“Bili?im Teknolojileri” konusunda yazd???m ü? kitaptan sonra as?l uzmanl?k alan?m olan veritabanlar? konusunda uzun y?llar ?nce yazmaya ba?lay?p bitiremedi?im daha do?rusu bas?lmayan bu kitab? güncelleyerek yeniden yazmaya karar vermek benim a??mdan yeni bir heyecan oldu. 1980’lerde COBOL ile ba?layan ve 1990’da dBase ve Informix’le devam eden veritaban? tecrübelerim, 1995 sonras? MS-Access ve SQL Server yard?m?yla geli?tirdi?im 100’e yak?n veritaban? uygulama programlar?yla devam etti. 1996’da Dallas’ta MCI Systemhouse’da FrontPage ve Access 95’le veritaban?na dayal? Intranet web siteleri geli?tiren ilk ki?ilerden birisi ben oldum. 1999’da Movo Mediya’da ilk ??p?atan web sitesi www.dating.com'un?arkas?ndaki SQL Server veritabanlar?n? tasarlayan ve y?neten ki?i de bendim. 2000 y?l?nda Aris Genesis Intermedia Inc’de web tabanl? muhasebe program?n?n arkas?ndaki SQL Server veritaban? tasar?mc?lar?ndan biriside bendim. Büyük al??veri? merkezlerinde g?rülen Kiosk’lar?n SQL Server tabanl? ilk uygulamas?n? Los Angeles’de kuran Genesis Intermedia Inc’deki tasar?mlar? yapan ki?ilerden birisi de bendim. 2001’de Los Angeles’de SQL Server ve ASP 3.0’la Citibank’ta kredi kartlar?yla ilgili projenin mimarlar?ndan biriside bendim. K?sacas? Veritabanlar?n?n Web’de kullan?lmas?nda ilk ?al??an ve tasarlayanlardan birisi oldu?umu s?ylemeliyim. 1995-2000 y?llar? aras?nda ya?anan ve dot com bom olarak bilinen metaforun i?inde bir fiil ?al??an ve yarat?c?lar?ndan birisiydim. Veritabanlar?n?n Internet’e ba?lanmas? i?in geli?tirilen ilk projelerinde uzun y?llar Kalifornya, New York ve Colorado firmalar?nda ?al??t?m ve dan??manl?k yapt?m. Bu tecrübelerim s?ras?nda ??rendi?im en ?nemli ?ey; tek bir konuda uzman olmak gerekti?idir. Ben Ms-Access ve SQL Server veritabanlar? tasar?m?nda uzmanla?t?m. Bir?ok teklif olmas?na ra?men Oracle, DB2, Aproach, File Maker gibi veritabanlar? tasar?mlar?yla ilgilenmedim ?ünkü her biri ayr? bir uzmanl?k isteyen veritaban? yaz?l?mlar?d?r. Bu a??dan ?zellikle Bili?im sekt?ründe ?al??anlara verebilece?im en ?nemli tavsiye tek bir konuda hatta tek bir programda uzmanla?malar?d?r. Kitapta Veritabanlar? tasar?m?n? Access ve SQL Server projeleri üzerinden anlatmaya ?al??t?m. University of Phoenix’de verdi?im Veritabanlar? ve Veri Ambarlar? ders notlar?m bu kitab?n omurgas?n? olu?turmaktad?r. Veritabanlar?yla ilgili kavramlar?, felsefesini, tasar?m?n? ve birazda y?netimini detaylar?yla anlatmaya ?al??t?m. Umut ediyorum ki yeni Veritaban? tasar?mc?lar? ve y?neticilerine burada payla?t???m enformasyon faydal? olur. 30 y?ll?k Bili?im Teknolojileri ve ?zellikle veritaban? alan?ndaki tecrübelerimin bir?o?unu bu kitapta okuyucularla payla?maya ?al??t?m. Daha ?nceki kitaplar?mda da vurgulad???m gibi bu kitapta da ilkokul ??retmenim Say?n ?erare ?zya?c? han?mdan, en son Doktora tez dan??man?m Say?n Prof. Dr. Len Rogers’a kadar yüzlerce ki?inin eme?inin oldu?u unutulmamal?d?r. 1984’ten beri Türkiye, ABD, Kanada ve ?ngiltere de ?al??t???m veya dan??manl???n? yapt???m onlarca firma ve mü?terilerimin katk?lar?n? unutabilir miyim? Di?er kitaplarda oldu?u gibi bu kitab?n yaz?lmas?nda bana katlanan e?im Meliha ?oruh’a ve o?lum Bu?ra’ya da en ba?tan te?ekkür etmeliyim. Burada isim isim te?ekkür edemedi?im ancak bu kitab?n yaz?lmas?nda katk?lar? olan daha yüzlerce ki?i var, hepsine en i?ten dileklerimle te?ekkür ediyorum. Elinizde tuttu?unuz bu kitap 30 y?ld?r Bili?im Teknolojileri alan?nda yapt???m ??retim, ?al??ma ve tecrübelerin veritabanlar? alan?nda kay?t alt?na al?nm?? bir ?zetidir. Tabii ki kitab?n hatalar? ve eksikleri vard?r ve bunlar tamamen bana aittir. Kitapta Veritabanlar? denince akla gelebilecek bir?ok konuya de?inmeye ?al??t?m. Kitapta teori ile uygulamay? birlikte harmanlamaya ?al??t?m. Bu yüzden bu kitab?n bir elkitab? veya kaynak kitap olarak dü?ünülmesinde fayda vard?r. ? Mustafa ?oruh Kdz. Ere?li, Mart 2017

☆★☆ Javascript: Javascript Programming For Absolute Beginners☆★☆ The best starter guide for javascript!The fundamentals of javascript are often missed, however, this book's primary focus and emphasis is learning the essentials and to build from the ground up.? What You'lll Learn The history of JavaScript and its uses Setting Up Your Environment The Vital Basics of HTML and CSS Statements, Comments & Variables How to properly use jQuery String Operators JavaScript Array Methods Loops and Iteration How To Use Functions And much, much more! ? Within this book you will learn various mechanisms of javascript programming: variables, conditional statements, and why learning these core principles lead to success.Once you gain knowledge of the fundamental building blocks of javascript you will gain confidence to tackle more complex topics down the road.Programming books can easily retail for 100s of dollars, why not start with an expert you can trust and for an affordable price?The immense value of this book cannot be understated, and this is a once in a life time opportunity for you to take advantage of and invest in yourself by empowering yourself with the right tools and knowledge for success.What are you waiting for?Includes: 21 practice questions! Note* For best visual experience of diagrams it is highly recommend you purchases the paperback version for best image quality.☆★☆ Grab your copy now!☆★☆

Everything you need to start working with React 16 and assess React FiberAbout This Book·Hands-on examples and tutorials for the latest React 16 release·Assess the impact of React Fiber for your future web development·Build maintainable and high performance React 16 web applicationsWho This Book Is ForIf you're a frontend developer with some knowledge of native JavaScript development and frontend frameworks, wishing to learn the fastest web user interface library there is, then this book is ideal for you.What You Will Learn·Learn to code React 16 with hands-on examples and clear tutorials·Install powerful React 16 tools to make development much more efficient·Understand the impact of React Fiber today and the future of your web development·Utilize the Redux application architecture with your React components·Create React 16 elements with properties and children·Get started with stateless and stateful React components·Use JSX to speed up your React 16 development process·Add reactivity to your React 16 components with lifecycle methods·Test your React 16 components with the Jest test frameworkIn DetailReact 16 Essentials, Second Edition, fully updated for React 16, takes you on a fast-paced journey through building your own maintainable React 16 applications. React experts Artemij Fedosejev and Adam Boduch give you all the essentials you need to know and start working with React 16, in this new edition of the best-selling React.js Essentials title. You'll find the latest React 16 code updates, assessment of React Fiber, new coverage of Redux, and how to work as a modern React developer.The authors offer you their current assessment of React Fiber, and you'll soon be exploring React 16 hands on, creating your own single and multiple user interface elements with React 16. You'll then see how to create stateless and stateful components and make them reactive. You'll also learn to interact between your components and lifecycle methods, and gauge how to effectively integrate your user interface components with other JavaScript libraries. Delve deep into the core elements of the Redux architecture and learn how to manage your application and data persistence. Then go the extra mile with the Jest test framework, and run multiple tests on your applications and find solutions to scale without complexity.Today React is used by Facebook, Instagram, Khan Academy, and Imperial College London, to name a few. Many new users recognize the benefits of React and adopt it in their own projects, forming a fast-growing community. The speed at which React has evolved promises a bright future for anyone who invests in learning it today. Let Artemij and Adam bring you a brand new look at React 16 and React Fiber, and move your web development into the future.Style and approachReact 16 Essentials, Second Edition, will take you on a fast-paced, hands-on journey through building your own maintainable React 16 applications.

Frustrated with the plethora of conflicting information on how to self-publish? Wouldn’t it be wonderful to sit down with someone who has already made the mistakes, done the analysis, and will provide you the short cuts—the secrets about the things that work? Now you have that chance with the Career Author Secrets series.Indie Publishing (Self Publishing) has changed dramatically in the past five years. There are now new, easier tools to use for every part of the process—editing, formatting, distribution, sales, and analysis. This first book in the Career Author Secrets series provides a foundation for navigating the indie publishing process and staying away from the scammers. It breaks down the requirements for self-publishing successfully, protecting your rights for the future, and YES I do share all the secrets I’ve learned. It contains everything a DIY author needs to get her book from manuscript to professional publication in both ebook and print, including: Why books don’t sell Options for DIY or contracting professionals The truth about ISBNs & Copyright Registration Secrets for formatting your book the easy way Creating book covers that sell Making decisions about distribution This book is especially valuable for those with limited technical skills who want to produce a quality professional book for the least amount of cost. Learn the secrets to easier implementation and how to make good decisions on what is worth your time and money.

An ebook is just a website in a boxBut what’s inside the box?In this clear, concise guide, ebook designer and indie author David Kudler folds back the lid of ePub, the universal ebook format. He introduces you to the nuts and bolts that make an ebook work. Includes overviews of the ePub format and internal structure as well as basic guides to the HTML and CSS (Cascading Style Sheets) that you need to know to make your ebooks look professional.(Self-Publishing & Ebook Creation)David Kudler is an independent publisher and author. He has been designing ebooks since 2010. He blogs about ebook creation, publishing, and marketing on Huffington Post, Stillpoint Digital Press, and The Book Designer.

Turn your noisy data into relevant, insight-ready information by leveraging the data wrangling techniques in Python and RAbout This Book·This easy-to-follow guide takes you through every step of the data wrangling process in the best possible way·Work with different types of datasets, and reshape the layout of your data to make it easier for analysis·Get simple examples and real-life data wrangling solutions for data pre-processingWho This Book Is ForIf you are a data scientist, data analyst, or a statistician who wants to learn how to wrangle your data for analysis in the best possible manner, this book is for you. As this book covers both R and Python, some understanding of them will be beneficial.What You Will Learn·Read a csv file into python and R, and print out some statistics on the data·Gain knowledge of the data formats and programming structures involved in retrieving API data·Make effective use of regular expressions in the data wrangling process·Explore the tools and packages available to prepare numerical data for analysis·Find out how to have better control over manipulating the structure of the data·Create a dexterity to programmatically read, audit, correct, and shape data·Write and complete programs to take in, format, and output data setsIn DetailAround 80% of time in data analysis is spent on cleaning and preparing data for analysis. This is, however, an important task, and is a prerequisite to the rest of the data analysis workflow, including visualization, analysis and reporting. Python and R are considered a popular choice of tool for data analysis, and have packages that can be best used to manipulate different kinds of data, as per your requirements. This book will show you the different data wrangling techniques, and how you can leverage the power of Python and R packages to implement them.You'll start by understanding the data wrangling process and get a solid foundation to work with different types of data. You'll work with different data structures and acquire and parse data from various locations. You'll also see how to reshape the layout of data and manipulate, summarize, and join data sets. Finally, we conclude with a quick primer on accessing and processing data from databases, conducting data exploration, and storing and retrieving data quickly using databases.The book includes practical examples on each of these points using simple and real-world data sets to give you an easier understanding. By the end of the book, you'll have a thorough understanding of all the data wrangling concepts and how to implement them in the best possible way.Style and approachThis is a practical book on data wrangling designed to give you an insight into the practical application of data wrangling. It takes you through complex concepts and tasks in an accessible way, featuring information on a wide range of data wrangling techniques with Python and R

Bu kitap “Bili?im Teknolojileri (BT) Ekonomisi ve Toplumu” adl? ilk kitab?mda BT’lerin hayat?m?z? de?i?tirdi?i d?rt yerdeki (Evde, okulda, kentlerde ve i?yerlerinde) incelememin ü?üncüsü olan i?yerlerindeki etkileri üzerinedir. Daha ?nce “Bili?im Teknolojileri Destekli ??renim” ve “Bili?im Kentleri ?a??” adl? kitaplar?mda BT’lerin okul ve kent ya?am?ndaki etkilerini detaylar?yla inceledim. 30 y?l? a?an i? hayat?mda BT’lerin i? dünyas?n? ve y?netimini kurulan Bili?im Sistemleri (BS) vas?tas?yla nas?l de?i?tirdi?ini ya?ayarak bildi?imden bu konu i?in uzun bir ara?t?rma yapmak zorunda oldu?umu biliyordum. Di?er yandan 592 sayfay? bulan bu ara?t?rmada sayfa s?n?rlamas? amac?yla BS’lerle ilgili baz? konular? (?rne?in Toplam Kalite Y?netimi, 6 Sigma, Simülasyon, Gereksinim Y?netimi, Programlama vs.) kitap haricinde b?rakmak zorunda kald???m? da belirtmeliyim. Bu kitapta a??rl?kl? olarak BT’lerin i?letmelerdeki uygulamas? olan Bili?im Sistemlerinden bahsettim ?ünkü BT’ler BS’ler vas?tas?yla i?letmeleri ve y?netimlerini etkilemektedirler. Dünyan?n en h?zl? bilgisayar?n? veya en yeni ak?ll? telefonunu sat?n alman?z veya en h?zl? internet eri?imine sahip olman?z i?letmeye ekstra bir katk? sa?lamamaktad?r. Ne zaman ki bu ara?lar i?letme süre?lerinin otomasyonunu sa?layan BS’ler i?inde kullan?lmaya ba?lan?nca i?letme rekabet?ili?ine, kar?na veya maliyetlerinin kontrolüne bir faydas? olabilmektedir. Bu yüzden i?letme y?neticilerinin bilmesi gereken en ?nemli konu BT ara?lar?n? ve di?er yeni teknolojik ara?lar? i?letme i? süre?lerinde nas?l verimli ve etkin bir ?ekilde kullanabileceklerini bilmeleridir. Bilmiyorlarsa da bilenleri i?e almalar?d?r. En son yenilikleri kullanmak belki de firmaya zarar vermekte veya rekabet dezavantaj? olu?turmaktad?r. Bu a??dan ?ncelikle bugün BS’lerin hangi i?letme fonksiyonlar?n? nas?l etkiledi?ini ve gelecekte nas?l etkileyebilece?ini anlatmaya ?al??t?m. ?rne?in, Yapay Zek? (YZ) ve onun en ?nemli uygulamalar?ndan birisi olan Robotiklerin i? süre?leri ve i?letme y?netimlerini yak?n bir zamanda nas?l etkileyebilece?inden bahsettim. Endüstri 4.0 teknolojileriyle insan ve makinelerin birlikte nas?l verimli ve etkin bir ?ekilde ?al??malar? gerekti?i insanl???n ve i?letmelerin ?nünde duran en ?nemli konulardan birisi oldu?unu s?ylemek fazla fütüristik bir kehanet de?il. Kitapta ??letmelerde kullan?lan Bili?im Sistemleriyle ilgili temel konulara bir bütünlük i?inde bakarken kitab?n arka kapa??ndaki sorular? cevaplamaya ?al??t?m. Bili?im Sistemleri aras?ndaki ili?kileri, farkl?l?klar?n? ve birbirlerini nas?l tamamlad?klar?n? sat?r aralar?nda vermeye ?al??t?m. BS’lerle i?letme süre?lerinin nas?l bütünle?tirilece?i i?letmelerdeki en yeni y?netim sorunlar? oldu?u unutulmamal?d?r. ??letme y?neticilerinin hat?rlamas? gereken bir ?nemli konuda BS’lerin bir yaz?l?m ve de?i?im projesi olmas?d?r. Bili?im Teknolojileri ve Sistemleri okuryazarl??? i?in bilinmesi gereken baz? teknik, bilimsel ve teknolojik terimlerin k?saltmalar?n? kitapta ilk kullan?ld???nda uzun ve k?salt?lm?? yaz?l?mlar?yla birlikte kulland?m. ?rne?in Veritabanlar? (VT), Veri ??leme Sistemi (V?S), Kurumsal ?? Zek?s? (K?Z), Y?netim Bili?im Sistemi (YBS), Karar Destek Sistemi (KDS), Veri Ambar? (VA), Veri Madencili?i (VM), Kurumsal Kaynak Planlama (KKP), Mü?teri ?li?kileri Y?netimi (M?Y), Tedarik Zinciri Y?netimi (TZY), Ofis Otomasyon Sistemi (OOS) ve Bilgi Y?netimi (BY) en fazla kulland???m k?saltmalard?r. Kitap sonundaki “K?saltmalar” tablosunda tüm k?saltmalar? listelemeye ?al??t?m. Ayr?ca bir?ok terimin ?ngilizcesini de parantez i?inde vermeye ?al??t?m. ?rne?in Veritabanlar? (Database) gibi. Dilimize girmi? bir?ok yabanc? teknik terim ve kelimelerin Türk?esini kullanmaya ?zen g?sterdim ve bu yabanc? kelimeleri de parantez i?inde yazd?m. Ayr?ca BT’lerin BS’ler vas?tas?yla i?letmeler üzerindeki etkilerini incelerken, birazda üniversitelerimizde YBS b?lümlerinde okutulan BS’lerle ilgili uzmanl?k konular?n?n ?o?unu ?zetlemeye ?al??t?m. ?zellikle i? Dünyas?nda ?ok?a kullan?lan baz? konulara (V?S, YBS, KDS, VT, VA, BY, US, KKP, M?Y, Sistem yakla??m?, SGYD vs.) biraz detayl? bakmaya ?al??t?m. K?sacas? kitapta i?letmelerde Bili?im Teknolojileri ve Sistemleri denince akla gelebilecek bir?ok konuya de?inmeye ?al??t?m. Bu yüzden bu kitab?n BS alan?nda bir elkitab? veya kaynak kitap olarak dü?ünülmesinde fayda vard?r. Bu kitapta ilkokul ??retmenim Say?n ?erare ?zya?c? han?mdan, en son Doktora tez dan??man?m say?n Prof. Dr. Len Rogers’a kadar yüzlerce ki?inin eme?inin oldu?u unutulmamal?d?r. 1984’ten beri Türkiye, ABD, Kanada ve ?ngiltere de ?al??t???m veya dan??manl???n? yapt???m onlarca firma ve mü?terilerimin katk?lar?n? unutabilir miyim? Burada isim isim te?ekkür edemedi?im ancak bu kitab?n yaz?lmas?nda katk?lar? olan daha yüzlerce ki?i var, hepsine en i?ten dileklerimle te?ekkür ederim. Hayatta neyi tek ba??m?za yapabiliyoruz ki? Bu kitap 30+ y?ld?r üretim planlama ve stok kontrol müdürü, metot etüdcü, sistem analisti, programc?, VT tasar?mc?s?

Plan and build useful machine learning systems for financial services, with full working Python code Key Features * Build machine learning systems that will be useful across the financial services industry * Discover how machine learning can solve finance industry challenges * Gain the machine learning insights and skills fintech companies value most Book Description Machine learning skills are essential for anybody working in financial data analysis. Machine Learning for Finance shows you how to build machine learning models for use in financial services organizations. It shows you how to work with all the key machine learning models, from simple regression to advanced neural networks. You will see how to use machine learning to automate manual tasks, identify and address systemic bias, and find new insights and patterns hidden in available data. Machine Learning for Finance encourages and equips you to find new ways to use data to serve an organization’s business goals. Broad in scope yet deeply practical in approach, Machine Learning for Finance will help you to apply machine learning in all parts of a financial organization’s infrastructure. If you work or plan to work in fintech, and want to gain one of the most valuable skills in the sector today, this book is for you. What you will learn * Practical machine learning for the finance sector * Build machine learning systems that support the goals of financial organizations * Think creatively about problems and how machine learning can solve them * Identify and reduce sources of bias from machine learning models * Apply machine learning to structured data, natural language, photographs, and written text related to finance * Use machine learning to detect fraud, forecast financial trends, analyze customer sentiments, and more * Implement heuristic baselines, time series, generative models, and reinforcement learning in Python, scikit-learn, Keras, and TensorFlow Who this book is for Machine Learning for Finance is for financial professionals who want to develop and apply machine learning skills, and for students entering the field. You should be comfortable with Python and the basic data science stack, such as NumPy, pandas, and Matplotlib, to get the most out of this book.

Implement Business Central and explore methods to upgrade to NAV 2018 Key Features *Learn the key roles of Dynamics NAV partner and the roles within your customer's organization *Create configuration packages and perform data migration *Explore Microsoft Dynamics 365 Business Central to use Dynamics NAV 2018 functionalities in the Cloud Book Description Microsoft Dynamics Business Central is a full business solution suite and a complete ERP solution, which contains a robust set of development tools; these tools can help you to gain control over your business and can simplify supply chains, manufacturing, and operations. Implementing Microsoft Dynamics 365 Business Central On-Premise covers the latest features of Dynamics Business Central and NAV from the end users' and developers' perspectives. It also provides an insight into different tools available for implementation, whether it's a new installation or migrating from the previous version of Dynamics NAV. This book will take you from an introduction to Dynamics NAV 2018 through to exploring all the techniques related to implementation and migration. You will also learn to expand functionalities within your existing Microsoft Dynamics NAV installation, perform data analysis, and implement free third-party add-ons to your existing installation. As you progress through the book, you will learn to work with third-party add-on tools. In the concluding chapters, you will explore Dynamics 365 Business Central, the new Cloud solution based on the Microsoft NAV platform, and techniques for using Docker and Sandbox to develop applications. By the end of the book, you will have gained a deep understanding of the key components for successful Dynamics NAV implementation for an organization. What you will learn *Explore new features introduced in Microsoft Dynamics NAV 2018 *Migrate to Microsoft Dynamics NAV 2018 from previous versions *Learn abstract techniques for data analysis, reporting, and debugging *Install, configure, and use additional tools for business intelligence, document management, and reporting *Discover Dynamics 365 Business Central and several other Microsoft services *Utilize different tools to develop applications for Business Central Who this book is for Implementing Microsoft Dynamics 365 Business Central On-Premise is for Dynamics NAV partners and end users who want to know everything about Dynamics NAV implementation. This book is for you if you want to be a project manager or get involved with Dynamics NAV, but do not have the expertise to write code yourself. This book can also help you to understand the need to move to Business Central and its advantages.

Understand the nitty-gritty of Cybersecurity with ease Key Features * Align your security knowledge with industry leading concepts and tools * Acquire required skills and certifications to survive the ever changing market needs * Learn from industry experts to analyse, implement, and maintain a robust environment Book Description It's not a secret that there is a huge talent gap in the cybersecurity industry. Everyone is talking about it including the prestigious Forbes Magazine, Tech Republic, CSO Online, DarkReading, and SC Magazine, among many others. Additionally, Fortune CEO's like Satya Nadella, McAfee's CEO Chris Young, Cisco's CIO Colin Seward along with organizations like ISSA, research firms like Gartner too shine light on it from time to time. This book put together all the possible information with regards to cybersecurity, why you should choose it, the need for cyber security and how can you be part of it and fill the cybersecurity talent gap bit by bit. Starting with the essential understanding of security and its needs, we will move to security domain changes and how artificial intelligence and machine learning are helping to secure systems. Later, this book will walk you through all the skills and tools that everyone who wants to work as security personal need to be aware of. Then, this book will teach readers how to think like an attacker and explore some advanced security methodologies. Lastly, this book will deep dive into how to build practice labs, explore real-world use cases and get acquainted with various cybersecurity certifications. By the end of this book, readers will be well-versed with the security domain and will be capable of making the right choices in the cybersecurity field. What you will learn * Get an overview of what cybersecurity is and learn about the various faces of cybersecurity as well as identify domain that suits you best * Plan your transition into cybersecurity in an efficient and effective way * Learn how to build upon your existing skills and experience in order to prepare for your career in cybersecurity Who this book is for This book is targeted to any IT professional who is looking to venture in to the world cyber attacks and threats. Anyone with some understanding or IT infrastructure workflow will benefit from this book. Cybersecurity experts interested in enhancing their skill set will also find this book useful.

Concepts, tools, and techniques to explore deep learning architectures and methodologies Key Features * Explore advanced deep learning architectures using various datasets and frameworks * Implement deep architectures for neural network models such as CNN, RNN, GAN, and many more * Discover design patterns and different challenges for various deep learning architectures Book Description Deep learning architectures are composed of multilevel nonlinear operations that represent high-level abstractions; this allows you to learn useful feature representations from the data. This book will help you learn and implement deep learning architectures to resolve various deep learning research problems. Hands-On Deep Learning Architectures with Python explains the essential learning algorithms used for deep and shallow architectures. Packed with practical implementations and ideas to help you build efficient artificial intelligence systems (AI), this book will help you learn how neural networks play a major role in building deep architectures. You will understand various deep learning architectures (such as AlexNet, VGG Net, GoogleNet) with easy-to-follow code and diagrams. In addition to this, the book will also guide you in building and training various deep architectures such as the Boltzmann mechanism, autoencoders, convolutional neural networks (CNNs), recurrent neural networks (RNNs), natural language processing (NLP), GAN, and more—all with practical implementations. By the end of this book, you will be able to construct deep models using popular frameworks and datasets with the required design patterns for each architecture. You will be ready to explore the potential of deep architectures in today's world. What you will learn * Implement CNNs, RNNs, and other commonly used architectures with Python * Explore architectures such as VGGNet, AlexNet, and GoogLeNet * Build deep learning architectures for AI applications such as face and image recognition, fraud detection, and many more * Understand the architectures and applications of Boltzmann machines and autoencoders with concrete examples * Master artificial intelligence and neural network concepts and apply them to your architecture * Understand deep learning architectures for mobile and embedded systems Who this book is for If you’re a data scientist, machine learning developer/engineer, or deep learning practitioner, or are curious about AI and want to upgrade your knowledge of various deep learning architectures, this book will appeal to you. You are expected to have some knowledge of statistics and machine learning algorithms to get the best out of this book

Design and create neural networks with deep learning and artificial intelligence principles using OpenAI Gym, TensorFlow, and Keras Key Features * Explore neural network architecture and understand how it functions * Learn algorithms to solve common problems using back propagation and perceptrons * Understand how to apply neural networks to applications with the help of useful illustrations Book Description Neural networks play a very important role in deep learning and artificial intelligence (AI), with applications in a wide variety of domains, right from medical diagnosis, to financial forecasting, and even machine diagnostics. Hands-On Neural Networks is designed to guide you through learning about neural networks in a practical way. The book will get you started by giving you a brief introduction to perceptron networks. You will then gain insights into machine learning and also understand what the future of AI could look like. Next, you will study how embeddings can be used to process textual data and the role of long short-term memory networks (LSTMs) in helping you solve common natural language processing (NLP) problems. The later chapters will demonstrate how you can implement advanced concepts including transfer learning, generative adversarial networks (GANs), autoencoders, and reinforcement learning. Finally, you can look forward to further content on the latest advancements in the field of neural networks. By the end of this book, you will have the skills you need to build, train, and optimize your own neural network model that can be used to provide predictable solutions. What you will learn * Learn how to train a network by using backpropagation * Discover how to load and transform images for use in neural networks * Study how neural networks can be applied to a varied set of applications * Solve common challenges faced in neural network development * Understand the transfer learning concept to solve tasks using Keras and Visual Geometry Group (VGG) network * Get up to speed with advanced and complex deep learning concepts like LSTMs and NLP * Explore innovative algorithms like GANs and deep reinforcement learning Who this book is for If you are interested in artificial intelligence and deep learning and want to further your skills, then this intermediate-level book is for you. Some knowledge of statistics will help you get the most out of this book.

A practical guide to building high performance systems for object detection, segmentation, video processing, smartphone applications, and more. This book is based on the alpha version of TensorFlow 2. Key Features * Discover how to build, train, and serve your own deep neural networks with TensorFlow 2 and Keras * Apply modern solutions to a wide range of applications such as object detection and video analysis * Learn how to run your models on mobile devices and webpages and improve their performance Book Description Computer vision solutions are becoming increasingly common, making their way in fields such as health, automobile, social media, and robotics. This book will help you explore TensorFlow 2, the brand new version of Google's open source framework for machine learning. You will understand how to benefit from using convolutional neural networks (CNNs) for visual tasks. Hands-On Computer Vision with TensorFlow 2 starts with the fundamentals of computer vision and deep learning, teaching you how to build a neural network from scratch. You will discover the features that have made TensorFlow the most widely used AI library, along with its intuitive Keras interface, and move on to building, training, and deploying CNNs efficiently. Complete with concrete code examples, the book demonstrates how to classify images with modern solutions, such as Inception and ResNet, and extract specific content using You Only Look Once (YOLO), Mask R-CNN, and U-Net. You will also build Generative Adversarial Networks (GANs) and Variational Auto-Encoders (VAEs) to create and edit images, and LSTMs to analyze videos. In the process, you will acquire advanced insights into transfer learning, data augmentation, domain adaptation, and mobile and web deployment, among other key concepts. By the end of the book, you will have both the theoretical understanding and practical skills to solve advanced computer vision problems with TensorFlow 2.0. What you will learn * Create your own neural networks from scratch * Classify images with modern architectures including Inception and ResNet * Detect and segment objects in images with YOLO, Mask R-CNN, and U-Net * Tackle problems in developing self-driving cars and facial emotion recognition systems * Boost your application’s performance with transfer learning, GANs, and domain adaptation * Use recurrent neural networks for video analysis * Optimize and deploy your networks on mobile devices and in the browser Who this book is for If you’re new to deep learning and have some background in Python programming and image processing, like reading/writing image files and editing pixels, this book is for you. Even if you’re an expert curious about the new TensorFlow 2 features, you’ll find this book useful. While some theoretical explanations require knowledge in algebra and calculus, the book covers concrete examples for learners focused on practical applications such as visual recognition for self-driving cars and smartphone apps.

Build and train scalable neural network models on various platforms by leveraging the power of Caffe2 Key Features * Migrate models trained with other deep learning frameworks on Caffe2 * Integrate Caffe2 with Android or iOS and implement deep learning models for mobile devices * Leverage the distributed capabilities of Caffe2 to build models that scale easily Book Description Caffe2 is a popular deep learning library used for fast and scalable training and inference of deep learning models on various platforms. This book introduces you to the Caffe2 framework and shows how you can leverage its power to build, train, and deploy efficient neural network models at scale. It will cover the topics of installing Caffe2, composing networks using its operators, training models, and deploying models to different architectures. It will also show how to import models from Caffe and from other frameworks using the ONNX interchange format. It covers the topic of deep learning accelerators such as CPU and GPU and shows how to deploy Caffe2 models for inference on accelerators using inference engines. Caffe2 is built for deployment to a diverse set of hardware, using containers on the cloud and resource constrained hardware such as Raspberry Pi, which will be demonstrated. By the end of this book, you will be able to not only compose and train popular neural network models with Caffe2, but also be able to deploy them on accelerators, to the cloud and on resource constrained platforms such as mobile and embedded hardware. What you will learn * Build and install Caffe2 * Compose neural networks * Train neural network on CPU or GPU * Import a neural network from Caffe * Import deep learning models from other frameworks * Deploy models on CPU or GPU accelerators using inference engines * Deploy models at the edge and in the cloud Who this book is for Data scientists and machine learning engineers who wish to create fast and scalable deep learning models in Caffe2 will find this book to be very useful. Some understanding of the basic machine learning concepts and prior exposure to programming languages like C++ and Python will be useful.

Get to grips with pandas—a versatile and high-performance Python library for data manipulation, analysis, and discovery Key Features * Perform efficient data analysis and manipulation tasks using pandas * Apply pandas to different real-world domains using step-by-step demonstrations * Get accustomed to using pandas as an effective data exploration tool Book Description Data analysis has become a necessary skill in a variety of positions where knowing how to work with data and extract insights can generate significant value. Hands-On Data Analysis with Pandas will show you how to analyze your data, get started with machine learning, and work effectively with Python libraries often used for data science, such as pandas, NumPy, matplotlib, seaborn, and scikit-learn. Using real-world datasets, you will learn how to use the powerful pandas library to perform data wrangling to reshape, clean, and aggregate your data. Then, you will learn how to conduct exploratory data analysis by calculating summary statistics and visualizing the data to find patterns. In the concluding chapters, you will explore some applications of anomaly detection, regression, clustering, and classification, using scikit-learn, to make predictions based on past data. By the end of this book, you will be equipped with the skills you need to use pandas to ensure the veracity of your data, visualize it for effective decision-making, and reliably reproduce analyses across multiple datasets. What you will learn * Understand how data analysts and scientists gather and analyze data * Perform data analysis and data wrangling in Python * Combine, group, and aggregate data from multiple sources * Create data visualizations with pandas, matplotlib, and seaborn * Apply machine learning (ML) algorithms to identify patterns and make predictions * Use Python data science libraries to analyze real-world datasets * Use pandas to solve common data representation and analysis problems * Build Python scripts, modules, and packages for reusable analysis code Who this book is for This book is for data analysts, data science beginners, and Python developers who want to explore each stage of data analysis and scientific computing using a wide range of datasets. You will also find this book useful if you are a data scientist who is looking to implement pandas in machine learning. Working knowledge of Python programming language will be beneficial.

Practical solutions to overcome challenges in creating console and web applications and working with systems-level and embedded code, network programming, deep neural networks, and much more. Key Features * Work through recipes featuring advanced concepts such as concurrency, unsafe code, and macros to migrate your codebase to the Rust programming language * Learn how to run machine learning models with Rust * Explore error handling, macros, and modularization to write maintainable code Book Description Rust 2018, Rust's first major milestone since version 1.0, brings more advancement in the Rust language. The Rust Programming Cookbook is a practical guide to help you overcome challenges when writing Rust code. This Rust book covers recipes for configuring Rust for different environments and architectural designs, and provides solutions to practical problems. It will also take you through Rust's core concepts, enabling you to create efficient, high-performance applications that use features such as zero-cost abstractions and improved memory management. As you progress, you'll delve into more advanced topics, including channels and actors, for building scalable, production-grade applications, and even get to grips with error handling, macros, and modularization to write maintainable code. You will then learn how to overcome common roadblocks when using Rust for systems programming, IoT, web development, and network programming. Finally, you'll discover what Rust 2018 has to offer for embedded programmers. By the end of the book, you'll have learned how to build fast and safe applications and services using Rust. What you will learn * Understand how Rust provides unique solutions to solve system programming language problems * Grasp the core concepts of Rust to develop fast and safe applications * Explore the possibility of integrating Rust units into existing applications for improved efficiency * Discover how to achieve better parallelism and security with Rust * Write Python extensions in Rust * Compile external assembly files and use the Foreign Function Interface (FFI) * Build web applications and services using Rust for high performance Who this book is for The Rust cookbook is for software developers looking to enhance their knowledge of Rust and leverage its features using modern programming practices. Familiarity with Rust language is expected to get the most out of this book.

Simplify your DevOps roles with DevOps tools and techniques Key Features * Learn to utilize business resources effectively to increase productivity and collaboration * Leverage the ultimate open source DevOps tools to achieve continuous integration and continuous delivery (CI/CD) * Ensure faster time-to-market by reducing overall lead time and deployment downtime Book Description The implementation of DevOps processes requires the efficient use of various tools, and the choice of these tools is crucial for the sustainability of projects and collaboration between development (Dev) and operations (Ops). This book presents the different patterns and tools that you can use to provision and configure an infrastructure in the cloud. You'll begin by understanding DevOps culture, the application of DevOps in cloud infrastructure, provisioning with Terraform, configuration with Ansible, and image building with Packer. You'll then be taken through source code versioning with Git and the construction of a DevOps CI/CD pipeline using Jenkins, GitLab CI, and Azure Pipelines. This DevOps handbook will also guide you in containerizing and deploying your applications with Docker and Kubernetes. You'll learn how to reduce deployment downtime with blue-green deployment and the feature flags technique, and study DevOps practices for open source projects. Finally, you'll grasp some best practices for reducing the overall application lead time to ensure faster time to market. By the end of this book, you'll have built a solid foundation in DevOps, and developed the skills necessary to enhance a traditional software delivery process using modern software delivery tools and techniques What you will learn * Become well versed with DevOps culture and its practices * Use Terraform and Packer for cloud infrastructure provisioning * Implement Ansible for infrastructure configuration * Use basic Git commands and understand the Git flow process * Build a DevOps pipeline with Jenkins, Azure Pipelines, and GitLab CI * Containerize your applications with Docker and Kubernetes * Check application quality with SonarQube and Postman * Protect DevOps processes and applications using DevSecOps tools Who this book is for If you are a developer or a system administrator interested in understanding continuous integration, continuous delivery, and containerization with DevOps tools and techniques, this book is for you.

Push the limits of what C - and you - can do, with this high-intensity guide to the most advanced capabilities of C Key Features * Make the most of C’s low-level control, flexibility, and high performance * A comprehensive guide to C’s most powerful and challenging features * A thought-provoking guide packed with hands-on exercises and examples Book Description There’s a lot more to C than knowing the language syntax. The industry looks for developers with a rigorous, scientific understanding of the principles and practices. Extreme C will teach you to use C’s advanced low-level power to write effective, efficient systems. This intensive, practical guide will help you become an expert C programmer. Building on your existing C knowledge, you will master preprocessor directives, macros, conditional compilation, pointers, and much more. You will gain new insight into algorithm design, functions, and structures. You will discover how C helps you squeeze maximum performance out of critical, resource-constrained applications. C still plays a critical role in 21st-century programming, remaining the core language for precision engineering, aviations, space research, and more. This book shows how C works with Unix, how to implement OO principles in C, and fully covers multi-processing. In Extreme C, Amini encourages you to think, question, apply, and experiment for yourself. The book is essential for anybody who wants to take their C to the next level. What you will learn * Build advanced C knowledge on strong foundations, rooted in first principles * Understand memory structures and compilation pipeline and how they work, and how to make most out of them * Apply object-oriented design principles to your procedural C code * Write low-level code that’s close to the hardware and squeezes maximum performance out of a computer system * Master concurrency, multithreading, multi-processing, and integration with other languages * Unit Testing and debugging, build systems, and inter-process communication for C programming Who this book is for Extreme C is for C programmers who want to dig deep into the language and its capabilities. It will help you make the most of the low-level control C gives you.

Implement reinforcement learning techniques and algorithms with the help of real-world examples and recipes Key Features * Use PyTorch 1.x to design and build self-learning artificial intelligence (AI) models * Implement RL algorithms to solve control and optimization challenges faced by data scientists today * Apply modern RL libraries to simulate a controlled environment for your projects Book Description Reinforcement learning (RL) is a branch of machine learning that has gained popularity in recent times. It allows you to train AI models that learn from their own actions and optimize their behavior. PyTorch has also emerged as the preferred tool for training RL models because of its efficiency and ease of use. With this book, you'll explore the important RL concepts and the implementation of algorithms in PyTorch 1.x. The recipes in the book, along with real-world examples, will help you master various RL techniques, such as dynamic programming, Monte Carlo simulations, temporal difference, and Q-learning. You'll also gain insights into industry-specific applications of these techniques. Later chapters will guide you through solving problems such as the multi-armed bandit problem and the cartpole problem using the multi-armed bandit algorithm and function approximation. You'll also learn how to use Deep Q-Networks to complete Atari games, along with how to effectively implement policy gradients. Finally, you'll discover how RL techniques are applied to Blackjack, Gridworld environments, internet advertising, and the Flappy Bird game. By the end of this book, you'll have developed the skills you need to implement popular RL algorithms and use RL techniques to solve real-world problems. What you will learn * Use Q-learning and the state–action–reward–state–action (SARSA) algorithm to solve various Gridworld problems * Develop a multi-armed bandit algorithm to optimize display advertising * Scale up learning and control processes using Deep Q-Networks * Simulate Markov Decision Processes, OpenAI Gym environments, and other common control problems * Select and build RL models, evaluate their performance, and optimize and deploy them * Use policy gradient methods to solve continuous RL problems Who this book is for Machine learning engineers, data scientists and AI researchers looking for quick solutions to different reinforcement learning problems will find this book useful. Although prior knowledge of machine learning concepts is required, experience with PyTorch will be useful but not necessary.

Explore GPU-enabled programmable environment for machine learning, scientific applications, and gaming using PuCUDA, PyOpenGL, and Anaconda Accelerate Key Features * Understand effective synchronization strategies for faster processing using GPUs * Write parallel processing scripts with PyCuda and PyOpenCL * Learn to use the CUDA libraries like CuDNN for deep learning on GPUs Book Description GPUs are proving to be excellent general purpose-parallel computing solutions for high performance tasks such as deep learning and scientific computing. This book will be your guide to getting started with GPU computing. It will start with introducing GPU computing and explain the architecture and programming models for GPUs. You will learn, by example, how to perform GPU programming with Python, and you’ll look at using integrations such as PyCUDA, PyOpenCL, CuPy and Numba with Anaconda for various tasks such as machine learning and data mining. Going further, you will get to grips with GPU work flows, management, and deployment using modern containerization solutions. Toward the end of the book, you will get familiar with the principles of distributed computing for training machine learning models and enhancing efficiency and performance. By the end of this book, you will be able to set up a GPU ecosystem for running complex applications and data models that demand great processing capabilities, and be able to efficiently manage memory to compute your application effectively and quickly. What you will learn * Utilize Python libraries and frameworks for GPU acceleration * Set up a GPU-enabled programmable machine learning environment on your system with Anaconda * Deploy your machine learning system on cloud containers with illustrated examples * Explore PyCUDA and PyOpenCL and compare them with platforms such as CUDA, OpenCL and ROCm. * Perform data mining tasks with machine learning models on GPUs * Extend your knowledge of GPU computing in scientific applications Who this book is for Data Scientist, Machine Learning enthusiasts and professionals who wants to get started with GPU computation and perform the complex tasks with low-latency. Intermediate knowledge of Python programming is assumed.

Design, deploy, and manage large-scale containers using Kubernetes Key Features * Gain insight into the latest features of Kubernetes, including Prometheus and API aggregation * Discover ways to keep your clusters always available, scalable, and up-to-date * Master the skills of designing and deploying large clusters on various cloud platforms Book Description If you are running a number of containers and want to be able to automate the way they’re managed, it can be helpful to have Kubernetes at your disposal. This Learning Path guides you through core Kubernetes constructs, such as pods, services, replica sets, replication controllers, and labels. You'll get started by learning how to integrate your build pipeline and deployments in a Kubernetes cluster. As you cover more chapters in the Learning Path, you'll get up to speed with orchestrating updates behind the scenes, avoiding downtime on your cluster, and dealing with underlying cloud provider instability in your cluster. With the help of real-world use cases, you'll also explore options for network configuration, and understand how to set up, operate, and troubleshoot various Kubernetes networking plugins. In addition to this, you'll gain insights into custom resource development and utilization in automation and maintenance workflows. By the end of this Learning Path, you'll have the expertise you need to progress from an intermediate to an advanced level of understanding Kubernetes. This Learning Path includes content from the following Packt products: * Getting Started with Kubernetes - Third Edition by Jonathan Baier and Jesse White * Mastering Kubernetes - Second Edition by Gigi Sayfan What you will learn * Download, install, and configure the Kubernetes code base * Create and configure custom Kubernetes resources * Use third-party resources in your automation workflows * Deliver applications as standard packages * Set up and access monitoring and logging for Kubernetes clusters * Set up external access to applications running in the cluster * Manage and scale Kubernetes with hosted platforms on Amazon Web Services (AWS), Azure, and Google Cloud Platform (GCP) * Run multiple clusters and manage them from a single control plane Who this book is for If you are a developer or a system administrator with an intermediate understanding of Kubernetes and want to master its advanced features, then this book is for you. Basic knowledge of networking is required to easily understand the concepts explained.