Introduction to deep learning and PyTorch by building a convolutional neural network and recurrent neural network for real-world use cases such as image classification, transfer learning, and natural language processing. Key Features *Clear and concise explanations *Gives important insights into deep learning models *Practical demonstration of key concepts Book Description PyTorch is extremely powerful and yet easy to learn. It provides advanced features, such as supporting multiprocessor, distributed, and parallel computation. This book is an excellent entry point for those wanting to explore deep learning with PyTorch to harness its power. This book will introduce you to the PyTorch deep learning library and teach you how to train deep learning models without any hassle. We will set up the deep learning environment using PyTorch, and then train and deploy different types of deep learning models, such as CNN, RNN, and autoencoders. You will learn how to optimize models by tuning hyperparameters and how to use PyTorch in multiprocessor and distributed environments. We will discuss long short-term memory network (LSTMs) and build a language model to predict text. By the end of this book, you will be familiar with PyTorch's capabilities and be able to utilize the library to train your neural networks with relative ease. What you will learn *Set up the deep learning environment using the PyTorch library *Learn to build a deep learning model for image classification *Use a convolutional neural network for transfer learning *Understand to use PyTorch for natural language processing *Use a recurrent neural network to classify text *Understand how to optimize PyTorch in multiprocessor and distributed environments *Train, optimize, and deploy your neural networks for maximum accuracy and performance *Learn to deploy production-ready models Who this book is for Developers and Data Scientist familiar with Machine Learning but new to deep learning, or existing practitioners of deep learning who would like to use PyTorch to train their deep learning models will find this book to be useful. Having knowledge of Python programming will be an added advantage, while previous exposure to PyTorch is not needed.

Understand, explore, and effectively present data using the powerful data visualization techniques of Python Key Features *Use the power of Pandas and Matplotlib to easily solve data mining issues *Understand the basics of statistics to build powerful predictive data models *Grasp data mining concepts with helpful use-cases and examples Book Description Data mining, or parsing the data to extract useful insights, is a niche skill that can transform your career as a data scientist Python is a flexible programming language that is equipped with a strong suite of libraries and toolkits, and gives you the perfect platform to sift through your data and mine the insights you seek. This Learning Path is designed to familiarize you with the Python libraries and the underlying statistics that you need to get comfortable with data mining. You will learn how to use Pandas, Python's popular library to analyze different kinds of data, and leverage the power of Matplotlib to generate appealing and impressive visualizations for the insights you have derived. You will also explore different machine learning techniques and statistics that enable you to build powerful predictive models. By the end of this Learning Path, you will have the perfect foundation to take your data mining skills to the next level and set yourself on the path to become a sought-after data science professional. This Learning Path includes content from the following Packt products: *Statistics for Machine Learning by Pratap Dangeti *Matplotlib 2.x By Example by Allen Yu, Claire Chung, Aldrin Yim *Pandas Cookbook by Theodore Petrou What you will learn *Understand the statistical fundamentals to build data models *Split data into independent groups *Apply aggregations and transformations to each group *Create impressive data visualizations *Prepare your data and design models *Clean up data to ease data analysis and visualization *Create insightful visualizations with Matplotlib and Seaborn *Customize the model to suit your own predictive goals Who this book is for If you want to learn how to use the many libraries of Python to extract impactful information from your data and present it as engaging visuals, then this is the ideal Learning Path for you. Some basic knowledge of Python is enough to get started with this Learning Path.

Build powerful data analytics applications with this business intelligence tool and overcome all your business challenges Key Features *Master time-saving techniques and make your QlikView development more efficient *Perform geographical analysis and sentiment analysis in your QlikView applications *Explore advanced QlikView techniques, tips, and tricks to deliver complex business requirements Book Description QlikView is one of the most flexible and powerful business intelligence platforms around, and if you want to transform data into insights, it is one of the best options you have at hand. Use this Learning Path, to explore the many features of QlikView to realize the potential of your data and present it as impactful and engaging visualizations. Each chapter in this Learning Path starts with an understanding of a business requirement and its associated data model and then helps you create insightful analysis and data visualizations around it. You will look at problems that you might encounter while visualizing complex data insights using QlikView, and learn how to troubleshoot these and other not-so-common errors. This Learning Path contains real-world examples from a variety of business domains, such as sales, finance, marketing, and human resources. With all the knowledge that you gain from this Learning Path, you will have all the experience you need to implement your next QlikView project like a pro. This Learning Path includes content from the following Packt products: *QlikView for Developers by Miguel ?ngel García, Barry Harmsen *Mastering QlikView by Stephen Redmond *Mastering QlikView Data Visualization by Karl Pover What you will learn *Deliver common business requirements using advanced techniques *Load data from disparate sources to build associative data models *Understand when to apply more advanced data visualization *Utilize the built-in aggregation functions for complex calculations *Build a data architecture that supports scalable QlikView deployments *Troubleshoot common data visualization errors in QlikView *Protect your QlikView applications and data Who this book is for This Learning Path is designed for developers who want to go beyond their technical knowledge of QlikView and understand how to create analysis and data visualizations that solve real business needs. To grasp the concepts explained in this Learning Path, you should have a basic understanding of the common QlikView functions and some hands-on experience with the tool.

Step-by-step guide to build high performing predictive applications Key Features *Use the Python data analytics ecosystem to implement end-to-end predictive analytics projects *Explore advanced predictive modeling algorithms with an emphasis on theory with intuitive explanations *Learn to deploy a predictive model's results as an interactive application Book Description Predictive analytics is an applied field that employs a variety of quantitative methods using data to make predictions. It involves much more than just throwing data onto a computer to build a model. This book provides practical coverage to help you understand the most important concepts of predictive analytics. Using practical, step-by-step examples, we build predictive analytics solutions while using cutting-edge Python tools and packages. The book's step-by-step approach starts by defining the problem and moves on to identifying relevant data. We will also be performing data preparation, exploring and visualizing relationships, building models, tuning, evaluating, and deploying model. Each stage has relevant practical examples and efficient Python code. You will work with models such as KNN, Random Forests, and neural networks using the most important libraries in Python's data science stack: NumPy, Pandas, Matplotlib, Seaborn, Keras, Dash, and so on. In addition to hands-on code examples, you will find intuitive explanations of the inner workings of the main techniques and algorithms used in predictive analytics. By the end of this book, you will be all set to build high-performance predictive analytics solutions using Python programming. What you will learn *Get to grips with the main concepts and principles of predictive analytics *Learn about the stages involved in producing complete predictive analytics solutions *Understand how to define a problem, propose a solution, and prepare a dataset *Use visualizations to explore relationships and gain insights into the dataset *Learn to build regression and classification models using scikit-learn *Use Keras to build powerful neural network models that produce accurate predictions *Learn to serve a model's predictions as a web application Who this book is for This book is for data analysts, data scientists, data engineers, and Python developers who want to learn about predictive modeling and would like to implement predictive analytics solutions using Python's data stack. People from other backgrounds who would like to enter this exciting field will greatly benefit from reading this book. All you need is to be proficient in Python programming and have a basic understanding of statistics and college-level algebra.

A comprehensive guide to Android forensics, from setting up the workstation to analyzing key artifacts Key Features *Get up and running with modern mobile forensic strategies and techniques *Analyze the most popular Android applications using free and open source forensic tools *Learn malware detection and analysis techniques to investigate mobile cybersecurity incidents Book Description Many forensic examiners rely on commercial, push-button tools to retrieve and analyze data, even though there is no tool that does either of these jobs perfectly. Learning Android Forensics will introduce you to the most up-to-date Android platform and its architecture, and provide a high-level overview of what Android forensics entails. You will understand how data is stored on Android devices and how to set up a digital forensic examination environment. As you make your way through the chapters, you will work through various physical and logical techniques to extract data from devices in order to obtain forensic evidence. You will also learn how to recover deleted data and forensically analyze application data with the help of various open source and commercial tools. In the concluding chapters, you will explore malware analysis so that you’ll be able to investigate cybersecurity incidents involving Android malware. By the end of this book, you will have a complete understanding of the Android forensic process, you will have explored open source and commercial forensic tools, and will have basic skills of Android malware identification and analysis. What you will learn *Understand Android OS and architecture *Set up a forensics environment for Android analysis *Perform logical and physical data extractions *Learn to recover deleted data *Explore how to analyze application data *Identify malware on Android devices *Analyze Android malware Who this book is for If you are a forensic analyst or an information security professional wanting to develop your knowledge of Android forensics, then this is the book for you. Some basic knowledge of the Android mobile platform is expected.

An effective guide to becoming an AWS Certified SysOps Administrator Key Features * Not only pass the certification with confidence but also enhance your skills to solving real-world scenarios. * A practical guide to getting you hands-on experience with application management, deployment, operation. * Enhance your AWS skills with practice questions and mock tests. Book Description AWS certifications are becoming one of the must have certifications for any IT professional working on an AWS Cloud platform. This book will act as your one stop preparation guide to validate your technical expertise in deployment, management, and operations on the AWS platform. Along with exam specific content this book will also deep dive into real world scenarios and hands-on instructions. This book will revolve around concepts like teaching you to deploy, manage, and operate scalable, highly available, and fault tolerant systems on AWS. You will also learn to migrate an existing on-premises application to AWS. You get hands-on experience in selecting the appropriate AWS service based on compute, data, or security requirements. This book will also get you well versed with estimating AWS usage costs and identifying operational cost control mechanisms. By the end of this book, you will be all prepared to implement and manage resources efficiently on the AWS cloud along with confidently passing the AWS Certified SysOps Administrator – Associate exam. What you will learn * Create and manage users, groups, and permissions using AWS IAM services * Create a secure VPC with public and private subnets, Network Access Control, and security groups * Get started with launching your first EC2 instance, and working with it * Handle application traffic with ELB and monitor AWS resources with CloudWatch * Work with S3, Glacier, and CloudFront * Work across distributed application components using SWF * Understand event-based processing with Lambda and messaging SQS and SNS in AWS * Get familiar with AWS deployment concepts and tools including Elastic Beanstalk, CloudFormation and AWS OpsWorks Who this book is for If you are a system administrator or a system engineer interested in leveraging the AWS platform to deploy applications then, this book is for you. IT professionals interested in passing the AWS Certified Sysops Administrator will also benefit from this book. Some basic understanding of working AWS components would do wonders.

Leverage the power of Kubernetes to build an efficient software delivery pipeline. Key Features * Learn about DevOps, containers, and Kubernetes all within one handy book * A practical guide to container management and orchestration * Learn how to monitor, log, and troubleshoot your Kubernetes applications Book Description Kubernetes has been widely adopted across public clouds and on-premise data centers. As we're living in an era of microservices, knowing how to use and manage Kubernetes is an essential skill for everyone in the IT industry. This book is a guide to everything you need to know about Kubernetes—from simply deploying a container to administrating Kubernetes clusters wisely. You'll learn about DevOps fundamentals, as well as deploying a monolithic application as microservices and using Kubernetes to orchestrate them. You will then gain an insight into the Kubernetes network, extensions, authentication and authorization. With the DevOps spirit in mind, you'll learn how to allocate resources to your application and prepare to scale them efficiently. Knowing the status and activity of the application and clusters is crucial, so we’ll learn about monitoring and logging in Kubernetes. Having an improved ability to observe your services means that you will be able to build a continuous delivery pipeline with confidence. At the end of the book, you'll learn how to run managed Kubernetes services on three top cloud providers: Google Cloud Platform, Amazon Web Services, and Microsoft Azure. What you will learn * Learn fundamental and advanced DevOps skills and tools * Get a comprehensive understanding of containers * Dockerize an application * Administrate and manage Kubernetes cluster * Extend the cluster functionality with custom resources * Understand Kubernetes network and service mesh * Implement Kubernetes logging and monitoring * Manage Kubernetes services in Amazon Web Services, Google Cloud Platform,and Microsoft Azure Who this book is for This book is for anyone who wants to learn containerization and clustering in a practical way using Kubernetes. No prerequisite skills are required, however, essential DevOps skill and public/private Cloud knowledge will accelerate the reading speed. If you're advanced, you can get a deeper understanding of all the tools and technique described in the book.

Build, secure, and deploy real-world serverless applications in AWS and peek into the serverless cloud offerings from Azure, Google Cloud, and IBM Cloud Key Features * Build serverless applications with AWS Lambda, AWS CloudFormation and AWS CloudWatch * Perform data analytics and natural language processing(NLP)on the AWS serverless platform * Explore various design patterns and best practices involved in serverless computing Book Description Managing physical servers will be a thing of the past once you’re able to harness the power of serverless computing. If you’re already prepped with the basics of serverless computing, Serverless Programming Cookbook will help you take the next step ahead. This recipe-based guide provides solutions to problems you might face while building serverless applications. You'll begin by setting up Amazon Web Services (AWS), the primary cloud provider used for most recipes. The next set of recipes will cover various components to build a Serverless application including REST APIs, database, user management, authentication, web hosting, domain registration, DNS management, CDN, messaging, notifications and monitoring. The book also introduces you to the latest technology trends such as Data Streams, Machine Learning and NLP. You will also see patterns and practices for using various services in a real world application. Finally, to broaden your understanding of Serverless computing, you'll also cover getting started guides for other cloud providers such as Azure, Google Cloud Platform and IBM cloud. By the end of this book, you’ll have acquired the skills you need to build serverless applications efficiently using various cloud offerings. What you will learn * Serverless computing in AWS and explore services with other clouds * Develop full-stack apps with API Gateway, Cognito, Lambda and DynamoDB * Web hosting with S3, CloudFront, Route 53 and AWS Certificate Manager * SQS and SNS for effective communication between microservices * Monitoring and troubleshooting with CloudWatch logs and metrics * Explore Kinesis Streams, Amazon ML models and Alexa Skills Kit Who this book is for For developers looking for practical solutions to common problems while building a serverless application, this book provides helpful recipes. To get started with this intermediate-level book, knowledge of basic programming is a must.

Unearth the power of GraphQL, React, Apollo, Node, and Express to build a scalable, production ready application Key Features * Build full stack applications with modern APIs using GraphQL and Apollo * Integrate Apollo into React and build frontend components using GraphQL * Implement a self-updating notification pop-up with a unique GraphQL feature called Subscriptions Book Description React, one of the most widely used JavaScript frameworks, allows developers to build fast and scalable front end applications for any use case. GraphQL is the modern way of querying an API. It represents an alternative to REST and is the next evolution in web development. Combining these two revolutionary technologies will give you a future-proof and scalable stack you can start building your business around. This book will guide you in implementing applications by using React, Apollo, Node.js and SQL. We'll focus on solving complex problems with GraphQL, such as abstracting multi-table database architectures and handling image uploads. Our client, and server will be powered by Apollo. Finally we will go ahead and build a complete Graphbook. While building the app, we'll cover the tricky parts of connecting React to the back end, and maintaining and synchronizing state. We'll learn all about querying data and authenticating users. We'll write test cases to verify the front end and back end functionality for our application and cover deployment. By the end of the book, you will be proficient in using GraphQL and React for your full-stack development requirements. What you will learn * Resolve data from multi-table database and system architectures * Build a GraphQL API by implementing models and schemas with Apollo and Sequelize * Set up an Apollo Client and build front end components using React * Use Mocha to test your full-stack application * Write complex React components and share data across them * Deploy your application using Docker Who this book is for The book is for web developers who want to enhance their skills and build complete full stack applications using industry standards. Familiarity with JavaScript, React, and GraphQL is expected to get the most from this book.

Create responsive eLearning content, including quizzes, demonstrations, simulations and Virtual Reality projects that fit on any device with Adobe Captivate 2019 Key Features * Build responsive, interactive and highly engaging eLearning content with Adobe Captivate 2019 * Build Virtual Reality eLearning experiences with Adobe Captivate 2019 * Assess your student knowledge with interactive and random quizzes * Seamlessly integrate your eLearning content with any SCORM or xAPI compliant LMS Book Description Adobe Captivate is used to create highly engaging, interactive, and responsive eLearning content. This book takes you through the production of a few pieces of eLearning content, covering all the project types and workflows of Adobe Captivate. First, you will learn how to create a typical interactive Captivate project. This will give you the opportunity to review all Captivate objects and uncover the application's main tools. Then, you will use the built-in capture engine of Captivate to create an interactive software simulation and a Video Demo that can be published as an MP4 video. Then, you will approach the advanced responsive features of Captivate to create a project that can be viewed on any device. And finally, you will immerse your learners in a 360o environment by creating Virtual Reality projects of Adobe Captivate. At the end of the book, you will empower your workflow and projects with the newer and most advanced features of the application, including variables, advanced actions, JavaScript, and using Captivate 2019 with other applications. If you want to produce high quality eLearning content using a wide variety of techniques, implement eLearning in your company, enable eLearning on any device, assess the effectiveness of the learning by using extensive Quizzing features, or are simply interested in eLearning, this book has you covered! What you will learn * Learn how to use the objects in Captivate to build professional eLearning content * Enhance your projects by adding interactivity, animations, and more * Add multimedia elements, such as audio and video, to create engaging learning experiences * Use themes to craft a unique visual experience * Use question slides to create SCORM-compliant quizzes that integrate seamlessly with your LMS * Make your content fit any device with responsive features of Captivate * Create immersive 360° experiences with Virtual Reality projects of Captivate 2019 * Integrate Captivate with other applications (such as PowerPoint and Photoshop) to establish a professional eLearning production workflow * Publish your project in a wide variety of formats including HTML5 and Flash Who this book is for If you are a teacher, instructional designer, eLearning developer, or human resources manager who wants to implement eLearning, then this book is for you. A basic knowledge of your OS is all it takes to create the next generation of responsive eLearning content.

A comprehensive guide for MCSA Exam 70-740, that will help you prepare from day one to earn the valuable Microsoft Certificate Key Features * Leverage practice questions and mock tests to pass this certification with confidence * Learn to Install Windows Servers,implement high availability, and monitor server environments * Gain necessary skills to implement and configure storage and compute features Book Description MCSA: Windows Server 2016 certification is one of the most sought-after certifications for IT professionals, which includes working with Windows Server and performing administrative tasks around it. This book is aimed at the 70-740 certification and is part of Packt's three-book series on MCSA Windows Server 2016 certification, which covers Exam 70-740, Exam 70-741, and Exam 70-742. This book will cover exam objectives for the 70-740 exam, and starting from installing and configuring Windows Server 2016, Windows Server imaging and deployment to configuring and managing disks and volumes, implementing and configuring server storage and implementing Hyper-V. At the end of each chapter you will be provided test questions to revise your learnings which will boost your confidence in preparing for the actual certifications. By the end of this book, you will learn everything needed to pass the, MCSA Exam 70-740: Installation, Storage, and Compute with Windows Server 2016, certification. What you will learn * Install Windows Server 2016 * Upgrade and Migrate servers and workloads * Implement and configure server storage * Install and configure Hyper-V * Configure the virtual machine (VM) settings * Configure Hyper-V storage * Configure Hyper-V networking Who this book is for This book is ideal for system administrators interested in installing and configuring storage and compute features with Windows Sever 2016 and aiming to pass the 70-740 certification. Some experience with Windows Server in an enterprise environment is assumed.

Begin writing graphical user interface(GUI) applications for building human machine interfaces with a clear understanding of key concepts of the Qt framework Key Features * Learn how to write, assemble, and build Qt application from the command line * Understand key concepts like Signals and Slots in Qt * Best practices and effective techniques for designing graphical user interfaces using Qt 5 Book Description Qt is a cross-platform application framework and widget toolkit that is used to create GUI applications that can run on different hardware and operating systems. The main aim of this book is to introduce Qt to the reader. Through the use of simple examples, we will walk you through building blocks without focusing too much on theory. Qt is a popular tool that can be used for building a variety of applications, such as web browsers, media players such as VLC, and Adobe Photoshop. Following Qt installation and setup, the book dives straight into helping you create your first application. You will be introduced to Widgets, Qt's interface building block, and the many varieties that are available for creating GUIs. Next, Qt's core concept of signals and slots are well illustrated with sufficient examples. The book further teaches you how to create custom widgets, signals and slots, and how to communicate useful information via dialog boxes. To cap everything off, you will be taken through writing applications that can connect to databases in order to persist data. By the end of the book, you should be well equipped to start creating your own Qt applications and confident enough to pick up more advanced Qt techniques and materials to hone your skills. What you will learn * Set up and configure your machine to begin developing Qt applications * Discover different widgets and layouts for constructing UIs * Understand the key concept of signals and slots * Understand how signals and slots help animate a GUI * Explore how to create customized widgets along with signals and slots * Understand how to subclass and create a custom windows application * Understand how to write applications that can talk to databases. Who this book is for Anyone trying to start development of graphical user interface application will find this book useful. One does not need prior exposure to other toolkits to understand this book. In order to learn from this book you should have basic knowledge of C++ and a good grasp of Object Oriented Programming. Familiarity with GNU/Linux will be very useful though it's not a mandatory skill.

Understand and solve complex computational problems and write efficient code with Kotlin Key Features * Learn about important data structures such as lists, arrays, queues, and stacks * Design custom algorithms for real-life implementations * Identify suitable tools for different scenarios and deliver immediate results Book Description Data structures and algorithms are more than just theoretical concepts. They help you become familiar with computational methods for solving problems and writing logical code. Equipped with this knowledge, you can write efficient programs that run faster and use less memory. Hands-On Data Structures and Algorithms with Kotlin book starts with the basics of algorithms and data structures, helping you get to grips with the fundamentals and measure complexity. You'll then move on to exploring the basics of functional programming while getting used to thinking recursively. Packed with plenty of examples along the way, this book will help you grasp each concept easily. In addition to this, you'll get a clear understanding of how the data structures in Kotlin's collection framework work internally. By the end of this book, you will be able to apply the theory of data structures and algorithms to work out real-world problems. What you will learn * Understand the basic principles of algorithms and data structures * Explore general-purpose data structures with arrays and linked lists * Get to grips with the basics of stacks, queues, and double-ended queues * Understand functional programming and related data structures * Use performant searching and efficient sorting * Uncover how Kotlin's collection framework functions * Become adept at implementing different types of maps Who this book is for If you're a Kotlin developer who wants to learn the intricacies of implementing data structures and algorithms for scalable application development, this book is for you.

Create dynamic dashboards to bring interactive data visualization to your enterprise using Qlik Sense Key Features * Implement various Qlik Sense features to create interactive dashboards * Analyze data easily and make business decisions faster using Qlik Sense * Perform self-service data analytics and geospatial analytics using an example-based approach Book Description Qlik Sense allows you to explore simple-to-complex data to reveal hidden insights and data relationships to make business-driven decisions. Hands-On Business Intelligence with Qlik Sense begins by helping you get to grips with underlying Qlik concepts and gives you an overview of all Qlik Sense’s features. You will learn advanced modeling techniques and learn how to analyze the data loaded using a variety of visualization objects. You’ll also be trained on how to share apps through Qlik Sense Enterprise and Qlik Sense Cloud and how to perform aggregation with AGGR. As you progress through the chapters, you’ll explore the stories feature to create data-driven presentations and update an existing story. This book will guide you through the GeoAnalytics feature with the geo-mapping object and GeoAnalytics connector. Furthermore, you’ll learn about the self-service analytics features and perform data forecasting using advanced analytics. Lastly, you’ll deploy Qlik Sense apps for mobile and tablet. By the end of this book, you will be well-equipped to run successful business intelligence applications using Qlik Sense's functionality, data modeling techniques, and visualization best practices. What you will learn * Discover how to load, reshape, and model data for analysis * Apply data visualization practices to create stunning dashboards * Make use of Python and R for advanced analytics * Perform geo-analysis to create visualizations using native objects * Learn how to work with AGGR and data stories Who this book is for If you’re a data analyst, BI developer, or interested in business intelligence and want to gain practical experience of working on Qlik Sense, this book is for you. You’ll also find it useful if you want to explore Qlik Sense’s next-generation applications for self-service business intelligence. No prior experience of working with Qlik Sense is required.

Understand the core concepts of deep learning and deep reinforcement learning by applying them to develop games Key Features * Apply the power of deep learning to complex reasoning tasks by building a Game AI * Exploit the most recent developments in machine learning and AI for building smart games * Implement deep learning models and neural networks with Python Book Description The number of applications of deep learning and neural networks has multiplied in the last couple of years. Neural nets has enabled significant breakthroughs in everything from computer vision, voice generation, voice recognition and self-driving cars. Game development is also a key area where these techniques are being applied. This book will give an in depth view of the potential of deep learning and neural networks in game development. We will take a look at the foundations of multi-layer perceptron’s to using convolutional and recurrent networks. In applications from GANs that create music or textures to self-driving cars and chatbots. Then we introduce deep reinforcement learning through the multi-armed bandit problem and other OpenAI Gym environments. As we progress through the book we will gain insights about DRL techniques such as Motivated Reinforcement Learning with Curiosity and Curriculum Learning. We also take a closer look at deep reinforcement learning and in particular the Unity ML-Agents toolkit. By the end of the book, we will look at how to apply DRL and the ML-Agents toolkit to enhance, test and automate your games or simulations. Finally, we will cover your possible next steps and possible areas for future learning. What you will learn * Learn the foundations of neural networks and deep learning. * Use advanced neural network architectures in applications to create music, textures, self driving cars and chatbots. * Understand the basics of reinforcement and DRL and how to apply it to solve a variety of problems. * Working with Unity ML-Agents toolkit and how to install, setup and run the kit. * Understand core concepts of DRL and the differences between discrete and continuous action environments. * Use several advanced forms of learning in various scenarios from developing agents to testing games. Who this book is for This books is for game developers who wish to create highly interactive games by leveraging the power of machine and deep learning. No prior knowledge of machine learning, deep learning or neural networks is required this book will teach those concepts from scratch. A good understanding of Python is required.