Mike Driscoll takes you on a journey talking to a hall-of-fame list of truly remarkable Python experts. You’ll be inspired every time by their passion for the Python language, as they share with you their experiences, contributions, and careers in Python. About This Book ? Hear from these key Python thinkers about the current status of Python, and where it's heading in the future ? Listen to their close thoughts on significant Python topics, such as Python's role in scientific computing, and machine learning ? Understand the direction of Python, and what needs to change for Python 4 Who This Book Is For Python programmers and students interested in the way that Python is used – past and present – with useful anecdotes. It will also be of interest to those looking to gain insights from top programmers. What You Will Learn ? How successful programmers think ? The history of Python ? Insights into the minds of the Python core team ? Trends in Python programming In Detail Each of these twenty Python Interviews can inspire and refresh your relationship with Python and the people who make Python what it is today. Let these interviews spark your own creativity, and discover how you also have the ability to make your mark on a thriving tech community. This book invites you to immerse in the Python landscape, and let these remarkable programmers show you how you too can connect and share with Python programmers around the world. Learn from their opinions, enjoy their stories, and use their tech tips. ? Brett Cannon - former director of the PSF, Python core developer, led the migration to Python 3. ? Steve Holden - tireless Python promoter and former chairman and director of the PSF. ? Carol Willing - former director of the PSF and Python core developer, Project Jupyter Steering Council member. ? Nick Coghlan - founding member of the PSF and Python core developer. ? Jessica McKellar - former director of the PSF and Python activist. ? Marc-André Lemburg - Python core developer and founding member of the PSF. ? Glyph Lefkowitz - founder of Twisted and fellow of the PSF. ? Doug Hellmann - fellow of the PSF, creator of the Python Module of the Week blog, Python community member since 1998. ? Massimo Di Pierro - fellow of the PSF, data scientist and the inventor of web2py. ? Alex Martelli - fellow of the PSF and co-author of Python in a Nutshell. ? Barry Warsaw - fellow of the PSF, Python core developer since 1995, and original member of PythonLabs. ? Tarek Ziadé - founder of Afpy and author of Expert Python Programming. ? Sebastian Raschka - data scientist and author of Python Machine Learning. ? Wesley Chun - fellow of the PSF and author of the Core Python Programming books. ? Steven Lott - Python blogger and author of Python for Secret Agents. ? Oliver Schoenborn - author of Pypubsub and wxPython mailing list contributor. ? Al Sweigart - bestselling author and creator of the Python modules Pyperclip and PyAutoGUI. ? Luciano Ramalho - fellow of the PSF and the author of Fluent Python. ? Mike Bayer - fellow of the PSF, creator of open source libraries including SQLAlchemy. ? Jake Vanderplas - data scientist and author of Python Data Science Handbook. Style and approach This is a book of one-to-one interviews with leading Python programmers and luminaries in the field.

Untangle your web scraping complexities and access web data with ease using Python *s About This Book ? Hands-on recipes for advancing your web scraping skills to expert level. ? One-Stop Solution Guide to address complex and challenging web scraping tasks using Python. ? Understand the web page structure and collect meaningful data from the website with ease Who This Book Is For This book is ideal for Python programmers, web administrators, security professionals or someone who wants to perform web analytics would find this book relevant and useful. Familiarity with Python and basic understanding of web scraping would be useful to take full advantage of this book. What You Will Learn ? Use a wide variety of tools to scrape any website and data—including BeautifulSoup, Scrapy, Selenium, and many more ? Master expression languages such as XPath, CSS, and regular expressions to extract web data ? Deal with scraping traps such as hidden form fields, throttling, pagination, and different status codes ? Build robust scraping pipelines with SQS and RabbitMQ ? Scrape assets such as images media and know what to do when Scraper fails to run ? Explore ETL techniques of build a customized crawler, parser, and convert structured and unstructured data from websites ? Deploy and run your scraper-as-aservice in AWS Elastic Container Service In Detail Python Web Scraping Cookbook is a solution-focused book that will teach you techniques to develop high-performance scrapers and deal with crawlers, sitemaps, forms automation, Ajax-based sites, caches, and more.You'll explore a number of real-world scenarios where every part of the development/product life cycle will be fully covered. You will not only develop the skills to design and develop reliable, performance data flows, but also deploy your codebase to an AWS. If you are involved in software engineering, product development, or data mining (or are interested in building data-driven products), you will find this book useful as each recipe has a clear purpose and objective. Right from extracting data from the websites to writing a sophisticated web crawler, the book's independent recipes will be a godsend on the job. This book covers Python libraries, requests, and BeautifulSoup. You will learn about crawling, web spidering, working with AJAX websites, paginated items, and more. You will also learn to tackle problems such as 403 errors, working with proxy, scraping images, LXML, and more. By the end of this book, you will be able to scrape websites more efficiently and to be able to deploy and operate your scraper in the cloud. Style and approach This book is a rich collection of recipes that will come in handy when you are scraping a website using Python. Addressing your common and not-so-common pain points while scraping website, this is a book that you must have on the shelf.

Design and administer enterprise-grade MySQL 8 solutions About This Book ? Store, retrieve, and manipulate your data using the latest MySQL 8 features ? Practical recipes on effective administration in MySQL, with a focus on security, performance tuning, troubleshooting, and more ? Contains tips, tricks, and best practices for designing, developing, and administering your MySQL 8 database solution without any hassle Who This Book Is For If you are a MySQL developer or administrator looking for quick, handy solutions to solve the most common and not-so-common problems in MySQL, this book is for you. MySQL DBAs looking to get up-to-speed with the latest MySQL 8 development and administration features will also find this book very useful. Prior knowledge of Linux and RDBMS is desirable. What You Will Learn ? Install and configure your MySQL 8 instance without any hassle ? Get to grips with new features of MySQL 8 like CTE, Window functions and many more ? Perform backup tasks, recover data and set up various replication topologies for your database ? Maximize performance by using new features of MySQL 8 like descending indexes, controlling query optimizer and resource groups ? Learn how to use general table space to suit the SaaS or multi-tenant applications ? Analyze slow queries using performance schema, sys schema and third party tools ? Manage and monitor your MySQL instance and implement efficient performance-tuning tasks In Detail MySQL is one of the most popular and widely used relational databases in the World today. The recently released MySQL 8 version promises to be better and more efficient than ever before. This book contains everything you need to know to be the go-to person in your organization when it comes to MySQL. Starting with a quick installation and configuration of your MySQL instance, the book quickly jumps into the querying aspects of MySQL. It shows you the newest improvements in MySQL 8 and gives you hands-on experience in managing high-transaction and real-time datasets. If you've already worked with MySQL before and are looking to migrate your application to MySQL 8, this book will also show you how to do that. The book also contains recipes on efficient MySQL administration, with tips on effective user management, data recovery, security, database monitoring, performance tuning, troubleshooting, and more. With quick solutions to common and not-so-common problems you might encounter while working with MySQL 8, the book contains practical tips and tricks to give you the edge over others in designing, developing, and administering your database effectively. Style and approach This book takes a recipe-based approach to tackling the pain points of SQL developers. It is a comprehensive book full of solutions to common problems faced by SQL administrators and developers alike.

Get more control of your applications performances in development and production and know how to meet your Service Level Agreement on critical microservices. About This Book ? Learn how to write a JavaEE application with performance constraints (Service Level Agreement—SLA) leveraging the platform ? Learn how to identify bottlenecks and hotspots in your application to fix them ? Ensure that you are able to continuously control your performance in production and during development Who This Book Is For If you're a Java developer looking to improve the performance of your code or simply wanting to take your skills up to the next level, then this book is perfect for you. What You Will Learn ? Identify performance bottlenecks in an application ? Locate application hotspots using performance tools ? Understand the work done under the hood by EE containers and its impact on performance ? Identify common patterns to integrate with Java EE applications ? Implement transparent caching on your applications ? Extract more information from your applications using Java EE without modifying existing code ? Ensure constant performance and eliminate regression In Detail The ease with which we write applications has been increasing, but with this comes the need to address their performance. A balancing act between easily implementing complex applications and keeping their performance optimal is a present-day need. In this book, we explore how to achieve this crucial balance while developing and deploying applications with Java EE 8. The book starts by analyzing various Java EE specifications to identify those potentially affecting performance adversely. Then, we move on to monitoring techniques that enable us to identify performance bottlenecks and optimize performance metrics. Next, we look at techniques that help us achieve high performance: memory optimization, concurrency, multi-threading, scaling, and caching. We also look at fault tolerance solutions and the importance of logging. Lastly, you will learn to benchmark your application and also implement solutions for continuous performance evaluation. By the end of the book, you will have gained insights into various techniques and solutions that will help create high-performance applications in the Java EE 8 environment. Style and approach This book will cover vital concepts implemented through a sample application built throughout the book. This will enable you to apply these concepts to suit your software requirements.

Powerful smart applications using deep learning algorithms to dominate numerical computing, deep learning, and functional programming. About This Book ? Explore machine learning techniques with prominent open source Scala libraries such as Spark ML, H2O, MXNet, Zeppelin, and DeepLearning4j ? Solve real-world machine learning problems by delving complex numerical computing with Scala functional programming in a scalable and faster way ? Cover all key aspects such as collection, storing, processing, analyzing, and evaluation required to build and deploy machine models on computing clusters using Scala Play framework. Who This Book Is For If you want to leverage the power of both Scala and Spark to make sense of Big Data, then this book is for you. If you are well versed with machine learning concepts and wants to expand your knowledge by delving into the practical implementation using the power of Scala, then this book is what you need! Strong understanding of Scala Programming language is recommended. Basic familiarity with machine Learning techniques will be more helpful. What You Will Learn ? Apply advanced regression techniques to boost the performance of predictive models ? Use different classification algorithms for business analytics ? Generate trading strategies for Bitcoin and stock trading using ensemble techniques ? Train Deep Neural Networks (DNN) using H2O and Spark ML ? Utilize NLP to build scalable machine learning models ? Learn how to apply reinforcement learning algorithms such as Q-learning for developing ML application ? Learn how to use autoencoders to develop a fraud detection application ? Implement LSTM and CNN models using DeepLearning4j and MXNet In Detail Machine learning has had a huge impact on academia and industry by turning data into actionable information. Scala has seen a steady rise in adoption over the past few years, especially in the fields of data science and analytics. This book is for data scientists, data engineers, and deep learning enthusiasts who have a background in complex numerical computing and want to know more hands-on machine learning application development. If you're well versed in machine learning concepts and want to expand your knowledge by delving into the practical implementation of these concepts using the power of Scala, then this book is what you need! Through 11 end-to-end projects, you will be acquainted with popular machine learning libraries such as Spark ML, H2O, DeepLearning4j, and MXNet. At the end, you will be able to use numerical computing and functional programming to carry out complex numerical tasks to develop, build, and deploy research or commercial projects in a production-ready environment. Style and approach Leverage the power of machine learning and deep learning in different domains, giving best practices and tips from a real world case studies and help you to avoid pitfalls and fallacies towards decision making based on predictive analytics with ML models.

Build, scale, and deploy deep neural network models using the star libraries in Python About This Book ? Delve into advanced machine learning and deep learning use cases using Tensorflow and Keras ? Build, deploy, and scale end-to-end deep neural network models in a production environment ? Learn to deploy TensorFlow on mobile, and distributed TensorFlow on GPU, Clusters, and Kubernetes Who This Book Is For This book is for data scientists, machine learning engineers, artificial intelligence engineers, and for all TensorFlow users who wish to upgrade their TensorFlow knowledge and work on various machine learning and deep learning problems. If you are looking for an easy-to-follow guide that underlines the intricacies and complex use cases of machine learning, you will find this book extremely useful. Some basic understanding of TensorFlow is required to get the most out of the book. What You Will Learn ? Master advanced concepts of deep learning such as transfer learning, reinforcement learning, generative models and more, using TensorFlow and Keras ? Perform supervised (classification and regression) and unsupervised (clustering) learning to solve machine learning tasks ? Build end-to-end deep learning (CNN, RNN, and Autoencoders) models with TensorFlow ? Scale and deploy production models with distributed and high-performance computing on GPU and clusters ? Build TensorFlow models to work with multilayer perceptrons using Keras, TFLearn, and R ? Learn the functionalities of smart apps by building and deploying TensorFlow models on iOS and Android devices ? Supercharge TensorFlow with distributed training and deployment on Kubernetes and TensorFlow Clusters In Detail TensorFlow is the most popular numerical computation library built from the ground up for distributed, cloud, and mobile environments. TensorFlow represents the data as tensors and the computation as graphs. This book is a comprehensive guide that lets you explore the advanced features of TensorFlow 1.x. Gain insight into TensorFlow Core, Keras, TF Estimators, TFLearn, TF Slim, Pretty Tensor, and Sonnet. Leverage the power of TensorFlow and Keras to build deep learning models, using concepts such as transfer learning, generative adversarial networks, and deep reinforcement learning. Throughout the book, you will obtain hands-on experience with varied datasets, such as MNIST, CIFAR-10, PTB, text8, and COCO-Images. You will learn the advanced features of TensorFlow1.x, such as distributed TensorFlow with TF Clusters, deploy production models with TensorFlow Serving, and build and deploy TensorFlow models for mobile and embedded devices on Android and iOS platforms. You will see how to call TensorFlow and Keras API within the R statistical software, and learn the required techniques for debugging when the TensorFlow API-based code does not work as expected. The book helps you obtain in-depth knowledge of TensorFlow, making you the go-to person for solving artificial intelligence problems. By the end of this guide, you will have mastered the offerings of TensorFlow and Keras, and gained the skills you need to build smarter, faster, and efficient machine learning and deep learning systems. Style and approach Step-by-step comprehensive guide filled with advanced, real-world examples to help you master Tensorflow 1.x

Learn how to model and train advanced neural networks to implement a variety of Computer Vision tasks About This Book ? Train different kinds of deep learning model from scratch to solve specific problems in Computer Vision ? Combine the power of Python, Keras, and TensorFlow to build deep learning models for object detection, image classification, similarity learning, image captioning, and more ? Includes tips on optimizing and improving the performance of your models under various constraints Who This Book Is For This book is targeted at data scientists and Computer Vision practitioners who wish to apply the concepts of Deep Learning to overcome any problem related to Computer Vision. A basic knowledge of programming in Python—and some understanding of machine learning concepts—is required to get the best out of this book. What You Will Learn ? Set up an environment for deep learning with Python, TensorFlow, and Keras ? Define and train a model for image and video classification ? Use features from a pre-trained Convolutional Neural Network model for image retrieval ? Understand and implement object detection using the real-world Pedestrian Detection scenario ? Learn about various problems in image captioning and how to overcome them by training images and text together ? Implement similarity matching and train a model for face recognition ? Understand the concept of generative models and use them for image generation ? Deploy your deep learning models and optimize them for high performance In Detail Deep learning has shown its power in several application areas of Artificial Intelligence, especially in Computer Vision. Computer Vision is the science of understanding and manipulating images, and finds enormous applications in the areas of robotics, automation, and so on. This book will also show you, with practical examples, how to develop Computer Vision applications by leveraging the power of deep learning. In this book, you will learn different techniques related to object classification, object detection, image segmentation, captioning, image generation, face analysis, and more. You will also explore their applications using popular Python libraries such as TensorFlow and Keras. This book will help you master state-of-the-art, deep learning algorithms and their implementation. Style and approach This book will teach advanced techniques for Computer Vision, applying the deep learning model in reference to various datasets.

Build your defense against web attacks with Kali Linux, including command injection flaws, crypto implementation layers, and web application security holes About This Book ? Know how to set up your lab with Kali Linux ? Discover the core concepts of web penetration testing ? Get the tools and techniques you need with Kali Linux Who This Book Is For Since this book sets out to cover a large number of tools and security fields, it can work as an introduction to practical security skills for beginners in security. In addition, web programmers and also system administrators would benefit from this rigorous introduction to web penetration testing. Basic system administration skills are necessary, and the ability to read code is a must. What You Will Learn ? Learn how to set up your lab with Kali Linux ? Understand the core concepts of web penetration testing ? Get to know the tools and techniques you need to use with Kali Linux ? Identify the difference between hacking a web application and network hacking ? Expose vulnerabilities present in web servers and their applications using server-side attacks ? Understand the different techniques used to identify the flavor of web applications ? See standard attacks such as exploiting cross-site request forgery and cross-site *ing flaws ? Get an overview of the art of client-side attacks ? Explore automated attacks such as fuzzing web applications In Detail Web Penetration Testing with Kali Linux - Third Edition shows you how to set up a lab, helps you understand the nature and mechanics of attacking websites, and explains classical attacks in great depth. This edition is heavily updated for the latest Kali Linux changes and the most recent attacks. Kali Linux shines when it comes to client-side attacks and fuzzing in particular. From the start of the book, you'll be given a thorough grounding in the concepts of hacking and penetration testing, and you'll see the tools used in Kali Linux that relate to web application hacking. You'll gain a deep understanding of classicalSQL, command-injection flaws, and the many ways to exploit these flaws. Web penetration testing also needs a general overview of client-side attacks, which is rounded out by a long discussion of *ing and input validation flaws. There is also an important chapter on cryptographic implementation flaws, where we discuss the most recent problems with cryptographic layers in the networking stack. The importance of these attacks cannot be overstated, and defending against them is relevant to most internet users and, of course, penetration testers. At the end of the book, you'll use an automated technique called fuzzing to identify flaws in a web application. Finally, you'll gain an understanding of web application vulnerabilities and the ways they can be exploited using the tools in Kali Linux. Style and approach This step-by-step guide covers each topic with detailed practical examples. Every concept is explained with the help of illustrations using the tools available in Kali Linux.

Build smart, efficient, and fast enterprise-grade web implementation of the microservices architecture that can be easily scaled. About This Book ? Write easy-to-maintain lean and clean code with Kotlin for developing better microservices ? Scale your Microserivces in your own cloud with Docker and Docker Swarm ? Explore Spring 5 functional reactive web programming with Spring WebFlux Who This Book Is For If you are a Kotlin developer with a basic knowledge of microservice architectures and now want to effectively implement these services on enterprise-level web applications, then this book is for you What You Will Learn ? Understand microservice architectures and principles ? Build microservices in Kotlin using Spring Boot 2.0 and Spring Framework 5.0 ? Create reactive microservices that perform non-blocking operations with Spring WebFlux ? Use Spring Data to get data reactively from MongoDB ? Test effectively with JUnit and Kotlin ? Create cloud-native microservices with Spring Cloud ? Build and publish Docker images of your microservices ? Scaling microservices with Docker Swarm ? Monitor microservices with JMX ? Deploy microservices in OpenShift Online In Detail With Google's inclusion of first-class support for Kotlin in their Android ecosystem, Kotlin's future as a mainstream language is assured. Microservices help design scalable, easy-to-maintain web applications; Kotlin allows us to take advantage of modern idioms to simplify our development and create high-quality services. With 100% interoperability with the JVM, Kotlin makes working with existing Java code easier. Well-known Java systems such as Spring, Jackson, and Reactor have included Kotlin modules to exploit its language features. This book guides the reader in designing and implementing services, and producing production-ready, testable, lean code that's shorter and simpler than a traditional Java implementation. Reap the benefits of using the reactive paradigm and take advantage of non-blocking techniques to take your services to the next level in terms of industry standards. You will consume NoSQL databases reactively to allow you to create high-throughput microservices. Create cloud-native microservices that can run on a wide range of cloud providers, and monitor them. You will create Docker containers for your microservices and scale them. Finally, you will deploy your microservices in OpenShift Online. Style and approach This book guides the reader in designing and implementing services, achieving production- ready, testable, easy-to-maintain, lean code that's shorter and simpler than a traditional Java implementation.

Write code that scales across CPU registers, multi-core, and machine clusters About This Book ? Explore concurrent programming in C++ ? Identify memory management problems ? Use SIMD and STL containers for performance improvement Who This Book Is For If you're a C++ developer looking to improve the speed of your code or simply wanting to take your skills up to the next level, then this book is perfect for you. What You Will Learn ? Find out how to use exciting new tools that will help you improve your code ? Identify bottlenecks to optimize your code ? Develop applications that utilize GPU computation ? Reap the benefits of concurrent programming ? Write code that can protect against application errors using error handling ? Use STL containers and algorithms effciently ? Extend your toolbox with Boost containers ? Achieve effcient memory management by using custom memory allocators In Detail C++ is a highly portable language and can be used to write complex applications and performance-critical code. It has evolved over the last few years to become a modern and expressive language. This book will guide you through optimizing the performance of your C++ apps by allowing them to run faster and consume fewer resources on the device they're running on. The book begins by helping you to identify the bottlenecks in C++. It then moves on to measuring performance, and you'll see how this affects the way you write code. Next, you'll see the importance of data structure optimization and how it can be used efficiently. After that, you'll see which algorithm should be used to achieve faster execution, followed by how to use STL containers. Moving on, you'll learn how to improve memory management in C++. You'll get hands on experience making use of multiple cores to enable more efficient and faster execution. The book ends with a brief overview of utilizing the capabilities of your GPU by using Boost Compute and OpenCL. Style and approach This easy-to-follow guide is full of examples and self-sufficient code snippets that help you with high performance programming with C++. You’ll get your hands dirty with this all-inclusive guide that uncovers hidden performance improvement areas for any C++ code.

Design, build and test RESTful web services with the Django framework and Python About This Book ? Create efficient real-world RESTful web services with the latest Django framework ? Authenticate, secure, and integrate third-party packages efficiently in your Web Services ? Leverage the power of Python for faster Web Service development Who This Book Is For This book is for Python developers who want to create RESTful web services with Django; you need to have a basic working knowledge of Django but no previous experience with RESTful web services is required. What You Will Learn ? The best way to build a RESTful Web Service or API with Django and the Django REST Framework ? Develop complex RESTful APIs from scratch with Django and the Django REST Framework ? Work with either SQL or NoSQL data sources ? Design RESTful Web Services based on application requirements ? Use third-party packages and extensions to perform common tasks ? Create automated tests for RESTful web services ? Debug, test, and profile RESTful web services with Django and the Django REST Framework In Detail Django is a Python web framework that makes the web development process very easy. It reduces the amount of trivial code, which simplifies the creation of web applications and results in faster development. It is very powerful and a great choice for creating RESTful web services. If you are a Python developer and want to efficiently create RESTful web services with Django for your apps, then this is the right book for you. The book starts off by showing you how to install and configure the environment, required software, and tools to create RESTful web services with Django and the Django REST framework. We then move on to working with advanced serialization and migrations to interact with SQLite and non-SQL data sources. We will use the features included in the Django REST framework to improve our simple web service. Further, we will create API views to process diverse HTTP requests on objects, go through relationships and hyperlinked API management, and then discover the necessary steps to include security and permissions related to data models and APIs. We will also apply throttling rules and run tests to check that versioning works as expected. Next we will run automated tests to improve code coverage. By the end of the book, you will be able to build RESTful web services with Django." Style and approach The book takes a straightforward approach, giving you the techniques and best use cases to build great web services with Django and Python

One stop guide to implementing award-winning, and cutting-edge CNN architectures About This Book ? Fast-paced guide with use cases and real-world examples to get well versed with CNN techniques ? Implement CNN models on image classification, transfer learning, Object Detection, Instance Segmentation, GANs and more ? Implement powerful use-cases like image captioning, reinforcement learning for hard attention, and recurrent attention models Who This Book Is For This book is for data scientists, machine learning and deep learning practitioners, Cognitive and Artificial Intelligence enthusiasts who want to move one step further in building Convolutional Neural Networks. Get hands-on experience with extreme datasets and different CNN architectures to build efficient and smart ConvNet models. Basic knowledge of deep learning concepts and Python programming language is expected. What You Will Learn ? From CNN basic building blocks to advanced concepts understand practical areas they can be applied to ? Build an image classifier CNN model to understand how different components interact with each other, and then learn how to optimize it ? Learn different algorithms that can be applied to Object Detection, and Instance Segmentation ? Learn advanced concepts like attention mechanisms for CNN to improve prediction accuracy ? Understand transfer learning and implement award-winning CNN architectures like AlexNet, VGG, GoogLeNet, ResNet and more ? Understand the working of generative adversarial networks and how it can create new, unseen images In Detail Convolutional Neural Network (CNN) is revolutionizing several application domains such as visual recognition systems, self-driving cars, medical discoveries, innovative eCommerce and more.You will learn to create innovative solutions around image and video analytics to solve complex machine learning and computer vision related problems and implement real-life CNN models. This book starts with an overview of deep neural networkswith the example of image classification and walks you through building your first CNN for human face detector. We will learn to use concepts like transfer learning with CNN, and Auto-Encoders to build very powerful models, even when not much of supervised training data of labeled images is available. Later we build upon the learning achieved to build advanced vision related algorithms for object detection, instance segmentation, generative adversarial networks, image captioning, attention mechanisms for vision, and recurrent models for vision. By the end of this book, you should be ready to implement advanced, effective and efficient CNN models at your professional project or personal initiatives by working on complex image and video datasets. Style and approach An easy to follow concise and illustrative guide explaining the core concepts of ConvNets to help you understand, implement and deploy your CNN models quickly.

Your one step guide to learn all about AWS networking. About This Book ? Master your networking skills on Public Cloud. ? Gain hands-on experience of using Amazon VPC, Elastic Load Balancing, Direct Connect and other AWS products. ? Implement troubleshooting skills and best practices for security on AWS network. Who This Book Is For This book is targeted towards cloud architects, cloud solution providers, or any stakeholders dealing with networking on AWS Cloud. A prior idea of Amazon Web Services will be an added advantage. What You Will Learn ? Overview of all networking services available in AWS. ? Gain Work with load balance application across different regions. ? Learn auto scale instance based on the increase and decrease of the traffic. ? Deploy application in highly available and fault tolerant manner. ? Configure Route 53 for a web application. ? Troubleshooting tips and best practices at the end In Detail Amazon Web Services (AWS) dominates the public cloud market by a huge margin and it continues to be the first choice for many organizations. Networking has been an area of focus for all the leading cloud service providers. AWS has a suite of network-related products that help to perform network-related task in AWS. This book initially covers the basics of networking in AWS. Then we use AWS VPC to create an isolated virtual cloud for performing network-related tasks. We then provide an overview of AWS Direct Connect after taking a deep dive into scalability and load balancing using Auto scaling feature, Elastic Load Balancing, and Amazon Route S3. Toward the end of the book, we cover some troubleshooting tips and security best practices for your network. By the end of this book, you will have hands-on experience of working with network tasks on AWS. Style and approach A step by step practical guide that helps you use all networking services available in AWS effectively.

A comprehensive guide to mastering the art of preventing your Linux system from getting compromised. About This Book ? Leverage this guide to confidently deliver a system that reduces the risk of being hacked ? Perform a number of advanced Linux security techniques such as network service detection, user authentication, controlling special permissions, encrypting file systems, and much more ? Master the art of securing a Linux environment with this end-to-end practical guide Who This Book Is For If you are a systems administrator or a network engineer interested in making your Linux environment more secure, then this book is for you. Security consultants wanting to enhance their Linux security skills will also benefit from this book. Prior knowledge of Linux is mandatory. What You Will Learn ? Use various techniques to prevent intruders from accessing sensitive data ? Prevent intruders from planting malware, and detect whether malware has been planted ? Prevent insiders from accessing data that they aren’t authorized to access ? Do quick checks to see whether a computer is running network services that it doesn’t need to run ? Learn security techniques that are common to all Linux distros, and some that are distro-specific In Detail This book has extensive coverage of techniques that will help prevent attackers from breaching your system, by building a much more secure Linux environment. You will learn various security techniques such as SSH hardening, network service detection, setting up firewalls, encrypting file systems, protecting user accounts, authentication processes, and so on. Moving forward, you will also develop hands-on skills with advanced Linux permissions, access control, special modes, and more. Lastly, this book will also cover best practices and troubleshooting techniques to get your work done efficiently. By the end of this book, you will be confident in delivering a system that will be much harder to compromise. Style and approach An advanced-level guide filled with real-world examples that will help you secure your Linux system

A perfect guide to speed up the predicting power of machine learning algorithms About This Book ? Design, discover, and create dynamic, efficient features for your machine learning application ? Understand your data in-depth and derive astonishing data insights with the help of this Guide ? Grasp powerful feature-engineering techniques and build machine learning systems Who This Book Is For If you are a data science professional or a machine learning engineer looking to strengthen your predictive analytics model, then this book is a perfect guide for you. Some basic understanding of the machine learning concepts and Python *ing would be enough to get started with this book. What You Will Learn ? Identify and leverage different feature types ? Clean features in data to improve predictive power ? Understand why and how to perform feature selection, and model error analysis ? Leverage domain knowledge to construct new features ? Deliver features based on mathematical insights ? Use machine-learning algorithms to construct features ? Master feature engineering and optimization ? Harness feature engineering for real world applications through a structured case study In Detail Feature engineering is the most important step in creating powerful machine learning systems. This book will take you through the entire feature-engineering journey to make your machine learning much more systematic and effective. You will start with understanding your data—often the success of your ML models depends on how you leverage different feature types, such as continuous, categorical, and more, You will learn when to include a feature, when to omit it, and why, all by understanding error analysis and the acceptability of your models. You will learn to convert a problem statement into useful new features. You will learn to deliver features driven by business needs as well as mathematical insights. You'll also learn how to use machine learning on your machines, automatically learning amazing features for your data. By the end of the book, you will become proficient in Feature Selection, Feature Learning, and Feature Optimization. Style and approach This step-by-step guide with use cases, examples, and illustrations will help you master the concepts of feature engineering. Along with explaining the fundamentals, the book will also introduce you to slightly advanced concepts later on and will help you implement these techniques in the real world.

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