Analiza danych
Tim Pulver
MQ Telemetry Transport (MQTT) is a lightweight messaging protocol for smart devices that can be used to build exciting, highly scalable Internet of Things (IoT) projects.This book will get you started with a quick introduction to the concepts of IoT and MQTT and explain how the latter can help you build your own internet-connected prototypes. As you advance, you’ll gain insights into how microcontrollers communicate, and you'll get to grips with the different messaging protocols and techniques involved. Once you are well-versed with the essential concepts, you’ll be able to put what you’ve learned into practice by building three projects from scratch, including an automatic pet food dispenser and a smart e-ink to-do display. You’ll also discover how to present your own prototypes professionally. In addition to this, you'll learn how to use technologies from third-party web service providers, along with other rapid prototyping technologies, such as laser cutting, 3D printing, and PCB production.By the end of this book, you’ll have gained hands-on experience in using MQTT to build your own IoT prototypes.
Stefan Jansen
The explosive growth of digital data has boosted the demand for expertise in trading strategies that use machine learning (ML). This book enables you to use a broad range of supervised and unsupervised algorithms to extract signals from a wide variety of data sources and create powerful investment strategies.This book shows how to access market, fundamental, and alternative data via API or web scraping and offers a framework to evaluate alternative data. You’ll practice the ML work?ow from model design, loss metric definition, and parameter tuning to performance evaluation in a time series context. You will understand ML algorithms such as Bayesian and ensemble methods and manifold learning, and will know how to train and tune these models using pandas, statsmodels, sklearn, PyMC3, xgboost, lightgbm, and catboost. This book also teaches you how to extract features from text data using spaCy, classify news and assign sentiment scores, and to use gensim to model topics and learn word embeddings from financial reports. You will also build and evaluate neural networks, including RNNs and CNNs, using Keras and PyTorch to exploit unstructured data for sophisticated strategies.Finally, you will apply transfer learning to satellite images to predict economic activity and use reinforcement learning to build agents that learn to trade in the OpenAI Gym.
Giuseppe Ciaburro, V Kishore Ayyadevara, Alexis Perrier,...
Google Cloud Machine Learning Engine combines the services of Google Cloud Platform with the power and flexibility of TensorFlow. With this book, you will not only learn to build and train different complexities of machine learning models at scale but also host them in the cloud to make predictions.This book is focused on making the most of the Google Machine Learning Platform for large datasets and complex problems. You will learn from scratch how to create powerful machine learning based applications for a wide variety of problems by leveraging different data services from the Google Cloud Platform. Applications include NLP, Speech to text, Reinforcement learning, Time series, recommender systems, image classification, video content inference and many other. We will implement a wide variety of deep learning use cases and also make extensive use of data related services comprising the Google Cloud Platform ecosystem such as Firebase, Storage APIs, Datalab and so forth. This will enable you to integrate Machine Learning and data processing features into your web and mobile applications.By the end of this book, you will know the main difficulties that you may encounter and get appropriate strategies to overcome these difficulties and build efficient systems.
Anubhav Singh, Sayak Paul
When used effectively, deep learning techniques can help you develop intelligent web apps. In this book, you'll cover the latest tools and technological practices that are being used to implement deep learning in web development using Python.Starting with the fundamentals of machine learning, you'll focus on DL and the basics of neural networks, including common variants such as convolutional neural networks (CNNs). You'll learn how to integrate them into websites with the frontends of different standard web tech stacks. The book then helps you gain practical experience of developing a deep learning-enabled web app using Python libraries such as Django and Flask by creating RESTful APIs for custom models. Later, you'll explore how to set up a cloud environment for deep learning-based web deployments on Google Cloud and Amazon Web Services (AWS). Next, you'll learn how to use Microsoft's intelligent Emotion API, which can detect a person's emotions through a picture of their face. You'll also get to grips with deploying real-world websites, in addition to learning how to secure websites using reCAPTCHA and Cloudflare. Finally, you'll use NLP to integrate a voice UX through Dialogflow on your web pages.By the end of this book, you'll have learned how to deploy intelligent web apps and websites with the help of effective tools and practices.
Rounak Banik
Recommendation systems are at the heart of almost every internet business today; from Facebook to Net?ix to Amazon. Providing good recommendations, whether it's friends, movies, or groceries, goes a long way in defining user experience and enticing your customers to use your platform.This book shows you how to do just that. You will learn about the different kinds of recommenders used in the industry and see how to build them from scratch using Python. No need to wade through tons of machine learning theory—you'll get started with building and learning about recommenders as quickly as possible..In this book, you will build an IMDB Top 250 clone, a content-based engine that works on movie metadata. You'll use collaborative filters to make use of customer behavior data, and a Hybrid Recommender that incorporates content based and collaborative filtering techniques With this book, all you need to get started with building recommendation systems is a familiarity with Python, and by the time you're fnished, you will have a great grasp of how recommenders work and be in a strong position to apply the techniques that you will learn to your own problem domains.
Micheal Lanham
With the increased presence of AI in the gaming industry, developers are challenged to create highly responsive and adaptive games by integrating artificial intelligence into their projects. This book is your guide to learning how various reinforcement learning techniques and algorithms play an important role in game development with Python.Starting with the basics, this book will help you build a strong foundation in reinforcement learning for game development. Each chapter will assist you in implementing different reinforcement learning techniques, such as Markov decision processes (MDPs), Q-learning, actor-critic methods, SARSA, and deterministic policy gradient algorithms, to build logical self-learning agents. Learning these techniques will enhance your game development skills and add a variety of features to improve your game agent’s productivity. As you advance, you’ll understand how deep reinforcement learning (DRL) techniques can be used to devise strategies to help agents learn from their actions and build engaging games.By the end of this book, you’ll be ready to apply reinforcement learning techniques to build a variety of projects and contribute to open source applications.
Harish Gulati
SAS is one of the leading enterprise tools in the world today when it comes to data management and analysis. It enables the fast and easy processing of data and helps you gain valuable business insights for effective decision-making. This book will serve as a comprehensive guide that will prepare you for the SAS certification exam.After a quick overview of the SAS architecture and components, the book will take you through the different approaches to importing and reading data from different sources using SAS. You will then cover SAS Base and 4GL, understanding data management and analysis, along with exploring SAS functions for data manipulation and transformation. Next, you'll discover SQL procedures and get up to speed on creating and validating queries. In the concluding chapters, you'll learn all about data visualization, right from creating bar charts and sample geographic maps through to assigning patterns and formats. In addition to this, the book will focus on macro programming and its advanced aspects.By the end of this book, you will be well versed in SAS programming and have the skills you need to easily handle and manage your data-related problems in SAS.
Hands-On Time Series Analysis with R. Perform time series analysis and forecasting using R
Rami Krispin
Time-series analysis is the art of extracting meaningful insights from, and revealing patterns in, time-series data using statistical and data visualization approaches. These insights and patterns can then be utilized to explore past events and forecast future values in the series.This book explores the basics of time-series analysis with R and lays the foundation you need to build forecasting models. You will learn how to preprocess raw time-series data and clean and manipulate data with packages such as stats, lubridate, xts, and zoo. You will analyze data using both descriptive statistics and rich data visualization tools in R including the TSstudio, plotly, and ggplot2 packages. The book then delves into traditional forecasting models such as time-series linear regression, exponential smoothing (Holt, Holt-Winter, and more) and Auto-Regressive Integrated Moving Average (ARIMA) models with the stats and forecast packages. You'll also work on advanced time-series regression models with machine learning algorithms such as random forest and Gradient Boosting Machine using the h2o package.By the end of this book, you will have developed the skills necessary for exploring your data, identifying patterns, and building a forecasting model using various traditional and machine learning methods.
Anish Chapagain
Web scraping is an essential technique used in many organizations to gather valuable data from web pages. This book will enable you to delve into web scraping techniques and methodologies.The book will introduce you to the fundamental concepts of web scraping techniques and how they can be applied to multiple sets of web pages. You'll use powerful libraries from the Python ecosystem such as Scrapy, lxml, pyquery, and bs4 to carry out web scraping operations. You will then get up to speed with simple to intermediate scraping operations such as identifying information from web pages and using patterns or attributes to retrieve information. This book adopts a practical approach to web scraping concepts and tools, guiding you through a series of use cases and showing you how to use the best tools and techniques to efficiently scrape web pages. You'll even cover the use of other popular web scraping tools, such as Selenium, Regex, and web-based APIs.By the end of this book, you will have learned how to efficiently scrape the web using different techniques with Python and other popular tools.
Nishant Shukla
Step-by-step recipes filled with practical code samples and engaging examples demonstrate Haskell in practice, and then the concepts behind the code.This book shows functional developers and analysts how to leverage their existing knowledge of Haskell specifically for high-quality data analysis. A good understanding of data sets and functional programming is assumed.
Rajesh Nadipalli
If you want to discover one of the latest tools designed to produce stunning Big Data insights, this book features everything you need to get to grips with your data. Whether you are a data architect, developer, or a business strategist, HDInsight adds value in everything from development, administration, and reporting.
Vikas (Vik) Kumar, Shameer Khader
In recent years, machine learning technologies and analytics have been widely utilized across the healthcare sector. Healthcare Analytics Made Simple bridges the gap between practising doctors and data scientists. It equips the data scientists’ work with healthcare data and allows them to gain better insight from this data in order to improve healthcare outcomes.This book is a complete overview of machine learning for healthcare analytics, briefly describing the current healthcare landscape, machine learning algorithms, and Python and SQL programming languages. The step-by-step instructions teach you how to obtain real healthcare data and perform descriptive, predictive, and prescriptive analytics using popular Python packages such as pandas and scikit-learn. The latest research results in disease detection and healthcare image analysis are reviewed.By the end of this book, you will understand how to use Python for healthcare data analysis, how to import, collect, clean, and refine data from electronic health record (EHR) surveys, and how to make predictive models with this data through real-world algorithms and code examples.
Bilal Shahid
If you are a web developer with a basic knowledge of HTML, CSS, and JavaScript and want to quickly get started with this web charting technology, this is the book for you. This book will also serve as an essential guide to those who have probably used a similar library and are now looking at migrating to Highcharts.
Hurtownie danych. Od przetwarzania analitycznego do raportowania
Adam Pelikant
Spec od hurtowni danych? Zawsze będzie pilnie potrzebny! Jak stworzyć strukturę hurtowni danych i dokonać ich integracji? Jak przeprowadzić analizę danych z wykorzystaniem rozszerzenia MDX SQL? Do czego potrzebne jest raportowanie? Idea hurtowni danych ściśle wiąże się z ich kolosalnymi ilościami, gromadzonymi podczas tysięcy różnych sytuacji — przy dowolnej transakcji, w urzędzie, na lotnisku, w internecie… Nawet nasze połączenia telefoniczne są przechowywane przez operatora. Te wszystkie dane trzeba gdzieś pomieścić, sensownie posegregować i zapewnić sobie możliwość sięgnięcia do wybranego ich zakresu bez długotrwałych poszukiwań. Taką możliwość dają właśnie hurtownie danych — przemyślane, bardzo pojemne bazy, oferujące zarówno integrację wprowadzanych danych, jak i znakomite mechanizmy ich przeszukiwania. Jeśli chcesz poszerzyć swoją wiedzę na temat tworzenia i przeglądania zawartości hurtowni danych, trafiłeś pod właściwy adres! Książka "Hurtownie danych. Od przetwarzania analitycznego do raportowania" zawiera materiał przeznaczony nie tylko dla studentów wydziałów informatycznych, ale także dla pasjonatów tej tematyki oraz specjalistów zainteresowanych poszerzeniem wiedzy. W możliwie najprostszy, praktyczny sposób opisano w niej składnię i postać zapytań analitycznych, strukturę hurtowni danych oraz kwestię ich integracji i wizualnego tworzenia elementów hurtowni. Znajdziesz tu także omówienie analizy danych z wykorzystaniem rozszerzenia MDX SQL oraz zastosowań raportowania. Zapoznanie się z tymi informacjami oraz prześledzenie zgromadzonych tu przykładów pozwoli Ci zrozumieć problemy powstające przy budowie hurtowni danych i wykorzystać tę wiedzę we własnych projektach. Zapytania analityczne Struktura hurtowni danych Integracja danych Wizualne tworzenie elementów hurtowni danych Analiza danych z wykorzystaniem rozszerzenia MDX SQL Raportowanie Od bazy do hurtowni danych… Skocz na głęboką wodę!
Hurtownie danych. Od przetwarzania analitycznego do raportowania. Wydanie II
Adam Pelikant
Idea hurtowni danych ściśle wiąże się z ich kolosalnymi ilościami, gromadzonymi podczas tysięcy różnych sytuacji - przy dowolnej transakcji, w urzędzie, na lotnisku, w internecie... Nawet nasze połączenia telefoniczne są przechowywane przez operatora. Te wszystkie dane trzeba gdzieś pomieścić, sensownie posegregować i zapewnić sobie możliwość sięgnięcia do wybranego ich zakresu bez długotrwałych poszukiwań. Taką możliwość dają właśnie hurtownie danych - przemyślane, bardzo pojemne bazy, oferujące zarówno integrację wprowadzanych danych, jak i znakomite mechanizmy ich przeszukiwania. Jeśli chcesz poszerzyć swoją wiedzę na temat tworzenia i przeglądania zawartości hurtowni danych, trafiłeś pod właściwy adres! Książka Hurtownie danych. Od przetwarzania analitycznego do raportowania zawiera materiał przeznaczony nie tylko dla studentów wydziałów informatycznych, ale także dla pasjonatów tej tematyki oraz specjalistów zainteresowanych poszerzeniem wiedzy. W możliwie najprostszy, praktyczny sposób opisano w niej składnię i postać zapytań analitycznych, strukturę hurtowni danych oraz kwestię ich integracji i wizualnego tworzenia elementów hurtowni. Znajdziesz tu także omówienie analizy danych z wykorzystaniem rozszerzenia MDX SQL oraz zastosowań raportowania. Zapoznanie się z tymi informacjami oraz prześledzenie zgromadzonych tu przykładów pozwoli Ci zrozumieć problemy powstające przy budowie hurtowni danych i wykorzystać tę wiedzę we własnych projektach. Zapytania analityczne Struktura hurtowni danych Integracja danych Wizualne tworzenie elementów hurtowni danych Analiza danych z wykorzystaniem rozszerzenia MDX SQL Raportowanie
Keith McCormick, Jesus Salcedo
IBM SPSS Modeler allows users to quickly and efficiently use predictive analytics and gain insights from your data. With almost 25 years of history, Modeler is the most established and comprehensive Data Mining workbench available. Since it is popular in corporate settings, widely available in university settings, and highly compatible with all the latest technologies, it is the perfect way to start your Data Science and Machine Learning journey. This book takes a detailed, step-by-step approach to introducing data mining using the de facto standard process, CRISP-DM, and Modeler’s easy to learn “visual programming” style. You will learn how to read data into Modeler, assess data quality, prepare your data for modeling, find interesting patterns and relationships within your data, and export your predictions. Using a single case study throughout, this intentionally short and focused book sticks to the essentials. The authors have drawn upon their decades of teaching thousands of new users, to choose those aspects of Modeler that you should learn first, so that you get off to a good start using proven best practices. This book provides an overview of various popular data modeling techniques and presents a detailed case study of how to use CHAID, a decision tree model. Assessing a model’s performance is as important as building it; this book will also show you how to do that. Finally, you will see how you can score new data and export your predictions. By the end of this book, you will have a firm understanding of the basics of data mining and how to effectively use Modeler to build predictive models.
Jagjeet Singh Makhija, Charles Odunukwe
The DP-600 exam tests your ability to design and implement analytics solutions using Microsoft Fabric, including planning data analytics environments, managing data integration and security, and optimizing performance. Written by two Microsoft specialists with over three decades of combined experience, this book will help you confidently prepare for the DP-600 exam by teaching you the skills that are essential for effectively implementing and designing analytics solutions.You’ll explore data analytics in Microsoft Fabric in detail and understand foundational topics such as data exploration, SQL querying, and data transformation, alongside advanced techniques such as semantic model optimization, performance tuning, and enterprise-scale model design. The book addresses strategic planning, data integration, security, scalability, and the complete project lifecycle, including version control, deployment, and continuous improvement. You’ll also get to grips with practical SQL integration with Microsoft Fabric components, with mock exams to help you reinforce what you’ve learned.By the end of this book, you’ll be able to plan, implement, and optimize analytics solutions using Microsoft Fabric, and you'll be well-equipped with the practical skills needed to tackle real-world data challenges and pass the DP-600 exam.
Andrew Bell, Francisco Arturo Viveros, Sander Rensen,...
Implementing Oracle API Platform Cloud Service moves from theory to practice using the newest Oracle API management platform. This critical new platform for Oracle developers allows you to interface the complex array of services your clients expect in the modern world.First, you'll learn about Oracle’s new platform and get an overview of it, then you'll see a use case showing the functionality and use of this new platform for Oracle customers. Next, you’ll see the power of Apiary and begin designing your own APIs. From there, you’ll build and run microservices and set up the Oracle API gateways. Moving on, you’ll discover how to customize the developer portal and publish your own APIs. You’ll spend time looking at configuration management on the new platform, and implementing the Oauth 2.0 policy, as well as custom policies. The latest finance modules from Oracle will be examined, with some of the third party alternatives in sight as well.This broad-scoped book completes your journey with a clear examination of how to transition APIs from Oracle API Management 12c to the new Oracle API Platform, so that you can step into the future confidently.
Implementing Qlik Sense. Design, Develop, and Validate BI solutions for consultants
Ganapati Hegde, Kaushik Solanki
Qlik Sense is a leading platform for business intelligence (BI) solutions. Qlik Sense helps organizations in making informed decisions based on the data they have.This book will teach you how to effectively use Qlik for optimum customer satisfaction. You will undergo a metamorphosis from a developer to a consultant who is capable of building the most suitable BI solutions for your clients. The book will take you through several business cases – this will give you enough insight to understand the needs of the client clearly and build a BI solution that meets or exceeds their expectations. Starting from the pre-project activities, you will go to the actual execution of the project, the implementation, and even maintenance. This book will give you all the information you need - from the strategy to requirement gathering to implementing BI solutions using Qlik Sense. The book will empower you to take the right decisions in tricky and diffi cult situations while developing analytics and dashboards.
James D. Miller
Splunk is the leading platform that fosters an efficient methodology and delivers ways to search, monitor, and analyze growing amounts of big data. This book will allow you to implement new services and utilize them to quickly and efficiently process machine-generated big data. We introduce you to all the new features, improvements, and offerings of Splunk 7. We cover the new modules of Splunk: Splunk Cloud and the Machine Learning Toolkit to ease data usage. Furthermore, you will learn to use search terms effectively with Boolean and grouping operators. You will learn not only how to modify your search to make your searches fast but also how to use wildcards efficiently. Later you will learn how to use stats to aggregate values, a chart to turn data, and a time chart to show values over time; you'll also work with fields and chart enhancements and learn how to create a data model with faster data model acceleration. Once this is done, you will learn about XML Dashboards, working with apps, building advanced dashboards, configuring and extending Splunk, advanced deployments, and more. Finally, we teach you how to use the Machine Learning Toolkit and best practices and tips to help you implement Splunk services effectively and efficiently. By the end of this book, you will have learned about the Splunk software as a whole and implemented Splunk services in your tasks at projects
Liyanapathirannahelage H Perera
MapReduce is a technology that enables users to process large datasets and Hadoop is an implementation of MapReduce. We are beginning to see more and more data becoming available, and this hides many insights that might hold key to success or failure. However, MapReduce has the ability to analyze this data and write code to process it.Instant MapReduce Patterns – Hadoop Essentials How-to is a concise introduction to Hadoop and programming with MapReduce. It is aimed to get you started and give you an overall feel for programming with Hadoop so that you will have a well-grounded foundation to understand and solve all of your MapReduce problems as needed.Instant MapReduce Patterns – Hadoop Essentials How-to will start with the configuration of Hadoop before moving on to writing simple examples and discussing MapReduce programming patterns.We will start simply by installing Hadoop and writing a word count program. After which, we will deal with the seven styles of MapReduce programs: analytics, set operations, cross correlation, search, graph, Joins, and clustering. For each case, you will learn the pattern and create a representative example program. The book also provides you with additional pointers to further enhance your Hadoop skills.
Interactive Applications using Matplotlib
This book is intended for Python programmers who want to do more than just see their data. Experience with GUI toolkits is not required, so this book can be an excellent complement to other GUI programming resources.
Elias Dabbas
Plotly's Dash framework is a life-saver for Python developers who want to develop complete data apps and interactive dashboards without JavaScript, but you'll need to have the right guide to make sure you’re getting the most of it. With the help of this book, you'll be able to explore the functionalities of Dash for visualizing data in different ways.Interactive Dashboards and Data Apps with Plotly and Dash will first give you an overview of the Dash ecosystem, its main packages, and the third-party packages crucial for structuring and building different parts of your apps. You'll learn how to create a basic Dash app and add different features to it.Next, you’ll integrate controls such as dropdowns, checkboxes, sliders, date pickers, and more in the app and then link them to charts and other outputs. Depending on the data you are visualizing, you'll also add several types of charts, including scatter plots, line plots, bar charts, histograms, and maps, as well as explore the options available for customizing them.By the end of this book, you'll have developed the skills you need to create and deploy an interactive dashboard, handle complexities and code refactoring, and understand the process of improving your application.
MrExcel's Holy Macro! Books, Liam Bastick
This book serves as a comprehensive guide to financial modeling, equipping readers with the skills and knowledge to create accurate, reliable models for analysis and decision-making. Designed for professionals, students, and finance enthusiasts, it bridges theoretical principles with practical Excel-based techniques, ensuring a balanced and thorough understanding of the subject.Key Excel functions such as SUMPRODUCT, INDEX and MATCH, and LOOKUP are covered in depth, alongside essential tools like conditional formatting, data validation, and solver. The book emphasizes best practices in layout design, error checking, and model transparency, helping users build robust and easy-to-follow financial models. Practical methodologies for time-series analysis, control accounts, and financial statement theory are explored, making it a versatile resource.The step-by-step model-building example guides readers through structuring, linking, and finalizing financial statements, including revenue, expenditure, taxation, and cash flow. Ratio analysis and self-review techniques are also discussed to ensure model accuracy and integrity. This detailed yet accessible guide empowers readers to create professional financial models with confidence and clarity.