Mastering Machine Learning with scikit-learn. Apply effective learning algorithms to real-world problems using scikit-learn - Second Edition

Gavin Hackeling

Machine learning is the buzzword bringing computer science and statistics together to build smart and efficient models. Using powerful algorithms and techniques offered by machine learning you can automate any analytical model.This book examines a variety of machine learning models including popular machine learning algorithms such as k-nearest neighbors, logistic regression, naive Bayes, k-means, decision trees, and artificial neural networks. It discusses data preprocessing, hyperparameter optimization, and ensemble methods. You will build systems that classify documents, recognize images, detect ads, and more. You will learn to use scikit-learn’s API to extract features from categorical variables, text and images; evaluate model performance, and develop an intuition for how to improve your model’s performance.By the end of this book, you will master all required concepts of scikit-learn to build efficient models at work to carry out advanced tasks with the practical approach.

Modular Programming in Java 9. Build large scale applications using Java modularity and Project Jigsaw

Koushik Srinivas Kothagal

The Java 9 module system is an important addition to the language that affects the way we design, write, and organize code and libraries in Java. It provides a new way to achieve maintainable code by the encapsulation of Java types, as well as a way to write better libraries that have clear interfaces. Effectively using the module system requires an understanding of how modules work and what the best practices of creating modules are.This book will give you step-by-step instructions to create new modules as well as migrate code from earlier versions of Java to the Java 9 module system. You'll be working on a fully modular sample application and add features to it as you learn about Java modules. You'll learn how to create module definitions, setup inter-module dependencies, and use the built-in modules from the modular JDK. You will also learn about module resolution and how to use jlink to generate custom runtime images.We will end our journey by taking a look at the road ahead. You will learn some powerful best practices that will help you as you start building modular applications. You will also learn how to upgrade an existing Java 8 codebase to Java 9, handle issues with libraries, and how to test Java 9 applications.

Mastering Spring Cloud. Build self-healing, microservices-based, distributed systems using Spring Cloud

Piotr Mińkowski

Developing, deploying, and operating cloud applications should be as easy as local applications. This should be the governing principle behind any cloud platform, library, or tool. Spring Cloud–an open-source library–makes it easy to develop JVM applications for the cloud. In this book, you will be introduced to Spring Cloud and will master its features from the application developer's point of view. This book begins by introducing you to microservices for Spring and the available feature set in Spring Cloud. You will learn to configure the Spring Cloud server and run the Eureka server to enable service registration and discovery. Then you will learn about techniques related to load balancing and circuit breaking and utilize all features of the Feign client. The book now delves into advanced topics where you will learn to implement distributed tracing solutions for Spring Cloud and build message-driven microservice architectures. Before running an application on Docker container s, you will master testing and securing techniques with Spring Cloud.

Matplotlib 3.0 Cookbook. Over 150 recipes to create highly detailed interactive visualizations using Python

Srinivasa Rao Poladi

Matplotlib provides a large library of customizable plots, along with a comprehensive set of backends. Matplotlib 3.0 Cookbook is your hands-on guide to exploring the world of Matplotlib, and covers the most effective plotting packages for Python 3.7. With the help of this cookbook, you'll be able to tackle any problem you might come across while designing attractive, insightful data visualizations. With the help of over 150 recipes, you'll learn how to develop plots related to business intelligence, data science, and engineering disciplines with highly detailed visualizations. Once you've familiarized yourself with the fundamentals, you'll move on to developing professional dashboards with a wide variety of graphs and sophisticated grid layouts in 2D and 3D. You'll annotate and add rich text to the plots, enabling the creation of a business storyline. In addition to this, you'll learn how to save figures and animations in various formats for downstream deployment, followed by extending the functionality offered by various internal and third-party toolkits, such as axisartist, axes_grid, Cartopy, and Seaborn. By the end of this book, you'll be able to create high-quality customized plots and deploy them on the web and on supported GUI applications such as Tkinter, Qt 5, and wxPython by implementing real-world use cases and examples.

Reactive Programming with Swift 4. Build asynchronous reactive applications with easy-to-maintain and clean code using RxSwift and Xcode 9

Navdeep Singh

RxSwift belongs to a large family of Rx implementations in different programming languages that share almost identical syntax and semantics. Reactive approach will help you to write clean, cohesive, resilient, scalable, and maintainable code with highly configurable behavior.This book will introduce you to the world of reactive programming, primarily focusing on mobile platforms. It will tell how you can benefit from using RxSwift in your projects, existing or new. Further on, the book will demonstrate the unbelievable ease of configuring asynchronous behavior and other aspects of the app that are traditionally considered to be hard to implement and maintain. It will explain what Rx is made of, and how to switch to reactive way of thinking to get the most out of it. Also, test production code using RxTest and the red/ green approach. Finally, the book will dive into real-world recipes and show you how to build a real-world app by applying the reactive paradigm.By the end of the book, you’ll be able to build a reactive swift application by leveraging all the concepts this book takes you through.

Hands-On Data Science with Anaconda. Utilize the right mix of tools to create high-performance data science applications

Yuxing Yan, James Yan

Anaconda is an open source platform that brings together the best tools for data science professionals with more than 100 popular packages supporting Python, Scala, and R languages. Hands-On Data Science with Anaconda gets you started with Anaconda and demonstrates how you can use it to perform data science operations in the real world.The book begins with setting up the environment for Anaconda platform in order to make it accessible for tools and frameworks such as Jupyter, pandas, matplotlib, Python, R, Julia, and more. You’ll walk through package manager Conda, through which you can automatically manage all packages including cross-language dependencies, and work across Linux, macOS, and Windows. You’ll explore all the essentials of data science and linear algebra to perform data science tasks using packages such as SciPy, contrastive, scikit-learn, Rattle, and Rmixmod. Once you’re accustomed to all this, you’ll start with operations in data science such as cleaning, sorting, and data classification. You’ll move on to learning how to perform tasks such as clustering, regression, prediction, and building machine learning models and optimizing them. In addition to this, you’ll learn how to visualize data using the packages available for Julia, Python, and R.

NativeScript for Angular Mobile Development. Creating dynamic mobile apps for iOS and Android

Nathan Walker, Nathanael J. Anderson

NativeScript is an open source framework that is built by Progress in order to build truly native mobile apps with TypeScript, JavaScript or just Angular which is an open source framework built by Google that offers declarative templates, dependency injection, and fully featured modules to build rich applications. Angular’s versatile view handling architecture allows your views to be rendered as highly performant UI components native to iOS and Android mobile platforms. This decoupling of the view rendering layer in Angular combined with the power of native APIs with NativeScript have together created the powerful and exciting technology stack of NativeScript for Angular.This book focuses on the key concepts that you will need to know to build a NativeScript for Angular mobile app for iOS and Android. We’ll build a fun multitrack recording studio app, touching on powerful key concepts from both technologies that you may need to know when you start building an app of your own. The structure of the book takes the reader from a void to a deployed app on both the App Store and Google Play, serving as a reference guide and valuable tips/tricks handbook.By the end of this book, you’ll know majority of key concepts needed to build a successful NativeScript for Angular app.

CCNA Security 210-260 Certification Guide. Build your knowledge of network security and pass your CCNA Security exam (210-260)

Glen D. Singh, Michael Vinod, Vijay Anandh

With CCNA Security certification, a network professional can demonstrate the skills required to develop security infrastructure, recognize threats and vulnerabilities to networks, and mitigate security threats. The CCNA Security 210-260 Certification Guide will help you grasp the fundamentals of network security and prepare you for the Cisco CCNA Security Certification exam.You’ll begin by getting a grip on the fundamentals of network security and exploring the different tools available. Then, you’ll see how to securely manage your network devices by implementing the AAA framework and configuring different management plane protocols.Next, you’ll learn about security on the data link layer by implementing various security toolkits. You’ll be introduced to various firewall technologies and will understand how to configure a zone-based firewall on a Cisco IOS device. You’ll configure a site-to-site VPN on a Cisco device and get familiar with different types of VPNs and configurations. Finally, you’ll delve into the concepts of IPS and endpoint security to secure your organization’s network infrastructure.By the end of this book, you’ll be ready to take the CCNA Security Exam (210-260).

Kali Linux 2018: Windows Penetration Testing. Conduct network testing, surveillance, and pen testing on MS Windows using Kali Linux 2018 - Second Edition

Wolf Halton, Bo Weaver

Microsoft Windows is one of the two most common OSes, and managing its security has spawned the discipline of IT security. Kali Linux is the premier platform for testing and maintaining Windows security. Kali is built on the Debian distribution of Linux and shares the legendary stability of that OS. This lets you focus on using the network penetration, password cracking, and forensics tools, and not the OS.This book has the most advanced tools and techniques to reproduce the methods used by sophisticated hackers to make you an expert in Kali Linux penetration testing. You will start by learning about the various desktop environments that now come with Kali. The book covers network sniffers and analysis tools to uncover the Windows protocols in use on the network. You will see several tools designed to improve your average in password acquisition, from hash cracking, online attacks, offline attacks, and rainbow tables to social engineering. It also demonstrates several use cases for Kali Linux tools like Social Engineering Toolkit, and Metasploit, to exploit Windows vulnerabilities.Finally, you will learn how to gain full system-level access to your compromised system and then maintain that access. By the end of this book, you will be able to quickly pen test your system and network using easy-to-follow instructions and support images.

Hands-On Deep Learning with TensorFlow. Uncover what is underneath your data!

Dan Van Boxel

Dan Van Boxel’s Deep Learning with TensorFlow is based on Dan’s best-selling TensorFlow video course. With deep learning going mainstream, making sense of data and getting accurate results using deep networks is possible. Dan Van Boxel will be your guide to exploring the possibilities with deep learning; he will enable you to understand data like never before. With the efficiency and simplicity of TensorFlow, you will be able to process your data and gain insights that will change how you look at data.With Dan’s guidance, you will dig deeper into the hidden layers of abstraction using raw data. Dan then shows you various complex algorithms for deep learning and various examples that use these deep neural networks. You will also learn how to train your machine to craft new features to make sense of deeper layers of data. In this book, Dan shares his knowledge across topics such as logistic regression, convolutional neural networks, recurrent neural networks, training deep networks, and high level interfaces. With the help of novel practical examples, you will become an ace at advanced multilayer networks, image recognition, and beyond.

Deep Learning with Theano. Perform large-scale numerical and scientific computations efficiently

Christopher Bourez

This book offers a complete overview of Deep Learning with Theano, a Python-based library that makes optimizing numerical expressions and deep learning models easy on CPU or GPU.The book provides some practical code examples that help the beginner understand how easy it is to build complex neural networks, while more experimented data scientists will appreciate the reach of the book, addressing supervised and unsupervised learning, generative models, reinforcement learning in the fields of image recognition, natural language processing, or game strategy.The book also discusses image recognition tasks that range from simple digit recognition, image classification, object localization, image segmentation, to image captioning. Natural language processing examples include text generation, chatbots, machine translation, and question answering. The last example deals with generating random data that looks real and solving games such as in the Open-AI gym. At the end, this book sums up the best -performing nets for each task. While early research results were based on deep stacks of neural layers, in particular, convolutional layers, the book presents the principles that improved the efficiency of these architectures, in order to help the reader build new custom nets.

Bootstrap 4 Cookbook. Solutions to common problems faced in Responsive Web Design

Ajdin Imsirovic

Bootstrap, one of the most popular front-end frameworks, is perfectly built to design elegant, powerful, and responsive interfaces for professional-level web pages. It supports responsive design by dynamically adjusting your web page layout.Bootstrap 4 is a major update with many impressive changes that greatly enhance the end results produced by Bootstrap. This cookbook is a collection of great recipes that show you how to use all the latest features of Bootstrap to build compelling UIs.This book is using the most up-to-date version of Bootstrap 4 in all its chapters. First off, you will be shown how you can leverage the latest core features of Bootstrap 4 to create stunning web pages and responsive media. You will gradually move on to extending Bootstrap 4 with the help of plugins to build highly customized and powerful UIs.By the end of this book, you will know how to leverage, extend, and integrate bootstrap to achieve optimal results for your web projects.

Learning Android Forensics. Analyze Android devices with the latest forensic tools and techniques - Second Edition

Oleg Skulkin, Donnie Tindall, Rohit Tamma

Many forensic examiners rely on commercial, push-button tools to retrieve and analyze data, even though there is no tool that does either of these jobs perfectly.Learning Android Forensics will introduce you to the most up-to-date Android platform and its architecture, and provide a high-level overview of what Android forensics entails. You will understand how data is stored on Android devices and how to set up a digital forensic examination environment. As you make your way through the chapters, you will work through various physical and logical techniques to extract data from devices in order to obtain forensic evidence. You will also learn how to recover deleted data and forensically analyze application data with the help of various open source and commercial tools. In the concluding chapters, you will explore malware analysis so that you’ll be able to investigate cybersecurity incidents involving Android malware.By the end of this book, you will have a complete understanding of the Android forensic process, you will have explored open source and commercial forensic tools, and will have basic skills of Android malware identification and analysis.

Practical Machine Learning Cookbook. Supervised and unsupervised machine learning simplified

Atul Tripathi

Machine learning has become the new black. The challenge in today’s world is the explosion of data from existing legacy data and incoming new structured and unstructured data. The complexity of discovering, understanding, performing analysis, and predicting outcomes on the data using machine learning algorithms is a challenge. This cookbook will help solve everyday challenges you face as a data scientist. The application of various data science techniques and on multiple data sets based on real-world challenges you face will help you appreciate a variety of techniques used in various situations.The first half of the book provides recipes on fairly complex machine-learning systems, where you’ll learn to explore new areas of applications of machine learning and improve its efficiency. That includes recipes on classifications, neural networks, unsupervised and supervised learning, deep learning, reinforcement learning, and more.The second half of the book focuses on three different machine learning case studies, all based on real-world data, and offers solutions and solves specific machine-learning issues in each one.

Data Analysis with Python. A Modern Approach

David Taieb

Data Analysis with Python offers a modern approach to data analysis so that you can work with the latest and most powerful Python tools, AI techniques, and open source libraries. Industry expert David Taieb shows you how to bridge data science with the power of programming and algorithms in Python. You'll be working with complex algorithms, and cutting-edge AI in your data analysis. Learn how to analyze data with hands-on examples using Python-based tools and Jupyter Notebook. You'll find the right balance of theory and practice, with extensive code files that you can integrate right into your own data projects.Explore the power of this approach to data analysis by then working with it across key industry case studies. Four fascinating and full projects connect you to the most critical data analysis challenges you’re likely to meet in today. The first of these is an image recognition application with TensorFlow – embracing the importance today of AI in your data analysis. The second industry project analyses social media trends, exploring big data issues and AI approaches to natural language processing. The third case study is a financial portfolio analysis application that engages you with time series analysis - pivotal to many data science applications today. The fourth industry use case dives you into graph algorithms and the power of programming in modern data science. You'll wrap up with a thoughtful look at the future of data science and how it will harness the power of algorithms and artificial intelligence.

Java for Data Science. Examine the techniques and Java tools supporting the growing field of data science

Richard M. Reese, Jennifer L. Reese

para 1: Get the lowdown on Java and explore big data analytics with Java for Data Science. Packed with examples and data science principles, this book uncovers the techniques & Java tools supporting data science and machine learning. Para 2: The stability and power of Java combines with key data science concepts for effective exploration of data. By working with Java APIs and techniques, this data science book allows you to build applications and use analysis techniques centred on machine learning. Para 3: Java for Data Science gives you the understanding you need to examine the techniques and Java tools supporting big data analytics. These Java-based approaches allow you to tackle data mining and statistical analysis in detail. Deep learning and Java data mining are also featured, so you can explore and analyse data effectively, and build intelligent applications using machine learning. para 4: What?s Inside ? Understand data science principles with Java support ? Discover machine learning and deep learning essentials ? Explore data science problems with Java-based solutions