Biznes IT
R Deep Learning Projects. Master the techniques to design and develop neural network models in R
Yuxi (Hayden) Liu, Pablo Maldonado
R is a popular programming language used by statisticians and mathematicians for statistical analysis, and is popularly used for deep learning. Deep Learning, as we all know, is one of the trending topics today, and is finding practical applications in a lot of domains.This book demonstrates end-to-end implementations of five real-world projects on popular topics in deep learning such as handwritten digit recognition, traffic light detection, fraud detection, text generation, and sentiment analysis. You'll learn how to train effective neural networks in R—including convolutional neural networks, recurrent neural networks, and LSTMs—and apply them in practical scenarios. The book also highlights how neural networks can be trained using GPU capabilities. You will use popular R libraries and packages—such as MXNetR, H2O, deepnet, and more—to implement the projects. By the end of this book, you will have a better understanding of deep learning concepts and techniques and how to use them in a practical setting.
Dr. Sunil Kumar Chinnamgari
R is one of the most popular languages when it comes to performing computational statistics (statistical computing) easily and exploring the mathematical side of machine learning. With this book, you will leverage the R ecosystem to build efficient machine learning applications that carry out intelligent tasks within your organization.This book will help you test your knowledge and skills, guiding you on how to build easily through to complex machine learning projects. You will first learn how to build powerful machine learning models with ensembles to predict employee attrition. Next, you’ll implement a joke recommendation engine and learn how to perform sentiment analysis on Amazon reviews. You’ll also explore different clustering techniques to segment customers using wholesale data. In addition to this, the book will get you acquainted with credit card fraud detection using autoencoders, and reinforcement learning to make predictions and win on a casino slot machine.By the end of the book, you will be equipped to confidently perform complex tasks to build research and commercial projects for automated operations.
R Programming By Example. Practical, hands-on projects to help you get started with R
Omar Trejo Navarro
R is a high-level statistical language and is widely used among statisticians and data miners to develop analytical applications. Often, data analysis people with great analytical skills lack solid programming knowledge and are unfamiliar with the correct ways to use R. Based on the version 3.4, this book will help you develop strong fundamentals when working with R by taking you through a series of full representative examples, giving you a holistic view of R.We begin with the basic installation and configuration of the R environment. As you progress through the exercises, you'll become thoroughly acquainted with R's features and its packages. With this book, you will learn about the basic concepts of R programming, work efficiently with graphs, create publication-ready and interactive 3D graphs, and gain a better understanding of the data at hand. The detailed step-by-step instructions will enable you to get a clean set of data, produce good visualizations, and create reports for the results. It also teaches you various methods to perform code profiling and performance enhancement with good programming practices, delegation, and parallelization.By the end of this book, you will know how to efficiently work with data, create quality visualizations and reports, and develop code that is modular, expressive, and maintainable.
R Programming Fundamentals. Deal with data using various modeling techniques
Kaelen Medeiros
R Programming Fundamentals, focused on R and the R ecosystem, introduces you to the tools for working with data. You’ll start by understanding how to set up R and RStudio, followed by exploring R packages, functions, data structures, control flow, and loops.Once you have grasped the basics, you’ll move on to studying data visualization and graphics. You’ll learn how to build statistical and advanced plots using the powerful ggplot2 library. In addition to this, you’ll discover data management concepts such as factoring, pivoting, aggregating, merging, and dealing with missing values.By the end of this book, you’ll have completed an entire data science project of your own for your portfolio or blog.
R Web Scraping Quick Start Guide. Techniques and tools to crawl and scrape data from websites
Olgun Aydin
Web scraping is a technique to extract data from websites. It simulates the behavior of a website user to turn the website itself into a web service to retrieve or introduce new data. This book gives you all you need to get started with scraping web pages using R programming.You will learn about the rules of RegEx and Xpath, key components for scraping website data. We will show you web scraping techniques, methodologies, and frameworks. With this book's guidance, you will become comfortable with the tools to write and test RegEx and XPath rules. We will focus on examples of dynamic websites for scraping data and how to implement the techniques learned. You will learn how to collect URLs and then create XPath rules for your first web scraping script using rvest library. From the data you collect, you will be able to calculate the statistics and create R plots to visualize them. Finally, you will discover how to use Selenium drivers with R for more sophisticated scraping. You will create AWS instances and use R to connect a PostgreSQL database hosted on AWS. By the end of the book, you will be sufficiently confident to create end-to-end web scraping systems using R.
Simeon Kostadinov
Developers struggle to find an easy-to-follow learning resource for implementing Recurrent Neural Network (RNN) models. RNNs are the state-of-the-art model in deep learning for dealing with sequential data. From language translation to generating captions for an image, RNNs are used to continuously improve results. This book will teach you the fundamentals of RNNs, with example applications in Python and the TensorFlow library. The examples are accompanied by the right combination of theoretical knowledge and real-world implementations of concepts to build a solid foundation of neural network modeling.Your journey starts with the simplest RNN model, where you can grasp the fundamentals. The book then builds on this by proposing more advanced and complex algorithms. We use them to explain how a typical state-of-the-art RNN model works. From generating text to building a language translator, we show how some of today's most powerful AI applications work under the hood.After reading the book, you will be confident with the fundamentals of RNNs, and be ready to pursue further study, along with developing skills in this exciting field.
Eric McLeroy, Peter Sprygada
If you’re ready to take the next step in your system engineering career with the EX358, then this book is for you. Packed with all the knowledge and skills that you need to configure and maintain services and applications on the Red Hat Linux 8 (RHEL OS 8) platform, this book will help you ace the exam and thrive at work.Red Hat Certified Specialist in Service Management and Automation will help you build a solid foundation of the most recent and up-to-date exam requirements and practice questions.Throughout the course of the book, you’ll get hands-on experience with different technical processes needed to fully administer a Red Hat Enterprise Linux 8 system. This will include file storage, database management, direct configuration of applications, such as SMB shares, networking. You’ll be well equipped with the configuration of essential components like firewall, SELinux, and iSCSI while learning how to automate these tasks using Ansible Automation 2.9 in order to alleviate the burden of completing them by hand.By the end of this book, you'll have covered all essential topics to ace the Red Hat EX358 certification exam and add another feather to your career as a Red Hat Certified Specialist.
Redash v5 Quick Start Guide. Create and share interactive dashboards using Redash
Alexander Leibzon, Yael Leibzon
Data exploration and visualization is vital to Business Intelligence, the backbone of almost every enterprise or organization. Redash is a querying and visualization tool developed to simplify how marketing and business development departments are exposed to data. If you want to learn to create interactive dashboards with Redash, explore different visualizations, and share the insights with your peers, then this is the ideal book for you.The book starts with essential Business Intelligence concepts that are at the heart of data visualizations. You will learn how to find your way round Redash and its rich array of data visualization options for building interactive dashboards. You will learn how to create data storytelling and share these with peers. You will see how to connect to different data sources to process complex data, and then visualize this data to reveal valuable insights. By the end of this book, you will be confident with the Redash dashboarding tool to provide insight and communicate data storytelling.
Redis Essentials. Harness the power of Redis to integrate and manage your projects efficiently
Fredrik Sandell, Alexander Myltsev, Javier de la...
Redis is the most popular in-memory key-value data store. It's very lightweight and its data types give it an edge over the other competitors. If you need an in-memory database or a high-performance cache system that is simple to use and highly scalable, Redis is what you need.Redis Essentials is a fast-paced guide that teaches the fundamentals on data types, explains how to manage data through commands, and shares experiences from big players in the industry.We start off by explaining the basics of Redis followed by the various data types such as Strings, hashes, lists, and more. Next, Common pitfalls for various scenarios are described, followed by solutions to ensure you do not fall into common traps.After this, major differences between client implementations in PHP, Python, and Ruby are presented. Next, you will learn how to extend Redis with Lua, get to know security techniques such as basic authorization, firewall rules, and SSL encryption, and discover how to use Twemproxy, Redis Sentinel, and Redis Cluster to scale infrastructures horizontally. At the end of this book, you will be able to utilize all the essential features of Redis to optimize your project's performance.
Giuseppe Ciaburro
Regression analysis is a statistical process which enables prediction of relationships between variables. The predictions are based on the casual effect of one variable upon another. Regression techniques for modeling and analyzing are employed on large set of data in order to reveal hidden relationship among the variables.This book will give you a rundown explaining what regression analysis is, explaining you the process from scratch. The first few chapters give an understanding of what the different types of learning are – supervised and unsupervised, how these learnings differ from each other. We then move to covering the supervised learning in details covering the various aspects of regression analysis. The outline of chapters are arranged in a way that gives a feel of all the steps covered in a data science process – loading the training dataset, handling missing values, EDA on the dataset, transformations and feature engineering, model building, assessing the model fitting and performance, and finally making predictions on unseen datasets. Each chapter starts with explaining the theoretical concepts and once the reader gets comfortable with the theory, we move to the practical examples to support the understanding. The practical examples are illustrated using R code including the different packages in R such as R Stats, Caret and so on. Each chapter is a mix of theory and practical examples.By the end of this book you will know all the concepts and pain-points related to regression analysis, and you will be able to implement your learning in your projects.
Sayon Dutta
Reinforcement learning (RL) allows you to develop smart, quick and self-learning systems in your business surroundings. It's an effective method for training learning agents and solving a variety of problems in Artificial Intelligence - from games, self-driving cars and robots, to enterprise applications such as data center energy saving (cooling data centers) and smart warehousing solutions.The book covers major advancements and successes achieved in deep reinforcement learning by synergizing deep neural network architectures with reinforcement learning. You'll also be introduced to the concept of reinforcement learning, its advantages and the reasons why it's gaining so much popularity. You'll explore MDPs, Monte Carlo tree searches, dynamic programming such as policy and value iteration, and temporal difference learning such as Q-learning and SARSA. You will use TensorFlow and OpenAI Gym to build simple neural network models that learn from their own actions. You will also see how reinforcement learning algorithms play a role in games, image processing and NLP.By the end of this book, you will have gained a firm understanding of what reinforcement learning is and understand how to put your knowledge to practical use by leveraging the power of TensorFlow and OpenAI Gym.
Reklamuj się z Google. Skuteczne rozwiązania i przykłady
Kristina Cutura
Skuteczne kampanie na platformie Google Adwords! Google Adwords to skuteczne i niezwykle elastyczne narzędzie, dzięki któremu każdy może zareklamować się w sieci. Pozwala na dotarcie do pożądanej grupy docelowej, odgórne ustalenie ponoszonych kosztów oraz czasowe zaplanowanie emisji reklam. Ale to nie wszystko! Google Adwords to dziesiątki opcji, które mają znaczący wpływ na skuteczność Twojej reklamy. Dowiedz się, jak optymalnie wykorzystać Twoje środki na reklamę. W tej książce znajdziesz ponad sto najlepszych porad, które pozwolą Ci zoptymalizować Twoje działania reklamowe. W trakcie lektury nauczysz się badać rynek i konkurencję oraz ustalać cele. Dowiesz się, jak założyć konto w Google Adwords oraz przygotować pierwszą kampanię reklamową. Istotne jest, żebyś wiedział, jak wielu użytkowników klika Twoje reklamy oraz jak duży zysk to przynosi. Analizy współczynników konwersji pomogą Ci odpowiedzieć na to i wiele innych pytań. W kolejnych rozdziałach zobaczysz, w jaki sposób wybierać słowa kluczowe, określać budżety i stawki oraz korzystać z remarketingu. Książka ta jest bogatym źródłem informacji dla wszystkich Czytelników mających ambicję poprowadzić własną, skuteczną kampanię reklamową w Google Adwords. Dzięki tej książce: założysz konto w Google Adwords przygotujesz pierwszą kampanię reklamową zmierzysz skuteczność reklamy wykorzystasz możliwości remarketingu poznasz tajniki Google Adwords Wykorzystaj potencjał reklam Google Adwords!
Michał Kosiorek
Najlepsza praca świata? Oczywiście rekruter w IT! Branża IT jest dość nietypowa. Poza nielicznymi wyjątkami ― jak specjaliści od sprzętu ― większość osób realizujących projekty informatyczne, tworzących oprogramowania i podtrzymujących działanie systemów może pracować zdalnie. Co więcej, zdalnie oznacza czasem operowanie z drugiego końca świata, w ramach międzynarodowych zespołów, których członkowie spotykają się via komunikatory i na zebraniach online. I wszystko to potrafi zadziwiająco sprawnie funkcjonować! Skoro firmy z branży informatycznej są tak bardzo "zdalne", może także pracownicy HR, może również rekruterzy byliby w stanie funkcjonować bez codziennego pojawiania się w biurze? Czytać maile na plaży na Bali, Zanzibarze czy choćby we Włoszech . Realizować powierzone sobie zadania w sposób uporządkowany i systematyczny o godzinie, która najbardziej im odpowiada. I zarabiać przy tym kwoty rzędu kilkudziesięciu tysięcy na miesiąc. Jeśli taka wizja pracy w roli rekrutera w IT do Ciebie przemawia i zastanawiasz się, jak zmienić tę wizję w rzeczywistość, to przestań marzyć, a zacznij czytać tę książkę. Jej autor konkretnie, krok po kroku pokaże Ci, co musisz zrobić, by dołączyć do światowej armii digital recruiter nomads i pracować, skąd chcesz, jak chcesz i w godzinach, które Ci odpowiadają. Zobacz zapis z webinaru prowadzonego przez Michała Kosiorka oraz Krzysztofa Kempińskiego na temat: „Marka osobista na rynku pracy w IT” ⤵️