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Titlebook: Develop Intelligent iOS Apps with Swift; Understand Texts, Cl ?zgür Sahin Book 2021 ?zg?r Sahin 2021 Text Classification.Natural Language P

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發(fā)表于 2025-3-21 17:07:55 | 只看該作者 |倒序瀏覽 |閱讀模式
書目名稱Develop Intelligent iOS Apps with Swift
副標題Understand Texts, Cl
編輯?zgür Sahin
視頻videohttp://file.papertrans.cn/270/269671/269671.mp4
概述Build literate, language understanding apps.Train custom machine learning models for iOS development.Develop intelligent apps that read text and answer questions
圖書封面Titlebook: Develop Intelligent iOS Apps with Swift; Understand Texts, Cl ?zgür Sahin Book 2021 ?zg?r Sahin 2021 Text Classification.Natural Language P
描述.Build smart apps capable of analyzing language and performing language-specific tasks, such as script identification, tokenization, lemmatization, part-of-speech tagging, and?named entity recognition. This book will get you started in the world of building literate, language understanding apps. Cutting edge ML tools from Apple like CreateML, CoreML, and TuriCreate will become natural parts of your development toolbox as you construct intelligent, text-based apps.. .You‘ll explore a wide range of text processing topics, including reprocessing text, training custom machine learning models, converting state-of-the-art NLP models to CoreML from Keras, evaluating models, and deploying models to your iOS apps. You’ll develop sample apps to learn by doing. These include apps with functions for detecting spam SMS, extracting text with OCR, generating sentences with AI, categorizing the sentiment of text, developing intelligent apps that read text and answers questions, converting speech to text, detecting parts of speech, and identifying people, places, and organizations in text...Smart app development involves mainly teaching apps to learn and understand input without explicit prompts fr
出版日期Book 2021
關鍵詞Text Classification; Natural Language Processing; NLP; Swift; iOS; iPhone; iPad; Sentiment analysis; CreateM
版次1
doihttps://doi.org/10.1007/978-1-4842-6421-8
isbn_softcover978-1-4842-6420-1
isbn_ebook978-1-4842-6421-8
copyright?zg?r Sahin 2021
The information of publication is updating

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沙發(fā)
發(fā)表于 2025-3-21 22:19:05 | 只看該作者
Mthuli Ncube,Nombulelo Gumata,Eliphas Ndou, you will be introduced to natural language processing (NLP). You will learn how we make text data understandable for computers via NLP. Even if you have zero knowledge about these disciplines, you will gain the intuition behind after reading this chapter.
板凳
發(fā)表于 2025-3-22 02:23:58 | 只看該作者
Mthuli Ncube,Nombulelo Gumata,Eliphas Ndouks and tools introduced in this chapter are Vision, VisionKit, Natural Language, Speech, Core ML, Create ML, and Turi Create. We will learn what capabilities these tools have to offer and what kind of applications we can build using them.
地板
發(fā)表于 2025-3-22 08:38:31 | 只看該作者
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發(fā)表于 2025-3-22 11:30:49 | 只看該作者
Louise Warwick-Booth,Ruth Cross,Susan Coanwe will learn how to integrate Keras models into our application. In this chapter, we will convert the Keras model to Core ML format using the coremltools library. A sample text classification application will be developed to learn by doing. You will also learn to use the Google Colab service which is an online and free Python environment.
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發(fā)表于 2025-3-22 16:52:10 | 只看該作者
7#
發(fā)表于 2025-3-22 18:04:11 | 只看該作者
Introduction to Apple ML Tools,ks and tools introduced in this chapter are Vision, VisionKit, Natural Language, Speech, Core ML, Create ML, and Turi Create. We will learn what capabilities these tools have to offer and what kind of applications we can build using them.
8#
發(fā)表于 2025-3-22 23:10:44 | 只看該作者
Text Generation, best text generation models (GPT-2) and build an iOS application using this model. Our application will use built-in OCR capabilities to capture text from camera and generate text based on scanned sentences.
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發(fā)表于 2025-3-23 02:24:00 | 只看該作者
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發(fā)表于 2025-3-23 07:03:39 | 只看該作者
Mthuli Ncube,Nombulelo Gumata,Eliphas Ndoug, classify GitHub issues, find complaints in App Store reviews, or detect the language of a text. In this chapter, we will learn how to use Create ML and Turi Create to create text classification applications. We will learn by doing example apps. We will develop a spam SMS classifier app with Create ML first and then Turi Create.
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