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  • Nelson, Abhilash  (7)
  • Eramo, Michael  (6)
  • [Erscheinungsort nicht ermittelbar] : Packt Publishing  (13)
  • 1
    Online Resource
    Online Resource
    The Art of Doing : Dive Into Android Development with Kotlin (2021)
    [Erscheinungsort nicht ermittelbar] : Packt Publishing | Boston, MA : Safari
    Details
    ISBN: 9781803241739
    Language: English
    Pages: 1 online resource (1 video file, approximately 17 hr., 15 min.)
    Edition: 1st edition
    Keywords: Electronic videos
    Abstract: Master the fundamentals of Android Studio, Android app development, and the Kotlin programming language About This Video A complete practical course to master Android application development Create 6 full-fledge applications as well as many more "learning" applications throughout the course Learn to code in Kotlin, Google's official language for Android application development In Detail The Art of Doing: Dive into Android development with Kotlin is a course that takes the time to lay a foundation and build upon it. We won't just get Android Studio installed and rush through all it does for us in creating a project. Instead, we will walk through each file created and the given starter code, so you feel like you are in control of the applications you are writing! We'll continue on this trend of fully explaining and gaining a mastery level of understanding of concepts as we explore various views, layout styles, view and data binding, fragments and navigation, and lastly MVVM architecture. In this course, we will walk through, step by step, how to design the layout and the functionality of unique, engaging, and purposeful apps. Together, we will work through 15 sections of this course. Each section will highlight concepts and ideas, explaining every step along the way and answering any questions you might have. By the end of this course, you will be coming up with your own app ideas and feel confident enough in your abilities to create them. Who this book is for This course is designed for beginner Android students looking to understand Android application development with Kotlin. Also, students who have gained an introductory level knowledge in another language (Python, JavaScript) and are looking for ways to apply their knowledge can benefit from this course. One must have a basic understanding of computer programming principles such as variables, conditionals, loops, and functions as these won’t be covered. Also, have a computer capable of running Android Studio or the Android Emulator or a physical Android device for testing.
    Note: Online resource; Title from title screen (viewed September 28, 2021) , Mode of access: World Wide Web.
    URL: lizenzpflichtig
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  • 2
    Online Resource
    Online Resource
    Beginners' Guide to Practical Quantum Computing with IBM Qiskit (2021)
    [Erscheinungsort nicht ermittelbar] : Packt Publishing | Boston, MA : Safari
    Details
    ISBN: 9781801813686
    Language: English
    Pages: 1 online resource (1 video file, approximately 5 hr., 23 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: A perfect beginners’ guide that converts complex, boring mathematics and formulas into simple and easy to make it clearer. It’s a basic guide to understand general quantum computing concepts on IBM Qiskit documentation. About This Video Learn and understand about general quantum computing based on IBM Qiskit documentation Learn quantum key distribution, which utilizes the unique properties of quantum systems Learn quantum teleportation used for transferring quantum information from a sender to a receiver In Detail Quantum computers could help the development of new breakthroughs in science, medications, machine learning, material science, and finance, which will help mankind become the best civilization in the whole universe. In fact, quantum computing is so powerful that no one knows how to use its true potential and till now, no quantum algorithm is perfect. The hardware and code are still in development stages, providing great opportunities in the future for quantum computing professionals. This course starts by introducing you to the basics of current classical computing technology that is based on bits/binary digits (0 and 1) and quantum computing (qubits), and how it is way much more advanced than earlier. Then you will install and get tested on working with the Jupyter notebook and IBM Qiskit in order to execute codes. Lastly, you will learn all the quantum computing concepts and their execution simultaneously in a much leaner, simpler, and more concise format. By the end of this course, you will learn the basics of quantum computing through implementing it via IBM Qiskit, and you could be able to contribute yourself to the domain that is still in the development phase and be a part of great opportunities in the future for quantum computing professionals. Who this book is for The course is best suited for beginners who want to start with practical quantum computing concepts. Basic computer knowledge and enthusiasm about quantum computing are the only prerequisites to excel and extract the most out of this course.
    Note: Online resource; Title from title screen (viewed August 25, 2021) , Mode of access: World Wide Web.
    URL: lizenzpflichtig
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  • 3
    Online Resource
    Online Resource
    Deep Learning Using Keras - A Complete and Compact Guide for Beginners (2021)
    [Erscheinungsort nicht ermittelbar] : Packt Publishing | Boston, MA : Safari
    Details
    ISBN: 9781803242835
    Language: English
    Pages: 1 online resource (1 video file, approximately 9 hr., 37 min.)
    Edition: 1st edition
    Keywords: Electronic videos
    Abstract: Learn deep learning from scratch using Python and Keras About This Video Perform exploratory data analysis of the loaded data and prepare the data for giving it into the deep learning model Learn how basic CNN layers such as the convolution layer, the pooling layer, and the fully connected layer work Learn to use Google Colab to enhance parallel processing with VGGNet and ResNet models In Detail The artificial intelligence domain is divided broadly into deep learning and machine learning. In fact, deep learning is machine learning itself but deep learning with its deep neural networks and algorithms tries to learn high-level features from data without human intervention. That makes deep learning the base of all future self-intelligent systems. This course begins with going over the basics of Python and then quickly moves on to important libraries of Python that are critical to data analysis and visualizations, such as NumPy, Pandas, and Matplotlib. After the basics, we will then install the deep learning libraries—Theano and TensorFlow—and the API for dealing with these called Keras. Then, before we jump into deep learning, we will have an elaborate theory session about the basic structure of artificial neuron and neural networks, and about activation functions, loss functions, and optimizers. Furthermore, we will create deep learning multi-layer neural network models for a text-based dataset and then convolutional neural networks for an image-based dataset. You will also learn how the basic CNN layers such as the convolution layer, the pooling layer, and the fully connected layer work. Then, we will use different techniques to improve the quality of a model and perform optimization using image augmentation. By the end of this course, you will have a complete understanding of deep learning and will be able to implement these skills in your own projects. Who this book is for This course is designed for beginners who want to learn basic to advanced deep learning and have basic computer knowledge.
    Note: Online resource; Title from title screen (viewed October 27, 2021) , Mode of access: World Wide Web.
    URL: lizenzpflichtig
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  • 4
    Online Resource
    Online Resource
    Basic Statistics and Regression for Machine Learning in Python (2021)
    [Erscheinungsort nicht ermittelbar] : Packt Publishing | Boston, MA : Safari
    Details
    ISBN: 9781803238487
    Language: English
    Pages: 1 online resource (1 video file, approximately 5 hr., 9 min.)
    Edition: 1st edition
    Keywords: Electronic videos
    Abstract: Get ready to learn the basics of machine learning and the mathematics of statistical regression, which powers almost all machine learning algorithms. About This Video A comprehensive course that includes Python coding, visualization, loops, variables, and functions Manual calculation and then using Python functions/codes to understand the difference Beginner to advanced mathematics and statistical concepts that cover machine learning algorithms In Detail This course is for ML enthusiasts who want to understand basic statistics and regression for machine learning. The course starts with setting up the environment and understanding the basics of Python language and different libraries. Next, you'll see the basics of machine learning and different types of data. After that, you'll learn a statistics technique called Central Tendency Analysis. Post this, you'll focus on statistical techniques such as variance and standard deviation. Several techniques and mathematical concepts such as percentile, normal distribution, uniform distribution, finding z-score, linear regression, polynomial linear regression, and multiple regression with the help of manual calculation and Python functions are introduced as the course progresses. The dataset will get more complex as you proceed ahead; you'll use a CSV file to save the dataset. You'll see the traditional and complex method of finding the coefficient of regression and then explore ways to solve it easily with some Python functions. Finally, you'll learn a technique called data normalization or standardization, which will improve the performance of the algorithms very much compared to a non-scaled dataset. By the end of this course, you'll gain a solid foundation in machine learning and statistical regression using Python. Who this book is for This course is for beginners and individuals who want to learn mathematics for machine learning. You need not have any prior experience or knowledge in coding; just be ready with your learning mindset at the highest level. Individuals interested in learning what's actually happening behind the scenes of Python functions and algorithms (at least in a shallow layman's way) will be highly benefitted. Basic computer knowledge and an interest to learn mathematics for machine learning is the only prerequisite for this course.
    Note: Online resource; Title from title screen (viewed October 26, 2021) , Mode of access: World Wide Web.
    URL: lizenzpflichtig
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  • 5
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    Online Resource
    The Art of Doing : Video Game Creation with Python and Pygame (2021)
    [Erscheinungsort nicht ermittelbar] : Packt Publishing | Boston, MA : Safari
    Details
    ISBN: 9781803231587
    Language: English
    Pages: 1 online resource (1 video file, approximately 17 hr., 17 min.)
    Edition: 1st edition
    Keywords: Electronic videos
    Abstract: From simple games using single images to complex games using classes and 100 sprites, this course will teach you how to do it all! About This Video Learn to use the Pygame library in video game design Build seven arcade-style games with different difficulty levels Apply custom character animations using sprite sheets to help make our games really come to life In Detail Have you learned the fundamentals of Python and then asked yourself: what's next? Then this course is for you. We'll begin by learning the fundamentals of the Pygame library and video game design as we move on to making four incredibly fun, arcade-style games called Feed the Dragon, Click the Clown, Snake, and Burger Dog. We will then proceed to the concepts of classes and inheritance in Python, which are crucial tools for taking our games to the next level using Sprites and Sprite Groups. If, you have not worked with classes before, you need not worry, we've got you covered. We will spend some time learning more intermediate concepts such as how to use sprites, sprite groups, and various sprite collision detection methods as we move on to making two intermediate-level games called Monster Wrangler and Space Invaders. The third part of this course focuses on more advanced topics such as creating a tile map and using/reading it to create more complex-level designs, using 2-dimensional vectors to aid with more complex player movements such as running and jumping under forces of friction and gravity, and adding character animations to make our games really come to life! We will apply these concepts as well as all our previous knowledge to make one last game called Zombie Knight, which is the final project. By the end of this course, you will be able to put forward your own game ideas and feel confident enough in your abilities to create them. Who this book is for This course is designed for beginner Python developers who are curious about video game design and the Pygame library or looking to strengthen their understanding of classes and how they can be used in larger projects or have a love for classic arcade-style games. A basic understanding of programming concepts such as variables, lists, loops, and conditionals is required as these won‘t be covered in the course. In the second half of the course, we will be switching to using classes extensively. We will spend some time reviewing and learning the topics of classes and inheritance, although prior knowledge may be helpful.
    Note: Online resource; Title from title screen (viewed October 27, 2021) , Mode of access: World Wide Web.
    URL: lizenzpflichtig
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  • 6
    Online Resource
    Online Resource
    Computer Vision : YOLO Custom Object Detection with Colab GPU (2020)
    [Erscheinungsort nicht ermittelbar] : Packt Publishing | Boston, MA : Safari
    Details
    ISBN: 9781800563865
    Language: English
    Pages: 1 online resource (1 video file, approximately 3 hr., 57 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Pre-train the Coco dataset and custom-train the coronavirus object detection model with Google Colab GPU About This Video Get started with the YOLO object detection method Build models for recognizing objects in images and real-time webcam videos Learn how to prepare custom datasets for building your own coronavirus detection model In Detail Object detection is a popular application of computer vision, helping a computer recognize and classify objects inside an image. This video course will help you learn Python-based object recognition methods and teach you how to develop custom object detection models. The course starts with an introduction to the YOLO (You Only Look Once) object detection system, Python programming, and convolutional neural networks (CNN). You’ll get ready for object detection by installing Anaconda on your computer, and OpenCV library in Python. Next, you’ll perform object detection and recognition on a single object in the image and on a real-time webcam video using a YOLO pre-trained model and the Coco dataset. Moving ahead, you’ll learn the pros and cons of using a pre-trained dataset model and a custom-trained dataset model, along with exploring the free GPU offered by Google Colab. Toward the end, you’ll create a custom dataset and train a darknet YOLO model to detect coronavirus from an electron microscope image or video output. By the end of this video course, you’ll have developed the skills you need to build object recognition models using pre-defined and custom datasets.
    Note: Online resource; Title from title screen (viewed September 30, 2020) , Mode of access: World Wide Web.
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  • 7
    Online Resource
    Online Resource
    The Art of Doing : Master Networks and Network Scanning (2020)
    [Erscheinungsort nicht ermittelbar] : Packt Publishing | Boston, MA : Safari
    Details
    ISBN: 9781801075480
    Language: English
    Pages: 1 online resource (1 video file, approximately 9 hr., 10 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Discover networking from the Linux command-line interface and become an expert in network scanning. About This Video Understand Linux commands, such as ip, arp, ping, macchanger, and systemctl Get ready to use powerful tools like Netcat and Nmap Learn how to write error-free scripts to understand the concepts of network scanning In Detail Do you ever wonder how network scanning is executed just by entering “nmap 192.168.1.0/24” into the command line? With this video course, you'll not only understand how the commands work but you'll also master the concepts of virtual machines, network scanning, and port monitoring. By the end of this video, you will gain a good understanding of networking commands, and develop the skills needed to scan the network.
    Note: Online resource; Title from title screen (viewed November 27, 2020) , Mode of access: World Wide Web.
    URL: lizenzpflichtig
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  • 8
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    Online Resource
    Computer Vision : Python OCR & Object Detection Quick Starter (2020)
    [Erscheinungsort nicht ermittelbar] : Packt Publishing | Boston, MA : Safari
    Details
    ISBN: 9781800567481
    Language: English
    Pages: 1 online resource (1 video file, approximately 4 hr., 32 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Get to grips with optical character recognition, image recognition, object detection, and object recognition using Python About This Video Understand the optical character recognition (OCR) technology Explore convolutional neural networks pre-trained models for image recognition Use Mask R-CNN pre-trained models and MobileNet-SSD for object detection In Detail This course is a quick starter for anyone who wants to explore optical character recognition (OCR), image recognition, object detection, and object recognition using Python without having to deal with all the complexities and mathematics associated with a typical deep learning process. Starting with an introduction to the OCR technology, you’ll get your system ready for Python coding by installing Anaconda packages and the necessary libraries and dependencies. As you advance, you’ll work with convolutional neural networks (CNNs), the Keras library, and pre-trained models, such as VGGNet 16 and VGGNet 19, for performing image recognition with the help of sample images. The course then focuses on object recognition and shows you how to use MobileNet-SSD and Mask R-CNN pre-trained models to detect and label objects in a real-time live video from the computer’s webcam as well as in a saved video. Toward the end, you’ll learn how the YOLO model and the lite version, Tiny YOLO, fasten the process of detecting an object from a single image. By the end of the course, you’ll have developed a solid understanding of OCR and the methods involved and gain the confidence to perform optical character recognition using Python with ease.
    Note: Online resource; Title from title screen (viewed October 23, 2020) , Mode of access: World Wide Web.
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  • 9
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    Online Resource
    The Art of Doing : Code 40 Challenging Python Programs Today! (2020)
    [Erscheinungsort nicht ermittelbar] : Packt Publishing | Boston, MA : Safari
    Details
    ISBN: 9781801075756
    Language: English
    Pages: 1 online resource (1 video file, approximately 28 hr., 20 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: A well-crafted practical course to learn Python by building 40 entertaining applications About This Video Grasp the fundamentals of computer science that are transferable across all programming languages Learn how to import and work with Python libraries, such as Tkinter, Matplotlib, and Random Get ready to write your own real-world Python programs In Detail By encouraging you to build 40 applications, this course will make you well-versed with numerous ideas, theories, and fundamentals of computer science and Python. The course begins with the installation process of Python and an explanation of basic data types used in Python programming. You will then start building 40 meaningful, engaging, and purposeful Python applications that will help you to understand the concepts of Python programming in detail. Some of the applications that you will learn to build are letter counter application, grade sorter application, voter registration application, thesaurus application, and a lot more. By the end of this course, you will be well-versed in Python programming and will have developed the skills to build real-world applications in Python.
    Note: Online resource; Title from title screen (viewed December 24, 2020) , Mode of access: World Wide Web.
    URL: lizenzpflichtig
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  • 10
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    Online Resource
    Computer Vision : Face Recognition Quick Starter in Python (2020)
    [Erscheinungsort nicht ermittelbar] : Packt Publishing | Boston, MA : Safari
    Details
    ISBN: 9781800567221
    Language: English
    Pages: 1 online resource (1 video file, approximately 3 hr., 51 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Build Python deep learning-based face detection, recognition, emotion, gender and age classification systems About This Video Use Python to detect and recognize faces from images and real-time webcam video Become well-versed with emotion detection Get up to speed with predicting age and gender from images and real-time webcam video In Detail Face detection and face recognition are the most popular aspects in computer vision. They are widely used by governments and organizations for surveillance and policing. Moreover, they also have applications in our day-to-day life such as face unlocking mobile phones. This course will help you delve into face recognition using Python without having to deal with all the complexities and mathematics associated with the deep learning process. You will start with an introduction to face detection and face recognition technology. After this, you’ll get the system ready for Python coding by downloading and installing the Anaconda package and other dependencies and libraries that are required such as dlib and OpenCV. You’ll then write Python code to detect faces from a given image and extract the faces as separate images. Next, you’ll focus on face detection by streaming a real-time video from the webcam. The course will also guide you on how to customize the face detection program to blur the detected faces dynamically from the webcam video stream. Moving ahead, you’ll go on to learn facial expression recognition and age and gender prediction using a pre-trained deep learning model. Later, you’ll progress to writing Python code for face recognition, which will help identify the faces that are already detected. You’ll use static images as well as live streaming video from the computer’s webcam to recognize the detected faces with their names. The course then explores the concept of face distance, teaching you how to convert the face distance value to face matching percentage using simple mathematics. Finally, you’ll be able to tweak the face landmark points used for face detection. You’ll draw a line joining the face landmark points to visualize the points in the face which the computer used for evaluation. Taking the landmark points customization to the next level, you’ll create custom face make-up for the face image. By the end of this course, you’ll be well-versed with face recognition and detection and be able to apply your skills in the real world.
    Note: Online resource; Title from title screen (viewed July 30, 2020) , Mode of access: World Wide Web.
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  • 11
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    Online Resource
    The Art of Doing : Create 10 Python GUIs with Tkinter Today! (2020)
    [Erscheinungsort nicht ermittelbar] : Packt Publishing | Boston, MA : Safari
    Details
    ISBN: 9781801070263
    Language: English
    Pages: 1 online resource (1 video file, approximately 14 hr., 7 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Unleash the power of Python’s GUI library- Tkinter, to make real-world interactive applications About This Video Understand the fundamentals of the Tkinter library Learn how to design the layout and functionality of modern GUI applications Get ready to build eleven engaging and purposeful GUI applications In Detail Have you learned the fundamentals of Python and then asked yourself “What next?”. If so, consider taking this course, which will help you create your own Python GUI applications. The course starts with the installation process of Python on your machines and then takes you through the basics of GUI widgets. Once you are settled down, you will learn the concepts of Python by building interesting applications such as Metric Helper, Color Theme Maker, Morse Code Translator, Simon Memory Game, and a lot more. By building these applications, you will learn how to manage the application layout, understand the functionality of the call APIs, and will find out how to create stand-alone executable files that will run on any Windows machine. By the end of this course, you will be well-versed with the fundamentals of GUI application development using Python’s Tkinter library.
    Note: Online resource; Title from title screen (viewed November 30, 2020) , Mode of access: World Wide Web.
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  • 12
    Online Resource
    Online Resource
    The Art of Doing : Learn the Linux Command Line (2020)
    [Erscheinungsort nicht ermittelbar] : Packt Publishing | Boston, MA : Safari
    Details
    ISBN: 9781801071376
    Language: English
    Pages: 1 online resource (1 video file, approximately 6 hr., 59 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Master the Linux command line and develop fundamental skills needed to begin your journey into ethical hacking About This Video Get an insight into the structure of the Linux directory Learn how to work with files and directories using Linux commands Build a solid foundation in Bash scripting In Detail Linux commands are so powerful that using them you can interact with your computer without any assistance of point and click GUI applications. Linux commands are also essential if you are looking to step into the world of ethical hacking. This course will take you through the Linux command line and, in no time, you will be comfortable in performing file and management tasks by using only the Linux commands. The course starts with explaining the installation process of VirtualBox and Kali Linux. Next, you will get to know your computer with the help of terminal commands, such as ipconfig, ping, ip, dp, free, ps, top, kill, whoami, and uname. Moving along, you will learn to navigate through the directory structures and become familiar with the task of making and manipulating files. Later, you will learn to use the grep and awk commands to search through files and understand the concept of changing file permissions. Next, you will learn how to create and modify users and groups and go through the steps of installing new software. Toward the end, you will learn how to compress and extract files and get an overview of Bash scripting. By the end of this course, you will have developed the basic Linux command line skills that will help you to start your career in ethical hacking.
    Note: Online resource; Title from title screen (viewed November 26, 2020) , Mode of access: World Wide Web.
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  • 13
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    Online Resource
    Machine Learning and Data Science with Python : A Complete Beginners Guide (2019)
    [Erscheinungsort nicht ermittelbar] : Packt Publishing | Boston, MA : Safari
    Details
    ISBN: 9781838980689
    Language: English
    Pages: 1 online resource (1 video file, approximately 10 hr., 19 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Machine learning and data science for programming beginners using Python with scikit-learn, SciPy, Matplotlib and Pandas About This Video Learn machine learning and data science using Python A practical course designed for beginners who are interested in machine learning using Python In Detail Artificial intelligence, machine learning, and deep learning neural networks are the most used terms in the technology world today. They’re also the most misunderstood and confused terms. Artificial intelligence is a broad spectrum of science which tries to make machines intelligent like humans, while machine learning and neural networks are two subsets that sit within this vast machine learning platform. But in this course, you will focus mainly on machine learning, which will include preparing your machine to make it ready for a prediction test. You will be using Python as your programming language. Python is a great tool for the development of programs that perform data analysis and prediction. It has a variety of classes and features that perform complex mathematical analyses and provide solutions in just a few lines of code, making it easier for you to get up to speed with data science and machine learning. Machine learning and data science jobs are among the most lucrative in the technology industry in recent times. Exploring this course will help you get well-versed with essential concepts and prepare you for a career in these fields. Downloading the example code for this course: You can download the example code files for this course on GitHub at the following link: https://github.com/PacktPublishing/Machine-Learning-and-Data-Science-with-Python-A-Complete-Beginners-Guide . If you require support please email: customercarepackt.com
    Note: Online resource; Title from title screen (viewed May 29, 2019)
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