Build your Machine Learning portfolio by creating 6 cutting-edge Artificial Intelligence projects using neural networks in Python Key Features * Discover neural network architectures (like CNN and LSTM) that are driving recent advancements in AI * Build expert neural networks in Python using popular libraries such as Keras * Includes projects such as object detection, face identification, sentiment analysis, and more Book Description Neural networks are at the core of recent AI advances, providing some of the best resolutions to many real-world problems, including image recognition, medical diagnosis, text analysis, and more. This book goes through some basic neural network and deep learning concepts, as well as some popular libraries in Python for implementing them. It contains practical demonstrations of neural networks in domains such as fare prediction, image classification, sentiment analysis, and more. In each case, the book provides a problem statement, the specific neural network architecture required to tackle that problem, the reasoning behind the algorithm used, and the associated Python code to implement the solution from scratch. In the process, you will gain hands-on experience with using popular Python libraries such as Keras to build and train your own neural networks from scratch. By the end of this book, you will have mastered the different neural network architectures and created cutting-edge AI projects in Python that will immediately strengthen your machine learning portfolio. What you will learn * Learn various neural network architectures and its advancements in AI * Master deep learning in Python by building and training neural network * Master neural networks for regression and classification * Discover convolutional neural networks for image recognition * Learn sentiment analysis on textual data using Long Short-Term Memory * Build and train a highly accurate facial recognition security system Who this book is for This book is a perfect match for data scientists, machine learning engineers, and deep learning enthusiasts who wish to create practical neural network projects in Python. Readers should already have some basic knowledge of machine learning and neural networks.

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 .

Get ready for the Windows 10: 70-698 exam and configure Windows to manage data recovery Key Features * Implement Windows 10 operational and administrative tasks * Configure devices, remote management settings, advanced management tools, and device drivers * Comprehensive guide to help you work efficiently in Windows 10 Book Description The Installing and Configuring Windows 10: 70-698 Exam Guide is designed to confirm what you already know, while also updating your knowledge of Windows 10. With its easy-to-follow guidance, you will quickly learn the user interface and discover steps to work efficiently in Windows 10 to rule out delays and obstacles. This book begins by covering various ways of installing Windows 10, followed by instructions on post-installation tasks. You will learn about the deployment of Windows 10 in Enterprise and also see how to configure networking in Windows 10. You’ll understand how to leverage Disk Management and Windows PowerShell to configure disks, volumes, and file system options. As you progress through the chapters, you will be able to set up remote management in Windows 10 and learn more about Windows update usage, behavior, and settings. You will also gain insights that will help you monitor and manage data recovery and explore how to configure authentication, authorization, and advanced management tools in Windows 10. By the end of this book, you will be equipped with enough knowledge to take the 70-698 exam and explore different study methods to improve your chances of passing the exam with ease. What you will learn * Discover various ways of installing Windows 10 * Understand how to configure devices and device drivers * Configure and support IPv4 and IPv6 network settings * Troubleshoot storage and removable device issues * Get to grips with data access and usage * Explore the advanced management tools available in Windows 10 Who this book is for This book is for IT professionals who perform installation, configuration, general local management and maintenance of Windows 10 core services and are preparing to clear the Windows 10: 70-698 exam

Enhance your programming skills by learning the intricacies of object oriented programming in C# 8 Key Features * Understand the four pillars of OOP; encapsulation, inheritance, abstraction and polymorphism * Leverage the latest features of C# 8 including nullable reference types and Async Streams * Explore various design patterns, principles, and best practices in OOP Book Description Object-oriented programming (OOP) is a programming paradigm organized around objects rather than actions, and data rather than logic. With the latest release of C#, you can look forward to new additions that improve object-oriented programming. This book will get you up to speed with OOP in C# in an engaging and interactive way. The book starts off by introducing you to C# language essentials and explaining OOP concepts through simple programs. You will then go on to learn how to use classes, interfacesm and properties to write pure OOP code in your applications. You will broaden your understanding of OOP further as you delve into some of the advanced features of the language, such as using events, delegates, and generics. Next, you will learn the secrets of writing good code by following design patterns and design principles. You'll also understand problem statements with their solutions and learn how to work with databases with the help of ADO.NET. Further on, you'll discover a chapter dedicated to the Git version control system. As you approach the conclusion, you'll be able to work through OOP-specific interview questions and understand how to tackle them. By the end of this book, you will have a good understanding of OOP with C# and be able to take your skills to the next level. What you will learn * Master OOP paradigm fundamentals * Explore various types of exceptions * Utilize C# language constructs efficiently * Solve complex design problems by understanding OOP * Understand how to work with databases using ADO.NET * Understand the power of generics in C# * Get insights into the popular version control system, Git * Learn how to model and design your software Who this book is for This book is designed for people who are new to object-oriented programming. Basic C# skills are assumed, however, prior knowledge of OOP in any other language is not required.

Go beyond the basics and unleash the full power of QGIS 3.4 and 3.6 with practical, step-by-step examples Key Features * One-stop solution to all of your GIS needs * Master QGIS by learning about database integration, and geoprocessing tools * Learn about the new and updated Processing toolbox and perform spatial analysis Book Description QGIS is an open source solution to GIS and widely used by GIS professionals all over the world. It is the leading alternative to proprietary GIS software. Although QGIS is described as intuitive, it is also, by default, complex. Knowing which tools to use and how to apply them is essential to producing valuable deliverables on time. Starting with a refresher on the QGIS basics and getting you acquainted with the latest QGIS 3.6 updates, this book will take you all the way through to teaching you how to create a spatial database and a GeoPackage. Next, you will learn how to style raster and vector data by choosing and managing different colors. The book will then focus on processing raster and vector data. You will be then taught advanced applications, such as creating and editing vector data. Along with that, you will also learn about the newly updated Processing Toolbox, which will help you develop the advanced data visualizations. The book will then explain to you the graphic modeler, how to create QGIS plugins with PyQGIS, and how to integrate Python analysis scripts with QGIS. By the end of the book, you will understand how to work with all aspects of QGIS and will be ready to use it for any type of GIS work. What you will learn * Create and manage a spatial database * Get to know advanced techniques to style GIS data * Prepare both vector and raster data for processing * Add heat maps, live layer effects, and labels to your maps * Master LAStools and GRASS integration with the Processing Toolbox * Edit and repair topological data errors * Automate workflows with batch processing and the QGIS Graphical Modeler * Integrate Python scripting into your data processing workflows * Develop your own QGIS plugins Who this book is for If you are a GIS professional, a consultant, a student, or perhaps a fast learner who wants to go beyond the basics of QGIS, then this book is for you. It will prepare you to realize the full potential of QGIS.

Gain basic skills in network forensics and learn how to apply them effectively Key Features * Investigate network threats with ease * Practice forensics tasks such as intrusion detection, network analysis, and scanning * Learn forensics investigation at the network level Book Description Network forensics is a subset of digital forensics that deals with network attacks and their investigation. In the era of network attacks and malware threat, it’s now more important than ever to have skills to investigate network attacks and vulnerabilities. Hands-On Network Forensics starts with the core concepts within network forensics, including coding, networking, forensics tools, and methodologies for forensic investigations. You’ll then explore the tools used for network forensics, followed by understanding how to apply those tools to a PCAP file and write the accompanying report. In addition to this, you will understand how statistical flow analysis, network enumeration, tunneling and encryption, and malware detection can be used to investigate your network. Towards the end of this book, you will discover how network correlation works and how to bring all the information from different types of network devices together. By the end of this book, you will have gained hands-on experience of performing forensics analysis tasks. What you will learn * Discover and interpret encrypted traffic * Learn about various protocols * Understand the malware language over wire * Gain insights into the most widely used malware * Correlate data collected from attacks * Develop tools and custom scripts for network forensics automation Who this book is for The book targets incident responders, network engineers, analysts, forensic engineers and network administrators who want to extend their knowledge from the surface to the deep levels of understanding the science behind network protocols, critical indicators in an incident and conducting a forensic search over the wire.

Solve real-world data problems with R and machine learning Key Features * Third edition of the bestselling, widely acclaimed R machine learning book, updated and improved for R 3.5 and beyond * Harness the power of R to build flexible, effective, and transparent machine learning models * Learn quickly with a clear, hands-on guide by experienced machine learning teacher and practitioner, Brett Lantz Book Description Machine learning, at its core, is concerned with transforming data into actionable knowledge. R offers a powerful set of machine learning methods to quickly and easily gain insight from your data. Machine Learning with R, Third Edition provides a hands-on, readable guide to applying machine learning to real-world problems. Whether you are an experienced R user or new to the language, Brett Lantz teaches you everything you need to uncover key insights, make new predictions, and visualize your findings. This new 3rd edition updates the classic R data science book with newer and better libraries, advice on ethical and bias issues in machine learning, and an introduction to deep learning. Find powerful new insights in your data; discover machine learning with R. What you will learn * Discover the origins of machine learning and how exactly a computer learns by example * Prepare your data for machine learning work with the R programming language * Classify important outcomes using nearest neighbor and Bayesian methods * Predict future events using decision trees, rules, and support vector machines * Forecast numeric data and estimate financial values using regression methods * Model complex processes with artificial neural networks — the basis of deep learning * Avoid bias in machine learning models * Evaluate your models and improve their performance * Connect R to SQL databases and emerging big data technologies such as Spark, H2O, and TensorFlow Who this book is for Data scientists, students, and other practitioners who want a clear, accessible guide to machine learning with R.

Learn to use AWS IoT services to build your connected applications with the help of this comprehensive guide. About This Book ? Gets you started with AWS IoT and its functionalities ? Learn different modules of AWS IoT with practical use cases. ? Learn to secure your IoT communication Who This Book Is For This book is for anyone who wants to get started with the AWS IoT Suite and implement it with practical use cases. This book acts as an extensive guide, on completion of which you will be in a position to start building IoT projects using AWS IoT platform and using cloud services for your projects. What You Will Learn ? Implement AWS IoT on IoT projects ? Learn the technical capabilities of AWS IoT and IoT devices ? Create IoT-based AWS IoT projects ? Choose IoT devices and AWS IoT platforms to use based on the kind of project you need to build ? Deploy AWS Greengrass and AWS Lambda ? Develop program for AWS IoT Button ? Visualize IoT AWS data ? Build predictive analytics using AWS IoT and AWS Machine Learning In Detail The Internet of Things market increased a lot in the past few years and IoT development and its adoption have showed an upward trend. Analysis and predictions say that Enterprise IoT platforms are the future of IoT. AWS IoT is currently leading the market with its wide range of device support SDKs and versatile management console. This book initially introduces you to the IoT platforms, and how it makes our IoT development easy. It then covers the complete AWS IoT Suite and how it can be used to develop secure communication between internet-connected things such as sensors, actuators, embedded devices, smart applications, and so on. The book also covers the various modules of AWS: AWS Greengrass, AWS device SDKs, AWS IoT Platform, AWS Button, AWS Management consoles, AWS-related CLI, and API references, all with practical use cases. Near the end, the book supplies security-related best practices to make bi-directional communication more secure. When you've finished this book, you'll be up-and-running with the AWS IoT Suite, and building IoT projects. Style and approach This book is a step-by-step practical guide that helps you learn AWS IoT quickly.

Enhance your organization’s secure posture by improving your attack and defense strategies About This Book ? Gain a clear understanding of the attack methods, and patterns to recognize abnormal behavior within your organization with Blue Team tactics. ? Learn to unique techniques to gather exploitation intelligence, identify risk and demonstrate impact with Red Team and Blue Team strategies. ? A practical guide that will give you hands-on experience to mitigate risks and prevent attackers from infiltrating your system. Who This Book Is For This book aims at IT professional who want to venture the IT security domain. IT pentester, Security consultants, and ethical hackers will also find this course useful. Prior knowledge of penetration testing would be beneficial. What You Will Learn ? Learn the importance of having a solid foundation for your security posture ? Understand the attack strategy using cyber security kill chain ? Learn how to enhance your defense strategy by improving your security policies, hardening your network, implementing active sensors, and leveraging threat intelligence ? Learn how to perform an incident investigation ? Get an in-depth understanding of the recovery process ? Understand continuous security monitoring and how to implement a vulnerability management strategy ? Learn how to perform log analysis to identify suspicious activities In Detail The book will start talking about the security posture before moving to Red Team tactics, where you will learn the basic syntax for the Windows and Linux tools that are commonly used to perform the necessary operations. You will also gain hands-on experience of using new Red Team techniques with powerful tools such as python and PowerShell, which will enable you to discover vulnerabilities in your system and how to exploit them. Moving on, you will learn how a system is usually compromised by adversaries, and how they hack user's identity, and the various tools used by the Red Team to find vulnerabilities in a system. In the next section, you will learn about the defense strategies followed by the Blue Team to enhance the overall security of a system. You will also learn about an in-depth strategy to ensure that there are security controls in each network layer, and how you can carry out the recovery process of a compromised system. Finally, you will learn how to create a vulnerability management strategy and the different techniques for manual log analysis. By the end of this book, you will be well-versed with Red Team and Blue Team techniques and will have learned the techniques used nowadays to attack and defend systems. Style and approach This book uses a practical approach of the cybersecurity kill chain to explain the different phases of the attack, which includes the rationale behind each phase, followed by scenarios and examples that brings the theory into practice.

Build effective regression models in R to extract valuable insights from real data About This Book ? Implement different regression analysis techniques to solve common problems in data science - from data exploration to dealing with missing values ? From Simple Linear Regression to Logistic Regression - this book covers all regression techniques and their implementation in R ? A complete guide to building effective regression models in R and interpreting results from them to make valuable predictions Who This Book Is For This book is intended for budding data scientists and data analysts who want to implement regression analysis techniques using R. If you are interested in statistics, data science, machine learning and wants to get an easy introduction to the topic, then this book is what you need! Basic understanding of statistics and math will help you to get the most out of the book. Some programming experience with R will also be helpful What You Will Learn ? Get started with the journey of data science using Simple linear regression ? Deal with interaction, collinearity and other problems using multiple linear regression ? Understand diagnostics and what to do if the assumptions fail with proper analysis ? Load your dataset, treat missing values, and plot relationships with exploratory data analysis ? Develop a perfect model keeping overfitting, under-fitting, and cross-validation into consideration ? Deal with classification problems by applying Logistic regression ? Explore other regression techniques – Decision trees, Bagging, and Boosting techniques ? Learn by getting it all in action with the help of a real world case study. In Detail Regression analysis is a statistical process which enables prediction of relationships between variables. The predictions are based on the casual effect of one variable upon another. Regression techniques for modeling and analyzing are employed on large set of data in order to reveal hidden relationship among the variables. This book will give you a rundown explaining what regression analysis is, explaining you the process from scratch. The first few chapters give an understanding of what the different types of learning are – supervised and unsupervised, how these learnings differ from each other. We then move to covering the supervised learning in details covering the various aspects of regression analysis. The outline of chapters are arranged in a way that gives a feel of all the steps covered in a data science process – loading the training dataset, handling missing values, EDA on the dataset, transformations and feature engineering, model building, assessing the model fitting and performance, and finally making predictions on unseen datasets. Each chapter starts with explaining the theoretical concepts and once the reader gets comfortable with the theory, we move to the practical examples to support the understanding. The practical examples are illustrated using R code including the different packages in R such as R Stats, Caret and so on. Each chapter is a mix of theory and practical examples. By the end of this book you will know all the concepts and pain-points related to regression analysis, and you will be able to implement your learning in your projects. Style and approach An easy-to-follow step by step guide which will help you get to grips with real world application of Regression Analysis with R

Master the capabilities of PostgreSQL 10 to efficiently manage and maintain your database About This Book ? Your one-stop guide to mastering advanced concepts in PostgreSQL 10 with ease ? Master query optimization, replication, and high availability with PostgreSQL ? Extend the functionalities of your PostgreSQL instance to suit your organizational needs with minimal effort Who This Book Is For If you are a PostgreSQL data architect or an administrator and want to understand how to implement advanced functionalities and master complex administrative tasks with PostgreSQL 10, then this book is perfect for you. Prior experience of administrating a PostgreSQL database and a working knowledge of SQL are required to make the best use of this book. What You Will Learn ? Get to grips with the advanced features of PostgreSQL 10 and handle advanced SQL ? Make use of the indexing features in PostgreSQL and fine-tune the performance of your queries ? Work with stored procedures and manage backup and recovery ? Master replication and failover techniques ? Troubleshoot your PostgreSQL instance for solutions to common and not-so-common problems ? Learn how to migrate your database from MySQL and Oracle to PostgreSQL without any hassle In Detail PostgreSQL is an open source database used for handling large datasets (big data) and as a JSON document database. This book highlights the newly introduced features in PostgreSQL 10, and shows you how you can build better PostgreSQL applications, and administer your PostgreSQL database more efficiently. We begin by explaining advanced database design concepts in PostgreSQL 10, along with indexing and query optimization. You will also see how to work with event triggers and perform concurrent transactions and table partitioning, along with exploring SQL and server tuning. We will walk you through implementing advanced administrative tasks such as server maintenance and monitoring, replication, recovery, high availability, and much more. You will understand common and not-so-common troubleshooting problems and how you can overcome them. By the end of this book, you will have an expert-level command of advanced database functionalities and will be able to implement advanced administrative tasks with PostgreSQL 10. Style and approach This mastering-level guide delves into the advanced functionalities of PostgreSQL 10

Get up and running with all the new features of ECMAScript and explore new ways of coding with JavaScript. About This Book ? Grasp the latest features of ECMAScript and the best way to use it in production code ? Learn newly added native APIs to JS Engine and perform tasks efficiently with a cleaner code base ? Understand the more complex sides of JavaScript such as the inheritance model, low-level memory management, multithreaded environments, and web workers Who This Book Is For This book is for web developers who have some basic programming knowledge and want to learn to write cleaner code with the power of ECMAScript. What You Will Learn ? Implement methods associated with objects as per the latest ECMAScript specification ? Make use of the latest features of ECMAScript ? Make use of many new APIs in HTML5 and modern JavaScript implementation ? Use SharedArrayBuffers for superfast concurrent and parallel programming ? Perform asynchronous programming with JavaScript ? Implement the best ways and practices to perform modular programming in JavaScript In Detail Learn ECMAScript explores implementation of the latest ECMAScript features to add to your developer toolbox, helping you to progress to an advanced level. Learn to add 1 to a variable andsafely access shared memory data within multiple threads to avoid race conditions. You’ll start the book by building on your existing knowledge of JavaScript, covering performing arithmetic operations, using arrow functions and dealing with closures. Next, you will grasp the most commonly used ECMAScript skills such as reflection, proxies, and classes. Furthermore, you’ll learn modularizing the JS code base, implementing JS on the web and how the modern HTML5 + JS APIs provide power to developers on the web. Finally, you will learn the deeper parts of the language, which include making JavaScript multithreaded with dedicated and shared web workers, memory management, shared memory, and atomics. It doesn’t end here; this book is 100% compatible with ES.Next. By the end of this book, you'll have fully mastered all the features of ECMAScript! Style and approach The level goes gradually from basic to advanced so that the reader can adapt at every point and level up their skills at the same time. The chapters are carefully arranged in a manner that makes every concept easy to learn and deploy right away in your code.

Understand the ServiceNow *ing and build an efficient customized ServiceNow instance About This Book ? Customize your ServiceNow instance according to your organization’s needs ? Learn to work with inbuilt JavaScript APIs in ServiceNow ? Take your ServiceNow experience to the next level by learning to * Who This Book Is For This book is targeted toward ServiceNow administrators or anyone willing to learn inbuilt JavaScript APIs used to * and customize ServiceNow instances. Prior experience with ServiceNow is required. What You Will Learn ? Customize your ServiceNow instance according to your organization's needs ? Explore the ServiceNow-exposed JavaScript APIs and libraries ? Discover the method for using ServiceNow *ing functions ? Take your ServiceNow experience to the next level by understanding advanced *ing ? Learn to build, test, and debug custom applications ? Use your customized instance efficiently with the help of best practices In Detail Industry giants like RedHat and NetApp have adopted ServiceNow for their operational needs, and it is evolving as the number one platform choice for IT Service management. ServiceNow provides their clients with an add-on when it comes to baseline instances, where *ing can be used to customize and improve the performance of instances. It also provides inbuilt JavaScript API for *ing and improving your JavaScript instance. This book will initially cover the basics of ServiceNow *ing and the appropriate time to * in a ServiceNow environment. Then, we dig deeper into client-side and server-side *ing using JavaScipt API. We will also cover advance concepts like on-demand functions, * actions, and best practices. Mastering ServiceNow Scripting acts as an end-to-end guide for writing, testing, and debugging *s of ServiceNow. We cover update sets for moving customizations between ServiceNow instances, jelly *s for making custom pages, and best practices for all types of * in ServiceNow. By the end of this book, you will have hands-on experience in *ing ServiceNow using inbuilt JavaScript API. Style and approach The book will take a practical approach delving into different aspects of ServiceNow *ing to help you become a *ing master.

Develop and run efficient R *s and predictive models for SQL Server 2017 About This Book ? Learn how you can combine the power of R and SQL Server 2017 to build efficient, cost-effective data science solutions ? Leverage the capabilities of R Services to perform advanced analytics—from data exploration to predictive modeling ? A quick primer with practical examples to help you get up- and- running with SQL Server 2017 Machine Learning Services with R, as part of database solutions with continuous integration / continuous delivery. Who This Book Is For This book is for data analysts, data scientists, and database administrators with some or no experience in R but who are eager to easily deliver practical data science solutions in their day-to-day work (or future projects) using SQL Server. What You Will Learn ? Get an overview of SQL Server 2017 Machine Learning Services with R ? Manage SQL Server Machine Learning Services from installation to configuration and maintenance ? Handle and operationalize R code ? Explore RevoScaleR R algorithms and create predictive models ? Deploy, manage, and monitor database solutions with R ? Extend R with SQL Server 2017 features ? Explore the power of R for database administrators In Detail R Services was one of the most anticipated features in SQL Server 2016, improved significantly and rebranded as SQL Server 2017 Machine Learning Services. Prior to SQL Server 2016, many developers and data scientists were already using R to connect to SQL Server in siloed environments that left a lot to be desired, in order to do additional data analysis, superseding SSAS Data Mining or additional CLR programming functions. With R integrated within SQL Server 2017, these developers and data scientists can now benefit from its integrated, effective, efficient, and more streamlined analytics environment. This book gives you foundational knowledge and insights to help you understand SQL Server 2017 Machine Learning Services with R. First and foremost, the book provides practical examples on how to implement, use, and understand SQL Server and R integration in corporate environments, and also provides explanations and underlying motivations. It covers installing Machine Learning Services;maintaining, deploying, and managing code;and monitoring your services. Delving more deeply into predictive modeling and the RevoScaleR package, this book also provides insights into operationalizing code and exploring and visualizing data. To complete the journey, this book covers the new features in SQL Server 2017 and how they are compatible with R, amplifying their combined power. Style and approach This fast-paced guide will help data scientists and DBAs implement all new data science projects using SQL Server 2017 Machine Learning Services.

Leverage the power of machine learning and Swift programming to build intelligent iOS applications with ease About This Book ? Implement effective machine learning solutions for your iOS applications ? Use Swift and Core ML to build and deploy popular machine learning models ? Develop neural networks for natural language processing and computer vision Who This Book Is For iOS developers who wish to create smarter iOS applications using the power of machine learning will find this book to be useful. This book will also benefit data science professionals who are interested in performing machine learning on mobile devices. Familiarity with Swift programming is all you need to get started with this book. What You Will Learn ? Learn rapid model prototyping with Python and Swift ? Deploy pre-trained models to iOS using Core ML ? Find hidden patterns in the data using unsupervised learning ? Get a deeper understanding of the clustering techniques ? Learn modern compact architectures of neural networks for iOS devices ? Train neural networks for image processing and natural language processing In Detail Machine learning as a field promises to bring increased intelligence to the software by helping us learn and analyse information efficiently and discover certain patterns that humans cannot. This book will be your guide as you embark on an exciting journey in machine learning using the popular Swift language. We’ll start with machine learning basics in the first part of the book to develop a lasting intuition about fundamental machine learning concepts. We explore various supervised and unsupervised statistical learning techniques and how to implement them in Swift, while the third section walks you through deep learning techniques with the help of typical real-world cases. In the last section, we will dive into some hard core topics such as model compression, GPU acceleration and provide some recommendations to avoid common mistakes during machine learning application development. By the end of the book, you'll be able to develop intelligent applications written in Swift that can learn for themselves. Style and approach A comprehensive guide that teaches how to implement machine learning apps for iOS from scratch

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.

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.

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

Create interactive cross-platform games with the Godot Engine 3.0 About This Book ? Learn the art of developing cross-platform games ? Leverage Godot’s node and scene system to design robust, reusable game objects ? Integrate Blender easily and efficiently with Godot to create powerful 3D games Who This Book Is For Godot Engine Game Development Projects is for both new users and experienced developers, who want to learn to make games using a modern game engine. Some prior programming experience is recommended. What You Will Learn ? Get started with the Godot game engine and editor ? Organize a game project ? Import graphical and audio assets ? Use Godot’s node and scene system to design robust, reusable game objects ? Write code in GDScript to capture input and build complex behaviors ? Implement user interfaces to display information ? Create visual effects to spice up your game ? Learn techniques that you can apply to your own game projects In Detail Godot Engine Game Development Projects is an introduction to the Godot game engine and its new 3.0 version. Godot 3.0 brings a large number of new features and capabilities that make it a strong alternative to expensive commercial game engines. For beginners, Godot offers a friendly way to learn game development techniques, while for experienced developers it is a powerful, customizable tool that can bring your visions to life. This book consists of five projects that will help developers achieve a sound understanding of the engine when it comes to building games. Game development is complex and involves a wide spectrum of knowledge and skills. This book can help you build on your foundation level skills by showing you how to create a number of small-scale game projects. Along the way, you will learn how Godot works and discover important game development techniques that you can apply to your projects. Using a straightforward, step-by-step approach and practical examples, the book will take you from the absolute basics through to sophisticated game physics, animations, and other techniques. Upon completing the final project, you will have a strong foundation for future success with Godot 3.0. Style and approach The book is divided into five parts; each covering a different small-game project using a straightforward, step-by-step approach and practical examples. The book will take readers from the absolute basics through sophisticated game physics, animation, and other techniques.

Get up and running with the fundamentals of Amazon Alexa and build exciting IoT projects About This Book ? Gain hands-on experience of working with Amazon Echo and Alexa ? Build exciting IoT projects using Amazon Echo ? Learn about voice-enabled smart devices Who This Book Is For Alexa Skills Projects is for individuals who want to have a deep understanding of the underlying technology that drives Amazon Echo and Alexa, and how it can be integrated with the Internet of Things to develop hands-on projects. What You Will Learn ? Understand how Amazon Echo is already being used in various domains ? Discover how an Alexa Skill is architected ? Get a clear understanding of how some of the most popular Alexa Skills work ? Design Alexa Skills for specific purposes and interact with Amazon Echo to execute them ? Gain experience of programming for Amazon Echo ? Explore future applications of Amazon Echo and other voice-activated devices In Detail Amazon Echo is a smart speaker developed by Amazon, which connects to Amazon’s Alexa Voice Service and is entirely controlled by voice commands. Amazon Echo is currently being used for a variety of purposes such as home automation, asking generic queries, and even ordering a cab or pizza. Alexa Skills Projects starts with a basic introduction to Amazon Alexa and Echo. You will then deep dive into Alexa Programming concepts such as Intents, Slots, Lambdas and maintaining your skill’s state using DynamoDB. You will get a clear understanding of how some of the most popular Alexa Skills work, and gain experience of working with real-world Amazon Echo applications. In the concluding chapters, you will explore the future of voice-enabled applications and their coverage with respect to the Internet of Things. By the end of the book, you will have learned to design Alexa Skills for specific purposes and interact with Amazon Echo to execute these skills. Style and approach A practical guide filled with real world examples that will help you understand the process of creating Alexa Skills from scratch and it's real world applications.

Explore the various packages in Julia that support image processing and build neural networks for video processing and object tracking. About This Book ? Build a full-fledged image processing application using JuliaImages ? Perform basic to advanced image and video stream processing with Julia's APIs ? Understand and optimize various features of OpenCV with easy examples Who This Book Is For Hands-On Computer Vision with Julia is for Julia developers who are interested in learning how to perform image processing and want to explore the field of computer vision. Basic knowledge of Julia will help you understand the concepts more effectively. What You Will Learn ? Analyze image metadata and identify critical data using JuliaImages ? Apply filters and improve image quality and color schemes ? Extract 2D features for image comparison using JuliaFeatures ? Cluster and classify images with KNN/SVM machine learning algorithms ? Recognize text in an image using the Tesseract library ? Use OpenCV to recognize specific objects or faces in images and videos ? Build neural network and classify images with MXNet In Detail Hands-On Computer Vision with Julia is a thorough guide for developers who want to get started with building computer vision applications using Julia. Julia is well suited to image processing because it’s easy to use and lets you write easy-to-compile and efficient machine code. This book begins by introducing you to Julia's image processing libraries such as Images.jl and ImageCore.jl. You’ll get to grips with analyzing and transforming images using JuliaImages; some of the techniques discussed include enhancing and adjusting images. As you make your way through the chapters, you’ll learn how to classify images, cluster them, and apply neural networks to solve computer vision problems. In the concluding chapters, you will explore OpenCV applications to perform real-time computer vision analysis, for example, face detection and object tracking. You will also understand Julia's interaction with Tesseract to perform optical character recognition and build an application that brings together all the techniques we introduced previously to consolidate the concepts learned. By end of the book, you will have understood how to utilize various Julia packages and a few open source libraries such as Tesseract and OpenCV to solve computer vision problems with ease. Style and approach Readers will be taken through various packages that support image processing in Julia, and will also tap into open-source libraries such as Open CV and Tesseract to find the optimum solution to problems encountered in computer vision.