Practical Deep Learning for Cloud, Mobile, and Edge Real-World AI & Computer-Vision Projects Using Python, Keras & TensorFlow (雲端、行動與邊緣的實用深度學習)

Koul, Anirudh, Ganju, Siddha, Kasam, Meher

Practical Deep Learning for Cloud, Mobile, and Edge

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商品描述

Whether you're a software engineer aspiring to enter the world of artificial intelligence, a veteran data scientist, or a hobbyist with a simple dream of making the next viral AI app, you might have wondered where do I begin? This step-by-step guide teaches you how to build practical applications using deep neural networks for the cloud and mobile using a hands-on approach.

Relying on years of industry experience transforming deep learning research into award-winning applications, Anirudh Koul, Siddha Ganju, and Meher Kasam guide you through the process of converting an idea into something that people can use in the real world. Train, optimize, and deploy computer vision models with Keras, TensorFlow, CoreML, TensorFlow Lite, and MLKit, rapidly taking your system from zero to production quality.

  • Develop AI applications for the desktop, cloud, smartphones, browser, and smart robots using Raspberry Pi, Jetson Nano, and Google Coral
  • Perform Object Classification, Detection, Segmentation in real-time
  • Learn by building examples such as Silicon Valley's "Not Hotdog" app, image search engines, and Snapchat filters
  • Train an autonomous car in a video game environment and then build a real mini version
  • Use transfer learning to train models in minutes
  • Generate photos from sketches in your browser with Generative Adversarial Networks (GANs with pix2pix), and Body Pose Estimation (PoseNet)
  • Discover 50+ practical tips for data collection, model interoperability, debugging, avoiding bias, and scaling to millions of users

商品描述(中文翻譯)

無論你是一位渴望進入人工智慧領域的軟體工程師、一位經驗豐富的資料科學家，或者只是一位希望打造下一個病毒式人工智慧應用程式的愛好者，你可能會想知道「我應該從哪裡開始？」這本逐步指南將以實作為主，教你如何使用深度神經網路在雲端和行動裝置上建立實用的應用程式。

作者 Anirudh Koul、Siddha Ganju 和 Meher Kasam 憑藉多年的產業經驗，將深度學習研究轉化為屢獲殊榮的應用程式，引導你將想法轉化為現實世界中可供人們使用的東西。使用 Keras、TensorFlow、CoreML、TensorFlow Lite 和 MLKit，訓練、優化和部署電腦視覺模型，快速將你的系統從零建立到生產品質。

本書內容包括：

- 使用 Raspberry Pi、Jetson Nano 和 Google Coral 開發桌面、雲端、智慧手機、瀏覽器和智能機器人的人工智慧應用程式
- 實時進行物件分類、偵測和分割
- 通過構建實例，如矽谷的「Not Hotdog」應用程式、圖像搜索引擎和 Snapchat 濾鏡來學習
- 在視頻遊戲環境中訓練自駕車，然後建立一個真實的迷你版本
- 使用遷移學習在幾分鐘內訓練模型
- 在瀏覽器中使用生成對抗網絡（GANs）和姿勢估計（PoseNet）從草圖生成照片
- 發現50多個實用的技巧，包括數據收集、模型互操作性、調試、避免偏見和擴展到數百萬用戶的方法。

作者簡介

Anirudh Koul is the Head of AI & Research at Aira, and was previously at Microsoft AI & Research where he founded Seeing AI - the defacto app used by the blind community worldwide. With features shipped to about a billion people, he brings over a decade of production-oriented applied research experience on petabyte-scale datasets. He has been transforming ideas to reality using AI for Augmented Reality, Robotics, Speech, Productivity as well as building tools for people with disabilities. His work, which the IEEE has called 'life changing', has been honored by CES, FCC, Cannes Lions, American Council of the Blind, showcased at events by UN, White House, House of Lords, World Economic Forum, TEDx, on Netflix, National Geographic, and applauded by world leaders including Justin Trudeau and Theresa May.

Siddha Ganju, who Forbes featured in their 30 under 30 list, is a Self-Driving Architect at Nvidia. Previously at Deep Vision, she developed deep learning models for resource constraint edge devices. A graduate from Carnegie Mellon University, her prior work ranges from Visual Question Answering to Generative Adversarial Networks to gathering insights from CERN's petabyte-scale data and has been published at top-tier conferences including CVPR and NeurIPS. Serving as an AI domain expert, she has also been guiding teams at NASA as well as featured as a jury member in several international tech competitions.

Meher is a seasoned software developer with apps used by tens of millions of users every day. Currently at Square, and previously at Microsoft, he shipped features for a range of apps, from Square's Point of Sale to the Bing app. He was the mobile development lead for Microsoft's Seeing AI app, which has received widespread recognition and awards from Mobile World Congress, CES, FCC, American Council of the Blind to name a few. A hacker at heart with a flair for fast prototyping, he has won close to two dozen hackathons and converted them to features shipped in widely-used products. He also serves as a judge of international competitions including Global Mobile Awards, Edison Awards.

作者簡介(中文翻譯)

Anirudh Koul是Aira的AI和研究主管，曾在Microsoft AI和研究部門工作，創立了Seeing AI - 這是全球盲人社區使用的事實上的應用程式。他在處理PB級數據集的生產導向應用研究方面擁有超過十年的經驗，並為約十億人提供了功能。他利用AI將想法轉化為現實，應用於擴增實境、機器人技術、語音、生產力以及為殘障人士建立工具。他的工作被IEEE稱為“改變生活”，並獲得了CES、FCC、坎城獅子會、美國盲人協會的榮譽，並在聯合國、白宮、上議院、世界經濟論壇、TEDx、Netflix、國家地理等活動中展示，並受到包括賈斯汀·特魯多和特蕾莎·梅在內的世界領導人的讚揚。

Siddha Ganju是Nvidia的自駕車架構師，被福布斯評為30位30歲以下的傑出人才。之前在Deep Vision工作，為資源受限的邊緣設備開發深度學習模型。畢業於卡內基梅隆大學，她的先前工作涵蓋了視覺問答、生成對抗網絡以及從CERN的PB級數據中獲取洞察力，並在包括CVPR和NeurIPS在內的頂級會議上發表。作為AI領域的專家，她還指導NASA的團隊並擔任多個國際技術競賽的評委。

Meher是一位經驗豐富的軟體開發人員，每天有數千萬用戶使用他的應用程式。目前在Square工作，之前在Microsoft工作，為多個應用程式提供功能，從Square的銷售點到Bing應用程式。他是Microsoft Seeing AI應用程式的移動開發負責人，該應用程式獲得了Mobile World Congress、CES、FCC、美國盲人協會等的廣泛認可和獎項。他是一位心懷黑客精神並擅長快速原型設計的人，贏得了近二十個黑客松比賽，並將其轉化為廣泛使用的產品功能。他還擔任國際競賽的評委，包括全球移動獎和愛迪生獎。

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