Practical Deep Learning for Cloud, Mobile, and Edge Real-World AI & Computer-Vision Projects Using Python, Keras & TensorFlow
暫譯: 雲端、行動裝置與邊緣運算的實用深度學習

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)

無論您是希望進入人工智慧領域的軟體工程師、資深數據科學家，還是有著簡單夢想的愛好者，想要製作下一個病毒式的 AI 應用程式，您可能會想 我該從哪裡開始？ 本指南將以逐步的方式教您如何使用深度神經網絡為雲端和行動裝置構建實用應用程式，並採取實作的方式。

依靠多年將深度學習研究轉化為獲獎應用程式的行業經驗，Anirudh Koul、Siddha Ganju 和 Meher Kasam 將引導您將一個想法轉變為人們可以在現實世界中使用的東西。使用 Keras、TensorFlow、CoreML、TensorFlow Lite 和 MLKit 訓練、優化和部署計算機視覺模型，迅速將您的系統從零提升到生產級品質。


  • 使用 Raspberry Pi、Jetson Nano 和 Google Coral 為桌面、雲端、智慧型手機、瀏覽器和智能機器人開發 AI 應用程式

  • 實時執行物體分類、檢測和分割

  • 通過構建示例學習，例如矽谷的「Not Hotdog」應用程式、圖像搜索引擎和 Snapchat 濾鏡

  • 在視頻遊戲環境中訓練自動駕駛汽車，然後構建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 with pix2pix）和人體姿勢估計（PoseNet）從草圖生成照片

  • 發現 50 多個實用技巧，用於數據收集、模型互操作性、除錯、避免偏見以及擴展到數百萬用戶

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 與研究部門負責人，之前曾在 Microsoft AI 與研究部門工作，創立了 Seeing AI——這是一款全球盲人社群使用的事實上標準應用程式。該應用程式的功能已推送至約十億人，他擁有超過十年的以生產為導向的應用研究經驗，專注於 petabyte 級數據集。他一直在利用 AI 轉化增強現實、機器人技術、語音、效率等領域的想法為現實，並為殘障人士建立工具。他的工作被 IEEE 稱為「改變生活」，並獲得 CES、FCC、坎城獅子獎、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，受到包括賈斯廷·特魯多和特蕾莎·梅等世界領袖的讚賞。

Siddha Ganju 是 Nvidia 的自駕車架構師，曾被《福布斯》列入 30 位 30 歲以下精英名單。她之前在 Deep Vision 工作，為資源受限的邊緣設備開發深度學習模型。她是卡內基梅隆大學的畢業生，之前的工作範圍從視覺問答到生成對抗網絡，並從 CERN 的 petabyte 級數據中獲取見解，並在包括 CVPR 和 NeurIPS 等頂級會議上發表。作為 AI 領域的專家，她還指導 NASA 的團隊，並在幾個國際技術競賽中擔任評審委員。

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，他為多款應用程式推出功能，從 Square 的銷售點到 Bing 應用程式。他是 Microsoft Seeing AI 應用程式的行動開發負責人，該應用程式獲得了來自行動世界大會、CES、FCC、美國盲人協會等的廣泛認可和獎項。他是一位熱愛駭客的開發者，擅長快速原型設計，贏得了近二十場黑客馬拉松，並將其轉化為廣泛使用產品中的功能。他還擔任包括全球行動獎、愛迪生獎等國際競賽的評審。

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