Abhishek Mishra – författare
440 kr
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iOS Swift 24-Hour Trainer combines book and video lessons in Apple''s Swift programming language to prepare you to build iPhone and iPad apps—and distribute them through the Appstore. First, this approachable text covers the fundamentals of Swift by introducing you to iOS development in this language, and presenting best practices for setting up a development environment and using variables, statements, expressions, operators, functions, and closures. Next, you explore common tasks, such as alert views, table views, and collection views. You then deepen your knowledge of Swift by considering network programming and local data storage. Finally, this engaging resource dives into slightly more advanced concepts, such as tab bars, web views, the accelerometer, camera, photo library, Google maps, and core location.
Swift was designed by Apple to incorporate modern scripting features while offering simpler, cleaner syntax than Objective-C to maintain a minimal and easy to read style. This more expressive code offers numerous key features, such as closures unified with function pointers, tuples and multiple value returns, generics, and functional programming patterns.
Learn how to obtain a device UDID Test your applications on an actual device, so you can see your work in action Distribute your applications outside of the App store, allowing you to test your work with real users Review common reasons why apps are rejected by Apple to strengthen your case when submitting your apps for distributioniOS Swift 24-Hour Trainer is an essential guide to Apple''s Swift programming language for beginning programmers.
428 kr
Läs direkt efter köp
iOS Swift 24-Hour Trainer combines book and video lessons in Apple''s Swift programming language to prepare you to build iPhone and iPad apps—and distribute them through the Appstore. First, this approachable text covers the fundamentals of Swift by introducing you to iOS development in this language, and presenting best practices for setting up a development environment and using variables, statements, expressions, operators, functions, and closures. Next, you explore common tasks, such as alert views, table views, and collection views. You then deepen your knowledge of Swift by considering network programming and local data storage. Finally, this engaging resource dives into slightly more advanced concepts, such as tab bars, web views, the accelerometer, camera, photo library, Google maps, and core location.
Swift was designed by Apple to incorporate modern scripting features while offering simpler, cleaner syntax than Objective-C to maintain a minimal and easy to read style. This more expressive code offers numerous key features, such as closures unified with function pointers, tuples and multiple value returns, generics, and functional programming patterns.
Learn how to obtain a device UDID Test your applications on an actual device, so you can see your work in action Distribute your applications outside of the App store, allowing you to test your work with real users Review common reasons why apps are rejected by Apple to strengthen your case when submitting your apps for distributioniOS Swift 24-Hour Trainer is an essential guide to Apple''s Swift programming language for beginning programmers.
520 kr
Skickas inom 11-20 vardagar
520 kr
Läs direkt efter köp
Amazon Web Services for Mobile Developers: Building Apps with AWS presents a professional view of cloud computing and AWS for experienced iOS/Android developers and technical/solution architects. Cloud computing is a rapidly expanding ecosystem, and working professionals need a practical resource to bring them up-to-date on tools that are rapidly becoming indispensable; this book helps expand your skill set by introducing you to AWS offerings that can make your job easier, with a focus on real-world application. Author and mobile applications developer Abhishek Mishra shows you how to create IAM accounts and try out some of the most popular services, including EC2, Lambda, Mobile Analytics, Device Farm, and more. You''ll build a chat application in both Swift (iOS) and Java (Andoid), running completely off AWS Infrastructure to explore SDK installation, Xcode, Cognito authentication, DynamoDB, Amazon SNA Notifications, and other useful tools. By actually using the tools as you learn about them, you develop a more intuitive understanding that feels less like a shift and more like a streamlined integration.
If you have prior experience with Swift or Java and a solid knowledge of web services, this book can help you quickly take your skills to the next level with a practical approach to learning that translates easily into real-world use.
Understand the key concepts of AWS as applied to both iOS and Android developers Explore major AWS offerings for mobile developers, including DynamoDB, RDS, EC2, SNS, Cognito, and more Learn what people are talking about when they use buzzwords like PaaS, IaaS, SaaS, and APaaS Work through explanations by building apps that tie into the AWS ecosystemAny job is easier with the right tools, and Amazon Web Services for Mobile Developers: Building Apps with AWS gets you acquainted with an ever-expanding toolkit for mobile app development.
520 kr
Läs direkt efter köp
Amazon Web Services for Mobile Developers: Building Apps with AWS presents a professional view of cloud computing and AWS for experienced iOS/Android developers and technical/solution architects. Cloud computing is a rapidly expanding ecosystem, and working professionals need a practical resource to bring them up-to-date on tools that are rapidly becoming indispensable; this book helps expand your skill set by introducing you to AWS offerings that can make your job easier, with a focus on real-world application. Author and mobile applications developer Abhishek Mishra shows you how to create IAM accounts and try out some of the most popular services, including EC2, Lambda, Mobile Analytics, Device Farm, and more. You''ll build a chat application in both Swift (iOS) and Java (Andoid), running completely off AWS Infrastructure to explore SDK installation, Xcode, Cognito authentication, DynamoDB, Amazon SNA Notifications, and other useful tools. By actually using the tools as you learn about them, you develop a more intuitive understanding that feels less like a shift and more like a streamlined integration.
If you have prior experience with Swift or Java and a solid knowledge of web services, this book can help you quickly take your skills to the next level with a practical approach to learning that translates easily into real-world use.
Understand the key concepts of AWS as applied to both iOS and Android developers Explore major AWS offerings for mobile developers, including DynamoDB, RDS, EC2, SNS, Cognito, and more Learn what people are talking about when they use buzzwords like PaaS, IaaS, SaaS, and APaaS Work through explanations by building apps that tie into the AWS ecosystemAny job is easier with the right tools, and Amazon Web Services for Mobile Developers: Building Apps with AWS gets you acquainted with an ever-expanding toolkit for mobile app development.
530 kr
Skickas inom 3-6 vardagar
465 kr
Läs direkt efter köp
Put the power of AWS Cloud machine learning services to work in your business and commercial applications!
Machine Learning in the AWS Cloud introduces readers to the machine learning (ML) capabilities of the Amazon Web Services ecosystem and provides practical examples to solve real-world regression and classification problems. While readers do not need prior ML experience, they are expected to have some knowledge of Python and a basic knowledge of Amazon Web Services.
Part One introduces readers to fundamental machine learning concepts. You will learn about the types of ML systems, how they are used, and challenges you may face with ML solutions. Part Two focuses on machine learning services provided by Amazon Web Services. You’ll be introduced to the basics of cloud computing and AWS offerings in the cloud-based machine learning space. Then you’ll learn to use Amazon Machine Learning to solve a simpler class of machine learning problems, and Amazon SageMaker to solve more complex problems.
• Learn techniques that allow you to preprocess data, basic feature engineering, visualizing data, and model building
• Discover common neural network frameworks with Amazon SageMaker
• Solve computer vision problems with Amazon Rekognition
• Benefit from illustrations, source code examples, and sidebars in each chapter
The book appeals to both Python developers and technical/solution architects. Developers will find concrete examples that show them how to perform common ML tasks with Python on AWS. Technical/solution architects will find useful information on the machine learning capabilities of the AWS ecosystem.
465 kr
Läs direkt efter köp
Put the power of AWS Cloud machine learning services to work in your business and commercial applications!
Machine Learning in the AWS Cloud introduces readers to the machine learning (ML) capabilities of the Amazon Web Services ecosystem and provides practical examples to solve real-world regression and classification problems. While readers do not need prior ML experience, they are expected to have some knowledge of Python and a basic knowledge of Amazon Web Services.
Part One introduces readers to fundamental machine learning concepts. You will learn about the types of ML systems, how they are used, and challenges you may face with ML solutions. Part Two focuses on machine learning services provided by Amazon Web Services. You’ll be introduced to the basics of cloud computing and AWS offerings in the cloud-based machine learning space. Then you’ll learn to use Amazon Machine Learning to solve a simpler class of machine learning problems, and Amazon SageMaker to solve more complex problems.
• Learn techniques that allow you to preprocess data, basic feature engineering, visualizing data, and model building
• Discover common neural network frameworks with Amazon SageMaker
• Solve computer vision problems with Amazon Rekognition
• Benefit from illustrations, source code examples, and sidebars in each chapter
The book appeals to both Python developers and technical/solution architects. Developers will find concrete examples that show them how to perform common ML tasks with Python on AWS. Technical/solution architects will find useful information on the machine learning capabilities of the AWS ecosystem.
379 kr
Skickas inom 5-8 vardagar
465 kr
Läs direkt efter köp
Harness the power of Apple iOS machine learning (ML) capabilities and learn the concepts and techniques necessary to be a successful Apple iOS machine learning practitioner!
Machine earning (ML) is the science of getting computers to act without being explicitly programmed. A branch of Artificial Intelligence (AI), machine learning techniques offer ways to identify trends, forecast behavior, and make recommendations. The Apple iOS Software Development Kit (SDK) allows developers to integrate ML services, such as speech recognition and language translation, into mobile devices, most of which can be used in multi-cloud settings. Focusing on Apple’s ML services, Machine Learning for iOS Developers is an up-to-date introduction to the field, instructing readers to implement machine learning in iOS applications.
Assuming no prior experience with machine learning, this reader-friendly guide offers expert instruction and practical examples of ML integration in iOS. Organized into two sections, the book’s clearly-written chapters first cover fundamental ML concepts, the different types of ML systems, their practical uses, and the potential challenges of ML solutions. The second section teaches readers to use models—both pre-trained and user-built—with Apple’s CoreML framework. Source code examples are provided for readers to download and use in their own projects. This book helps readers:
Understand the theoretical concepts and practical applications of machine learning used in predictive data analytics Build, deploy, and maintain ML systems for tasks such as model validation, optimization, scalability, and real-time streaming Develop skills in data acquisition and modeling, classification, and regression. Compare traditional vs. ML approaches, and machine learning on handsets vs. machine learning as a service (MLaaS) Implement decision tree based models, an instance-based machine learning system, and integrate Scikit-learn & Keras models with CoreMLMachine Learning for iOS Developers is a must-have resource software engineers and mobile solutions architects wishing to learn ML concepts and implement machine learning on iOS Apps.
465 kr
Läs direkt efter köp
Harness the power of Apple iOS machine learning (ML) capabilities and learn the concepts and techniques necessary to be a successful Apple iOS machine learning practitioner!
Machine earning (ML) is the science of getting computers to act without being explicitly programmed. A branch of Artificial Intelligence (AI), machine learning techniques offer ways to identify trends, forecast behavior, and make recommendations. The Apple iOS Software Development Kit (SDK) allows developers to integrate ML services, such as speech recognition and language translation, into mobile devices, most of which can be used in multi-cloud settings. Focusing on Apple’s ML services, Machine Learning for iOS Developers is an up-to-date introduction to the field, instructing readers to implement machine learning in iOS applications.
Assuming no prior experience with machine learning, this reader-friendly guide offers expert instruction and practical examples of ML integration in iOS. Organized into two sections, the book’s clearly-written chapters first cover fundamental ML concepts, the different types of ML systems, their practical uses, and the potential challenges of ML solutions. The second section teaches readers to use models—both pre-trained and user-built—with Apple’s CoreML framework. Source code examples are provided for readers to download and use in their own projects. This book helps readers:
Understand the theoretical concepts and practical applications of machine learning used in predictive data analytics Build, deploy, and maintain ML systems for tasks such as model validation, optimization, scalability, and real-time streaming Develop skills in data acquisition and modeling, classification, and regression. Compare traditional vs. ML approaches, and machine learning on handsets vs. machine learning as a service (MLaaS) Implement decision tree based models, an instance-based machine learning system, and integrate Scikit-learn & Keras models with CoreMLMachine Learning for iOS Developers is a must-have resource software engineers and mobile solutions architects wishing to learn ML concepts and implement machine learning on iOS Apps.
670 kr
Skickas inom 10-15 vardagar
896 kr
Läs direkt efter köp
767 kr
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1 059 kr
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615 kr
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896 kr
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463 kr
Skickas inom 10-15 vardagar
652 kr
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565 kr
Skickas inom 5-8 vardagar
272 kr
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33 kr
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363 kr
Skickas inom 5-8 vardagar
363 kr
Skickas inom 5-8 vardagar
363 kr
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351 kr
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363 kr
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495 kr
Skickas inom 5-8 vardagar
495 kr
Skickas inom 5-8 vardagar
495 kr
Skickas inom 5-8 vardagar