Learn a modern approach to data analysis using Python to harness the power of programming and AI across your data. Detailed case studies bring this modern approach to life across visual data, social media, graph algorithms, and time series analysis. Key Features *Bridge your data analysis with the power of programming, complex algorithms, and AI *Use Python and its extensive libraries to power your way to new levels of data insight *Work with AI algorithms, TensorFlow, graph algorithms, NLP, and financial time series *Explore this modern approach across with key industry case studies and hands-on projects Book Description 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. What you will learn *A new toolset that has been carefully crafted to meet for your data analysis challenges *Full and detailed case studies of the toolset across several of today’s key industry contexts *Become super productive with a new toolset across Python and Jupyter Notebook *Look into the future of data science and which directions to develop your skills next Who this book is for This book is for developers wanting to bridge the gap between them and data scientists. Introducing PixieDust from its creator, the book is a great desk companion for the accomplished Data Scientist. Some fluency in data interpretation and visualization is assumed. It will be helpful to have some knowledge of Python, using Python libraries, and some proficiency in web development.

Explore a diverse set of meta-learning algorithms and techniques to enable human-like cognition for your machine learning models using various Python frameworks Key Features *Understand the foundations of meta learning algorithms *Explore practical examples to explore various one-shot learning algorithms with its applications in TensorFlow *Master state of the art meta learning algorithms like MAML, reptile, meta SGD Book Description Meta learning is an exciting research trend in machine learning, which enables a model to understand the learning process. Unlike other ML paradigms, with meta learning you can learn from small datasets faster. Hands-On Meta Learning with Python starts by explaining the fundamentals of meta learning and helps you understand the concept of learning to learn. You will delve into various one-shot learning algorithms, like siamese, prototypical, relation and memory-augmented networks by implementing them in TensorFlow and Keras. As you make your way through the book, you will dive into state-of-the-art meta learning algorithms such as MAML, Reptile, and CAML. You will then explore how to learn quickly with Meta-SGD and discover how you can perform unsupervised learning using meta learning with CACTUs. In the concluding chapters, you will work through recent trends in meta learning such as adversarial meta learning, task agnostic meta learning, and meta imitation learning. By the end of this book, you will be familiar with state-of-the-art meta learning algorithms and able to enable human-like cognition for your machine learning models. What you will learn *Understand the basics of meta learning methods, algorithms, and types *Build voice and face recognition models using a siamese network *Learn the prototypical network along with its variants *Build relation networks and matching networks from scratch *Implement MAML and Reptile algorithms from scratch in Python *Work through imitation learning and adversarial meta learning *Explore task agnostic meta learning and deep meta learning Who this book is for Hands-On Meta Learning with Python is for machine learning enthusiasts, AI researchers, and data scientists who want to explore meta learning as an advanced approach for training machine learning models. Working knowledge of machine learning concepts and Python programming is necessary.

Speed up the design and implementation of deep learning solutions using Apache Spark Key Features * Explore the world of distributed deep learning with Apache Spark * Train neural networks with deep learning libraries such as BigDL and TensorFlow * Develop Spark deep learning applications to intelligently handle large and complex datasets Book Description Deep learning is a subset of machine learning where datasets with several layers of complexity can be processed. Hands-On Deep Learning with Apache Spark addresses the sheer complexity of technical and analytical parts and the speed at which deep learning solutions can be implemented on Apache Spark. The book starts with the fundamentals of Apache Spark and deep learning. You will set up Spark for deep learning, learn principles of distributed modeling, and understand different types of neural nets. You will then implement deep learning models, such as convolutional neural networks (CNNs), recurrent neural networks (RNNs), and long short-term memory (LSTM) on Spark. As you progress through the book, you will gain hands-on experience of what it takes to understand the complex datasets you are dealing with. During the course of this book, you will use popular deep learning frameworks, such as TensorFlow, Deeplearning4j, and Keras to train your distributed models. By the end of this book, you'll have gained experience with the implementation of your models on a variety of use cases. What you will learn * Understand the basics of deep learning * Set up Apache Spark for deep learning * Understand the principles of distribution modeling and different types of neural networks * Obtain an understanding of deep learning algorithms * Discover textual analysis and deep learning with Spark * Use popular deep learning frameworks, such as Deeplearning4j, TensorFlow, and Keras * Explore popular deep learning algorithms Who this book is for If you are a Scala developer, data scientist, or data analyst who wants to learn how to use Spark for implementing efficient deep learning models, Hands-On Deep Learning with Apache Spark is for you. Knowledge of the core machine learning concepts and some exposure to Spark will be helpful.

Implement defensive techniques in your ecosystem successfully with Python Key Features * Identify and expose vulnerabilities in your infrastructure with Python * Learn custom exploit development . * Make robust and powerful cybersecurity tools with Python Book Description With the current technological and infrastructural shift, penetration testing is no longer a process-oriented activity. Modern-day penetration testing demands lots of automation and innovation; the only language that dominates all its peers is Python. Given the huge number of tools written in Python, and its popularity in the penetration testing space, this language has always been the first choice for penetration testers. Hands-On Penetration Testing with Python walks you through advanced Python programming constructs. Once you are familiar with the core concepts, you’ll explore the advanced uses of Python in the domain of penetration testing and optimization. You’ll then move on to understanding how Python, data science, and the cybersecurity ecosystem communicate with one another. In the concluding chapters, you’ll study exploit development, reverse engineering, and cybersecurity use cases that can be automated with Python. By the end of this book, you’ll have acquired adequate skills to leverage Python as a helpful tool to pentest and secure infrastructure, while also creating your own custom exploits. What you will learn * Get to grips with Custom vulnerability scanner development * Familiarize yourself with web application scanning automation and exploit development * Walk through day-to-day cybersecurity scenarios that can be automated with Python * Discover enterprise-or organization-specific use cases and threat-hunting automation * Understand reverse engineering, fuzzing, buffer overflows , key-logger development, and exploit development for buffer overflows. * Understand web scraping in Python and use it for processing web responses * Explore Security Operations Centre (SOC) use cases * Get to understand Data Science, Python, and cybersecurity all under one hood Who this book is for If you are a security consultant , developer or a cyber security enthusiast with little or no knowledge of Python and want in-depth insight into how the pen-testing ecosystem and python combine to create offensive tools , exploits , automate cyber security use-cases and much more then this book is for you. Hands-On Penetration Testing with Python guides you through the advanced uses of Python for cybersecurity and pen-testing, helping you to better understand security loopholes within your infrastructure .

Understand how to apply distributed tracing to microservices-based architectures Key Features * A thorough conceptual introduction to distributed tracing * An exploration of the most important open standards in the space * A how-to guide for code instrumentation and operating a tracing infrastructure Book Description Mastering Distributed Tracing will equip you to operate and enhance your own tracing infrastructure. Through practical exercises and code examples, you will learn how end-to-end tracing can be used as a powerful application performance management and comprehension tool. The rise of Internet-scale companies, like Google and Amazon, ushered in a new era of distributed systems operating on thousands of nodes across multiple data centers. Microservices increased that complexity, often exponentially. It is harder to debug these systems, track down failures, detect bottlenecks, or even simply understand what is going on. Distributed tracing focuses on solving these problems for complex distributed systems. Today, tracing standards have developed and we have much faster systems, making instrumentation less intrusive and data more valuable. Yuri Shkuro, the creator of Jaeger, a popular open-source distributed tracing system, delivers end-to-end coverage of the field in Mastering Distributed Tracing. Review the history and theoretical foundations of tracing; solve the data gathering problem through code instrumentation, with open standards like OpenTracing, W3C Trace Context, and OpenCensus; and discuss the benefits and applications of a distributed tracing infrastructure for understanding, and profiling, complex systems. What you will learn * How to get started with using a distributed tracing system * How to get the most value out of end-to-end tracing * Learn about open standards in the space * Learn about code instrumentation and operating a tracing infrastructure * Learn where distributed tracing fits into microservices as a core function Who this book is for Any developer interested in testing large systems will find this book very revealing and in places, surprising. Every microservice architect and developer should have an insight into distributed tracing, and the book will help them on their way. System administrators with some development skills will also benefit. No particular programming language skills are required, although an ability to read Java, while non-essential, will help with the core chapters.

A comprehensive guide to mastering the most advanced Hadoop 3 concepts Key Features * Get to grips with the newly introduced features and capabilities of Hadoop 3 * Crunch and process data using MapReduce, YARN, and a host of tools within the Hadoop ecosystem * Sharpen your Hadoop skills with real-world case studies and code Book Description Apache Hadoop is one of the most popular big data solutions for distributed storage and for processing large chunks of data. With Hadoop 3, Apache promises to provide a high-performance, more fault-tolerant, and highly efficient big data processing platform, with a focus on improved scalability and increased efficiency. With this guide, you’ll understand advanced concepts of the Hadoop ecosystem tool. You’ll learn how Hadoop works internally, study advanced concepts of different ecosystem tools, discover solutions to real-world use cases, and understand how to secure your cluster. It will then walk you through HDFS, YARN, MapReduce, and Hadoop 3 concepts. You’ll be able to address common challenges like using Kafka efficiently, designing low latency, reliable message delivery Kafka systems, and handling high data volumes. As you advance, you’ll discover how to address major challenges when building an enterprise-grade messaging system, and how to use different stream processing systems along with Kafka to fulfil your enterprise goals. By the end of this book, you’ll have a complete understanding of how components in the Hadoop ecosystem are effectively integrated to implement a fast and reliable data pipeline, and you’ll be equipped to tackle a range of real-world problems in data pipelines. What you will learn * Gain an in-depth understanding of distributed computing using Hadoop 3 * Develop enterprise-grade applications using Apache Spark, Flink, and more * Build scalable and high-performance Hadoop data pipelines with security, monitoring, and data governance * Explore batch data processing patterns and how to model data in Hadoop * Master best practices for enterprises using, or planning to use, Hadoop 3 as a data platform * Understand security aspects of Hadoop, including authorization and authentication Who this book is for If you want to become a big data professional by mastering the advanced concepts of Hadoop, this book is for you. You’ll also find this book useful if you’re a Hadoop professional looking to strengthen your knowledge of the Hadoop ecosystem. Fundamental knowledge of the Java programming language and basics of Hadoop is necessary to get started with this book.

A comprehensive guide packed with the latest features of Dynamics 365 for customer relationship management Key Features * Create efficient client-side apps and customized plugins that work seamlessly * Learn best practices from field experience to use Dynamics 365 efficiently * Unleash the power of Dynamics 365 to maximize your organization’s profits Book Description Microsoft Dynamics 365 is an all-in-one business management solution that's easy to use and adapt. It helps you connect your finances, sales, service, and operations to streamline business processes, improve customer interactions, and enable growth. This book gives you all the information you need to become an expert in MS Dynamics 365. This book starts with a brief overview of the functional features of Dynamics 365. You will learn how to create Word and Excel templates using CRM data to enable customized data analysis for your organization. This book helps you understand how to use Dynamics 365 as an XRM Framework, gain a deep understanding of client-side scripting in Dynamics 365, and create client-side applications using JavaScript and the Web API. In addition to this, you will discover how to customize Dynamics 365, and quickly move on to grasp the app structure, which helps you customize Dynamics 365 better. You will also learn how Dynamics 365 can be seamlessly embedded into various productivity tools to customize them for machine learning and contextual guidance. By the end of this book, you will have mastered utilizing Dynamics 365 features through real-world scenarios. What you will learn * Manage various divisions of your organization using Dynamics 365 customizations * Explore the XRM Framework and leverage its features * Provide an enhanced mobile and tablet experience * Develop client-side applications using JavaScript and the Web API * Understand how to develop plugins and workflows using Dynamics 365 * Explore solution framework improvements and new field types Who this book is for Mastering Microsoft Dynamics 365 Customer Engagement is for you if you have knowledge of Dynamics CRM and want to utilize the latest features of Dynamics 365. This book is also for you if you’re a skilled developer looking to move to the Microsoft stack to build business solution software. Extensive Dynamics CRM development experience will be beneficial to understand the concepts covered in this book.

Plug the gaps in your network’s infrastructure with resilient network security models Key Features * Develop a cost-effective and end-to-end vulnerability management program * Explore best practices for vulnerability scanning and risk assessment * Understand and implement network enumeration with Nessus and Network Mapper (Nmap) Book Description Digitization drives technology today, which is why it’s so important for organizations to design security mechanisms for their network infrastructures. Analyzing vulnerabilities is one of the best ways to secure your network infrastructure. This Learning Path begins by introducing you to the various concepts of network security assessment, workflows, and architectures. You will learn to employ open source tools to perform both active and passive network scanning and use these results to analyze and design a threat model for network security. With a firm understanding of the basics, you will then explore how to use Nessus and Nmap to scan your network for vulnerabilities and open ports and gain back door entry into a network. As you progress through the chapters, you will gain insights into how to carry out various key scanning tasks, including firewall detection, OS detection, and access management to detect vulnerabilities in your network. By the end of this Learning Path, you will be familiar with the tools you need for network scanning and techniques for vulnerability scanning and network protection. This Learning Path includes content from the following Packt books: * Network Scanning Cookbook by Sairam Jetty * Network Vulnerability Assessment by Sagar Rahalkar What you will learn * Explore various standards and frameworks for vulnerability assessments and penetration testing * Gain insight into vulnerability scoring and reporting * Discover the importance of patching and security hardening * Develop metrics to measure the success of a vulnerability management program * Perform configuration audits for various platforms using Nessus * Write custom Nessus and Nmap scripts on your own * Install and configure Nmap and Nessus in your network infrastructure * Perform host discovery to identify network devices Who this book is for This Learning Path is designed for security analysts, threat analysts, and security professionals responsible for developing a network threat model for an organization. Professionals who want to be part of a vulnerability management team and implement an end-to-end robust vulnerability management program will also find this Learning Path useful.

Create a real-world application in Go and explore various frameworks and methodologies for full-stack development Key Features * Organize your isomorphic codebase to enhance the maintainability of your application * Build web APIs and middleware in the Go language by making use of the popular Gin framework * Implement real-time web application functionality with WebSockets Book Description The Go programming language has been rapidly adopted by developers for building web applications. With its impressive performance and ease of development, Go enjoys the support of a wide variety of open source frameworks, for building scalable and high-performant web services and apps. Hands-On Full Stack Development with Go is a comprehensive guide that covers all aspects of full stack development with Go. This clearly written, example-rich book begins with a practical exposure to Go development and moves on to build a frontend with the popular React framework. From there, you will build RESTful web APIs utilizing the Gin framework. After that, we will dive deeper into important software backend concepts, such as connecting to the database via an ORM, designing routes for your services, securing your services, and even charging credit cards via the popular Stripe API. We will also cover how to test, and benchmark your applications efficiently in a production environment. In the concluding chapters, we will cover isomorphic developments in pure Go by learning about GopherJS. As you progress through the book, you'll gradually build a musical instrument online store application from scratch. By the end of the book, you will be confident in taking on full stack web applications in Go. What you will learn * Understand Go programming by building a real-world application * Learn the React framework to develop a frontend for your application * Understand isomorphic web development utilizing the GopherJS framework * Explore methods to write RESTful web APIs in Go using the Gin framework * Learn practical topics such as ORM layers, secure communications, and Stripe's API * Learn methods to benchmark and test web APIs in Go Who this book is for Hands-On Full Stack Development with Go will appeal to developers who are looking to start building amazing full stack web applications in Go. Basic knowhow of Go language and JavaScript is expected. The book targets web developers who are looking to move to the Go language.

Learn how to build complete machine learning systems with IBM Cloud and Watson Machine learning services Key Features * Implement data science and machine learning techniques to draw insights from real-world data * Understand what IBM Cloud platform can help you to implement cognitive insights within applications * Understand the role of data representation and feature extraction in any machine learning system Book Description IBM Cloud is a collection of cloud computing services for data analytics using machine learning and artificial intelligence (AI). This book is a complete guide to help you become well versed with machine learning on the IBM Cloud using Python. Hands-On Machine Learning with IBM Watson starts with supervised and unsupervised machine learning concepts, in addition to providing you with an overview of IBM Cloud and Watson Machine Learning. You'll gain insights into running various techniques, such as K-means clustering, K-nearest neighbor (KNN), and time series prediction in IBM Cloud with real-world examples. The book will then help you delve into creating a Spark pipeline in Watson Studio. You will also be guided through deep learning and neural network principles on the IBM Cloud using TensorFlow. With the help of NLP techniques, you can then brush up on building a chatbot. In later chapters, you will cover three powerful case studies, including the facial expression classification platform, the automated classification of lithofacies, and the multi-biometric identity authentication platform, helping you to become well versed with these methodologies. By the end of this book, you will be ready to build efficient machine learning solutions on the IBM Cloud and draw insights from the data at hand using real-world examples. What you will learn * Understand key characteristics of IBM machine learning services * Run supervised and unsupervised techniques in the cloud * Understand how to create a Spark pipeline in Watson Studio * Implement deep learning and neural networks on the IBM Cloud with TensorFlow * Create a complete, cloud-based facial expression classification solution * Use biometric traits to build a cloud-based human identification system Who this book is for This beginner-level book is for data scientists and machine learning engineers who want to get started with IBM Cloud and its machine learning services using practical examples. Basic knowledge of Python and some understanding of machine learning will be useful.

Leverage the power of MongoDB 4.x to build and administer fault-tolerant database applications Key Features * Master the new features and capabilities of MongoDB 4.x * Implement advanced data modeling, querying, and administration techniques in MongoDB * Includes rich case-studies and best practices followed by expert MongoDB developers Book Description MongoDB is the best platform for working with non-relational data and is considered to be the smartest tool for organizing data in line with business needs. The recently released MongoDB 4.x supports ACID transactions and makes the technology an asset for enterprises across the IT and fintech sectors. This book provides expertise in advanced and niche areas of managing databases (such as modeling and querying databases) along with various administration techniques in MongoDB, thereby helping you become a successful MongoDB expert. The book helps you understand how the newly added capabilities function with the help of some interesting examples and large datasets. You will dive deeper into niche areas such as high-performance configurations, optimizing SQL statements, configuring large-scale sharded clusters, and many more. You will also master best practices in overcoming database failover, and master recovery and backup procedures for database security. By the end of the book, you will have gained a practical understanding of administering database applications both on premises and on the cloud; you will also be able to scale database applications across all servers. What you will learn * Perform advanced querying techniques such as indexing and expressions * Configure, monitor, and maintain a highly scalable MongoDB environment * Master replication and data sharding to optimize read/write performance * Administer MongoDB-based applications on premises or on the cloud * Integrate MongoDB with big data sources to process huge amounts of data * Deploy MongoDB on Kubernetes containers * Use MongoDB in IoT, mobile, and serverless environments Who this book is for This book is ideal for MongoDB developers and database administrators who wish to become successful MongoDB experts and build scalable and fault-tolerant applications using MongoDB. It will also be useful for database professionals who wish to become certified MongoDB professionals. Some understanding of MongoDB and basic database concepts is required to get the most out of this book.

A practical guide for developing end-to-end serverless microservices in Python for developers, DevOps, and architects. Key Features * Create a secure, cost-effective, and scalable serverless data API * Use identity management and authentication for a user-specific and secure web application * Go beyond traditional web hosting to explore the full range of cloud hosting options Book Description Over the last few years, there has been a massive shift from monolithic architecture to microservices, thanks to their small and independent deployments that allow increased flexibility and agile delivery. Traditionally, virtual machines and containers were the principal mediums for deploying microservices, but they involved a lot of operational effort, configuration, and maintenance. More recently, serverless computing has gained popularity due to its built-in autoscaling abilities, reduced operational costs, and increased productivity. Building Serverless Microservices in Python begins by introducing you to serverless microservice structures. You will then learn how to create your first serverless data API and test your microservice. Moving on, you'll delve into data management and work with serverless patterns. Finally, the book introduces you to the importance of securing microservices. By the end of the book, you will have gained the skills you need to combine microservices with serverless computing, making their deployment much easier thanks to the cloud provider managing the servers and capacity planning. What you will learn * Discover what microservices offer above and beyond other architectures * Create a serverless application with AWS * Gain secure access to data and resources * Run tests on your configuration and code * Create a highly available serverless microservice data API * Build, deploy, and run your serverless configuration and code Who this book is for If you are a developer with basic knowledge of Python and want to learn how to build, test, deploy, and secure microservices, then this book is for you. No prior knowledge of building microservices is required.

Discover the power of location data to build effective, intelligent data models with Geospatial ecosystems Key Features * Manipulate location-based data and create intelligent geospatial data models * Build effective location recommendation systems used by popular companies such as Uber * A hands-on guide to help you consume spatial data and parallelize GIS operations effectively Book Description Data scientists, who have access to vast data streams, are a bit myopic when it comes to intrinsic and extrinsic location-based data and are missing out on the intelligence it can provide to their models. This book demonstrates effective techniques for using the power of data science and geospatial intelligence to build effective, intelligent data models that make use of location-based data to give useful predictions and analyses. This book begins with a quick overview of the fundamentals of location-based data and how techniques such as Exploratory Data Analysis can be applied to it. We then delve into spatial operations such as computing distances, areas, extents, centroids, buffer polygons, intersecting geometries, geocoding, and more, which adds additional context to location data. Moving ahead, you will learn how to quickly build and deploy a geo-fencing system using Python. Lastly, you will learn how to leverage geospatial analysis techniques in popular recommendation systems such as collaborative filtering and location-based recommendations, and more. By the end of the book, you will be a rockstar when it comes to performing geospatial analysis with ease. What you will learn * Learn how companies now use location data * Set up your Python environment and install Python geospatial packages * Visualize spatial data as graphs * Extract geometry from spatial data * Perform spatial regression from scratch * Build web applications which dynamically references geospatial data Who this book is for Data Scientists who would like to leverage location-based data and want to use location-based intelligence in their data models will find this book useful. This book is also for GIS developers who wish to incorporate data analysis in their projects. Knowledge of Python programming and some basic understanding of data analysis are all you need to get the most out of this book.

Explore the fundamentals of systems programming starting from kernel API and filesystem to network programming and process communications Key Features * Learn how to write Unix and Linux system code in Golang v1.12 * Perform inter-process communication using pipes, message queues, shared memory, and semaphores * Explore modern Go features such as goroutines and channels that facilitate systems programming Book Description System software and applications were largely created using low-level languages such as C or C++. Go is a modern language that combines simplicity, concurrency, and performance, making it a good alternative for building system applications for Linux and macOS. This Go book introduces Unix and systems programming to help you understand the components the OS has to offer, ranging from the kernel API to the filesystem, and familiarize yourself with Go and its specifications. You'll also learn how to optimize input and output operations with files and streams of data, which are useful tools in building pseudo terminal applications. You'll gain insights into how processes communicate with each other, and learn about processes and daemon control using signals, pipes, and exit codes. This book will also enable you to understand how to use network communication using various protocols, including TCP and HTTP. As you advance, you'll focus on Go's best feature-concurrency helping you handle communication with channels and goroutines, other concurrency tools to synchronize shared resources, and the context package to write elegant applications. By the end of this book, you will have learned how to build concurrent system applications using Go What you will learn * Explore concepts of system programming using Go and concurrency * Gain insights into Golang's internals, memory models and allocation * Familiarize yourself with the filesystem and IO streams in general * Handle and control processes and daemons' lifetime via signals and pipes * Communicate with other applications effectively using a network * Use various encoding formats to serialize complex data structures * Become well-versed in concurrency with channels, goroutines, and sync * Use concurrency patterns to build robust and performant system applications Who this book is for If you are a developer who wants to learn system programming with Go, this book is for you. Although no knowledge of Unix and Linux system programming is necessary, intermediate knowledge of Go will help you understand the concepts covered in the book

Evade antiviruses and bypass firewalls with the most widely used penetration testing frameworks Key Features * Gain insights into the latest antivirus evasion techniques * Set up a complete pentesting environment using Metasploit and virtual machines * Discover a variety of tools and techniques that can be used with Kali Linux Book Description Penetration testing or ethical hacking is a legal and foolproof way to identify vulnerabilities in your system. With thorough penetration testing, you can secure your system against the majority of threats. This Learning Path starts with an in-depth explanation of what hacking and penetration testing is. You’ll gain a deep understanding of classical SQL and command injection flaws, and discover ways to exploit these flaws to secure your system. You'll also learn how to create and customize payloads to evade antivirus software and bypass an organization's defenses. Whether it’s exploiting server vulnerabilities and attacking client systems, or compromising mobile phones and installing backdoors, this Learning Path will guide you through all this and more to improve your defense against online attacks. By the end of this Learning Path, you'll have the knowledge and skills you need to invade a system and identify all its vulnerabilities. This Learning Path includes content from the following Packt products: * Web Penetration Testing with Kali Linux - Third Edition by Juned Ahmed Ansari and Gilberto Najera-Gutierrez * Metasploit Penetration Testing Cookbook - Third Edition by Abhinav Singh , Monika Agarwal, et al What you will learn * Build and analyze Metasploit modules in Ruby * Integrate Metasploit with other penetration testing tools * Use server-side attacks to detect vulnerabilities in web servers and their applications * Explore automated attacks such as fuzzing web applications * Identify the difference between hacking a web application and network hacking * Deploy Metasploit with the Penetration Testing Execution Standard (PTES) * Use MSFvenom to generate payloads and backdoor files, and create shellcode Who this book is for This Learning Path is designed for security professionals, web programmers, and pentesters who want to learn vulnerability exploitation and make the most of the Metasploit framework. Some understanding of penetration testing and Metasploit is required, but basic system administration skills and the ability to read code are a must.

Understand how blockchain works and explore a variety of strategies to implement it in your organization effectively Key Features * Become familiar with business challenges faced by companies when using blockchain * Discover how companies implement blockchain to monetize and secure their data * Study real-world examples to understand blockchain and its use in organizations Book Description In addition to cryptocurrencies, blockchain-based apps are being developed in different industries such as banking, supply chain, and healthcare to achieve digital transformation and enhance user experience. Blockchain is not only about Bitcoin or cryptocurrencies, but also about different technologies such as peer-to-peer networks, consensus mechanisms, and cryptography. These technologies together help sustain trustless environments in which digital value can be transferred between individuals without intermediaries. This book will help you understand the basics of blockchain such as consensus protocols, decentralized applications, and tokenization. You'll focus on how blockchain is used today in different industries and the technological challenges faced while implementing a blockchain strategy. The book also enables you, as a decision maker, to understand blockchain from a technical perspective and evaluate its applicability in your business. Finally, you'll get to grips with blockchain frameworks such as Hyperledger and Quorum and their usability. By the end of this book, you'll have learned about the current use cases of blockchain and be able to implement a blockchain strategy on your own. What you will learn * Become well-versed with how blockchain works * Understand the difference between blockchain and Bitcoin * Learn how blockchain is being used in different industry verticals such as finance and retail * Delve into the technological and organizational challenges of implementing blockchain * Explore the possibilities that blockchain can unlock for decision makers * Choose a blockchain framework best suited for your projects from options such as Ethereum and Hyperledger Fabric Who this book is for This book is for CXOs, business professionals, organization leaders, decision makers, technology enthusiasts, and managers who wish to understand how blockchain is implemented in different organizations, its impact, and how it can be customized according to business needs. Prior experience with blockchain is not required.

Discover various techniques to develop maintainable code and keep it in shape. Key Features * Learn all about refactoring - why it is important and how to do it * Discover easy ways to refactor code with examples * Explore techniques that can be applied to most other programming languages Book Description Refactoring improves your code without changing its behavior. With refactoring, the best approach is to apply small targeted changes to a codebase. Instead of doing a huge sweeping change to your code, refactoring is better as a long-term and continuous enterprise. Refactoring TypeScript explains how to spot bugs and remove them from your code. You’ll start by seeing how wordy conditionals, methods, and null checks make code unhealthy and unstable. Whether it is identifying messy nested conditionals or removing unnecessary methods, this book will show various techniques to avoid these pitfalls and write code that is easier to understand, maintain, and test. By the end of the book, you’ll have learned some of the main causes of unhealthy code, tips to identify them and techniques to address them. What you will learn * Spot and fix common code smells to create code that is easier to read and understand * Discover ways to identify long methods and refactor them * Create objects that keep your code flexible, maintainable, and testable * Apply the Single Responsibility Principle to develop less-coupled code * Discover how to combine different refactoring techniques * Learn ways to solve the issues caused by overusing primitives Who this book is for This book is designed for programmers who are looking to explore various refactoring techniques to develop healthy and maintainable code. Some experience in JavaScript and TypeScript can help you easily grasp the concepts explained in this book.

Your one-stop guide to learning and implementing artificial neural networks with Keras effectively Key Features * Design and create neural network architectures on different domains using Keras * Integrate neural network models in your applications using this highly practical guide * Get ready for the future of neural networks through transfer learning and predicting multi network models Book Description Neural networks are used to solve a wide range of problems in different areas of AI and deep learning. Hands-On Neural Networks with Keras will start with teaching you about the core concepts of neural networks. You will delve into combining different neural network models and work with real-world use cases, including computer vision, natural language understanding, synthetic data generation, and many more. Moving on, you will become well versed with convolutional neural networks (CNNs), recurrent neural networks (RNNs), long short-term memory (LSTM) networks, autoencoders, and generative adversarial networks (GANs) using real-world training datasets. We will examine how to use CNNs for image recognition, how to use reinforcement learning agents, and many more. We will dive into the specific architectures of various networks and then implement each of them in a hands-on manner using industry-grade frameworks. By the end of this book, you will be highly familiar with all prominent deep learning models and frameworks, and the options you have when applying deep learning to real-world scenarios and embedding artificial intelligence as the core fabric of your organization. What you will learn * Understand the fundamental nature and workflow of predictive data modeling * Explore how different types of visual and linguistic signals are processed by neural networks * Dive into the mathematical and statistical ideas behind how networks learn from data * Design and implement various neural networks such as CNNs, LSTMs, and GANs * Use different architectures to tackle cognitive tasks and embed intelligence in systems * Learn how to generate synthetic data and use augmentation strategies to improve your models * Stay on top of the latest academic and commercial developments in the field of AI Who this book is for This book is for machine learning practitioners, deep learning researchers and AI enthusiasts who are looking to get well versed with different neural network architecture using Keras. Working knowledge of Python programming language is mandatory.

Create advanced applications with Python and OpenCV, exploring the potential of facial recognition, machine learning, deep learning, web computing and augmented reality. Key Features * Develop your computer vision skills by mastering algorithms in Open Source Computer Vision 4 (OpenCV 4)and Python * Apply machine learning and deep learning techniques with TensorFlow, Keras, and PyTorch * Discover the modern design patterns you should avoid when developing efficient computer vision applications Book Description OpenCV is considered to be one of the best open source computer vision and machine learning software libraries. It helps developers build complete projects in relation to image processing, motion detection, or image segmentation, among many others. OpenCV for Python enables you to run computer vision algorithms smoothly in real time, combining the best of the OpenCV C++ API and the Python language. In this book, you'll get started by setting up OpenCV and delving into the key concepts of computer vision. You'll then proceed to study more advanced concepts and discover the full potential of OpenCV. The book will also introduce you to the creation of advanced applications using Python and OpenCV, enabling you to develop applications that include facial recognition, target tracking, or augmented reality. Next, you'll learn machine learning techniques and concepts, understand how to apply them in real-world examples, and also explore their benefits, including real-time data production and faster data processing. You'll also discover how to translate the functionality provided by OpenCV into optimized application code projects using Python bindings. Toward the concluding chapters, you'll explore the application of artificial intelligence and deep learning techniques using the popular Python libraries TensorFlow, and Keras. By the end of this book, you'll be able to develop advanced computer vision applications to meet your customers' demands. What you will learn * Handle files and images, and explore various image processing techniques * Explore image transformations, including translation, resizing, and cropping * Gain insights into building histograms * Brush up on contour detection, filtering, and drawing * Work with Augmented Reality to build marker-based and markerless applications * Work with the main machine learning algorithms in OpenCV * Explore the deep learning Python libraries and OpenCV deep learning capabilities * Create computer vision and deep learning web applications Who this book is for This book is designed for computer vision developers, engineers, and researchers who want to develop modern computer vision applications. Basic experience of OpenCV and Python programming is a must.

Write efficient, reusable scripts to build custom characters, game environments, and control enemy AI Key Features * Build captivating multiplayer games using Unreal Engine and C++ * Incorporate existing C++ libraries into your game to add extra functionality such as hardware integration * Practical solutions for memory management, error handling, inputs, and collision for your game codebase Book Description Unreal Engine 4 (UE4) is a popular and award-winning game engine that powers some of the most popular games. A truly powerful tool for game development, there has never been a better time to use it for both commercial and independent projects. With more than 100 recipes, this book shows how to unleash the power of C++ while developing games with Unreal Engine. This book takes you on a journey to jumpstart your C++ and UE4 development skills. You will start off by setting up UE4 for C++ development and learn how to work with Visual Studio, a popular code editor. You will learn how to create C++ classes and structs the Unreal way. This will be followed by exploring memory management, smart pointers, and debugging your code. You will then learn how to make your own Actors and Components through code and how to handle input and collision events. You will also get exposure to many elements of game development including creating user interfaces, artificial intelligence, and writing code with networked play in mind. You will also learn how to add on to the Unreal Editor itself. With a range of task-oriented recipes, this book provides actionable information about writing code for games with UE4 using C++. By the end of the book, you will be empowered to become a top-notch developer with UE4 using C++ as your scripting language! What you will learn * Create C++ classes and structs that integrate well with UE4 and the Blueprints editor * Discover how to work with various APIs that Unreal Engine already contains * Utilize advanced concepts such as events, delegates, and interfaces in your UE4 projects * Build user interfaces using Canvas and UMG through C++ * Extend the Unreal Editor by creating custom windows and editors * Implement AI tasks and services using C++, Blackboard, and Behavior Trees * Write C++ code with networking in mind and replicate properties and functions Who this book is for If you are really passionate game developer looking for solutions to common scripting problems, then this is the book for you. Understanding of the fundamentals of game design and C++ is expected to get the most from this book.

Leverage Docker to unlock efficient and rapid container deployments to improve your development workflow Key Features * Reconfigure Docker hosts to create a logging system with the ElasticSearch-Logstash-Kibana (ELK) stack * Tackle the challenges of large-scale container deployment with this fast-paced guide * Benchmark the performance of your Docker containers using Apache JMeter Book Description Docker is an enterprise-grade container platform that allows you to build and deploy your apps. Its portable format lets you run your code right from your desktop workstations to popular cloud computing providers. This comprehensive guide will improve your Docker work?ows and ensure your application's production environment runs smoothly. This book starts with a refresher on setting up and running Docker and details the basic setup for creating a Docker Swarm cluster. You will then learn how to automate this cluster by using Chef Server and Cookbook. After that, you will run the Docker monitoring system with Prometheus and Grafana, and deploy the ELK stack. You will also learn some tips for optimizing Docker images. After deploying containers with the help of Jenkins, you will then move on to a tutorial on using Apache JMeter to analyze your application's performance. You will learn how to use Docker Swarm and NGINX to load-balance your application and how common debugging tools in Linux can be used to troubleshoot Docker containers. By the end of this book, you will be able to integrate all the optimizations that you have learned and put everything into practice in your applications. What you will learn * Automate provisioning and setting up nodes in a Docker Swarm cluster * Configure a monitoring system with Prometheus and Grafana * Use Apache JMeter to create workloads for benchmarking the performance of Docker containers * Understand how to load-balance an application with Docker Swarm and Nginx * Deploy strace, tcdump, blktrace, and other Linux debugging tools to troubleshoot containers * Integrate Docker optimizations for DevOps, Site Reliability Engineering, CI, and CD Who this book is for If you are a software developer with a good understanding of managing Docker services and the Linux file system and are looking for ways to optimize working with Docker containers, then this is the book for you. Developers fascinated with containers and workflow automation with benefit from this book.