the chapters, you will explore the application of binary searches and binary search trees, along with learning common techniques and structures used in tasks such as preprocessing, modeling, and transforming data. In the concluding chapters, you will get to grips with organizing your code in a manageable, consistent, and extendable way. You will also study how to bubble sort, selection sort, insertion sort, and merge sort algorithms in detail.By the end of the book, you will have learned how to build components that are easy to understand, debug, and use in different applications. You will get insights into Python implementation of all the important and relevant algorithms.
Claus Matzinger
Rust has come a long way and is now utilized in several contexts. Its key strengths are its software infrastructure and resource-constrained applications, including desktop applications, servers, and performance-critical applications, not forgetting its importance in systems' programming. This book will be your guide as it takes you through implementing classic data structures and algorithms in Rust, helping you to get up and running as a confident Rust programmer. The book begins with an introduction to Rust data structures and algorithms, while also covering essential language constructs. You will learn how to store data using linked lists, arrays, stacks, and queues. You will also learn how to implement sorting and searching algorithms. You will learn how to attain high performance by implementing algorithms to string data types and implement hash structures in algorithm design. The book will examine algorithm analysis, including Brute Force algorithms, Greedy algorithms, Divide and Conquer algorithms, Dynamic Programming, and Backtracking. By the end of the book, you will have learned how to build components that are easy to understand, debug, and use in different applications.
Christian Cote, Michelle Gutzait, Giuseppe Ciaburro
ETL is one of the essential techniques in data processing. Given data is everywhere, ETL will always be the vital process to handle data from different sources.Hands-On Data Warehousing with Azure Data Factory starts with the basic concepts of data warehousing and ETL process. You will learn how Azure Data Factory and SSIS can be used to understand the key components of an ETL solution. You will go through different services offered by Azure that can be used by ADF and SSIS, such as Azure Data Lake Analytics, Machine Learning and Databrick’s Spark with the help of practical examples. You will explore how to design and implement ETL hybrid solutions using different integration services with a step-by-step approach. Once you get to grips with all this, you will use Power BI to interact with data coming from different sources in order to reveal valuable insights.By the end of this book, you will not only learn how to build your own ETL solutions but also address the key challenges that are faced while building them.
Christian Cote, Michelle Gutzait, Giuseppe Ciaburro
ETL is one of the essential techniques in data processing. Given data is everywhere, ETL will always be the vital process to handle data from different sources.Hands-On Data Warehousing with Azure Data Factory starts with the basic concepts of data warehousing and ETL process. You will learn how Azure Data Factory and SSIS can be used to understand the key components of an ETL solution. You will go through different services offered by Azure that can be used by ADF and SSIS, such as Azure Data Lake Analytics, Machine Learning and Databrick’s Spark with the help of practical examples. You will explore how to design and implement ETL hybrid solutions using different integration services with a step-by-step approach. Once you get to grips with all this, you will use Power BI to interact with data coming from different sources in order to reveal valuable insights.By the end of this book, you will not only learn how to build your own ETL solutions but also address the key challenges that are faced while building them.
Micheal Lanham
The number of applications of deep learning and neural networks has multiplied in the last couple of years. Neural nets has enabled significant breakthroughs in everything from computer vision, voice generation, voice recognition and self-driving cars. Game development is also a key area where these techniques are being applied. This book will give an in depth view of the potential of deep learning and neural networks in game development. We will take a look at the foundations of multi-layer perceptron’s to using convolutional and recurrent networks. In applications from GANs that create music or textures to self-driving cars and chatbots. Then we introduce deep reinforcement learning through the multi-armed bandit problem and other OpenAI Gym environments.As we progress through the book we will gain insights about DRL techniques such as Motivated Reinforcement Learning with Curiosity and Curriculum Learning. We also take a closer look at deep reinforcement learning and in particular the Unity ML-Agents toolkit. By the end of the book, we will look at how to apply DRL and the ML-Agents toolkit to enhance, test and automate your games or simulations. Finally, we will cover your possible next steps and possible areas for future learning.