Productionizing AI: How to Deliver AI B2B Solutions with Cloud and Python
暫譯: 將AI產品化：如何利用雲端與Python交付AI B2B解決方案

Walsh, Barry

Productionizing AI: How to Deliver AI B2B Solutions with Cloud and Python

相關主題

商品描述

This book is a guide to productionizing AI solutions using best-of-breed cloud services with workarounds to lower costs. Supplemented with step-by-step instructions covering data import through wrangling to partitioning and modeling through to inference and deployment, and augmented with plenty of Python code samples, the book has been written to accelerate the process of moving from script or notebook to app.

From an initial look at the context and ecosystem of AI solutions today, the book drills down from high-level business needs into best practices, working with stakeholders, and agile team collaboration. From there you'll explore data pipeline orchestration, machine and deep learning, including working with and finding shortcuts using artificial neural networks such as AutoML and AutoAI. You'll also learn about the increasing use of NoLo UIs through AI application development, industry case studies, and finally a practical guide to deploying containerized AI solutions.

The book is intended for those whose role demands overcoming budgetary barriers or constraints in accessing cloud credits to undertake the often difficult process of developing and deploying an AI solution.

What You Will Learn

  • Develop and deliver production-grade AI in one month
  • Deploy AI solutions at a low cost
  • Work around Big Tech dominance and develop MVPs on the cheap
  • Create demo-ready solutions without overly complex python scripts/notebooks

Who this book is for:

Data scientists and AI consultants with programming skills in Python and driven to succeed in AI.

商品描述(中文翻譯)

這本書是一本關於如何使用最佳雲端服務來生產化人工智慧解決方案的指南，並提供降低成本的替代方案。書中包含逐步指導，涵蓋從數據導入到數據清理，再到分區和建模，直到推論和部署的過程，並附有大量的 Python 代碼範例，旨在加速從腳本或筆記本轉換為應用程式的過程。

本書首先探討當前人工智慧解決方案的背景和生態系統，然後深入探討高層次的商業需求、最佳實踐、與利益相關者的合作以及敏捷團隊協作。接著，您將探索數據管道的編排、機器學習和深度學習，包括使用人工神經網絡（如 AutoML 和 AutoAI）來尋找捷徑。您還將了解在人工智慧應用開發中日益增長的 NoLo 用戶介面的使用、行業案例研究，最後是關於部署容器化人工智慧解決方案的實用指南。

本書適合那些需要克服預算障礙或限制以獲取雲端信用，進而進行開發和部署人工智慧解決方案的讀者。

您將學到的內容


  • 在一個月內開發並交付生產級的人工智慧

  • 以低成本部署人工智慧解決方案

  • 繞過大型科技公司的主導地位，廉價開發 MVP

  • 創建可演示的解決方案，而不需要過於複雜的 Python 腳本/筆記本

本書適合的對象：
具備 Python 編程技能並渴望在人工智慧領域取得成功的數據科學家和人工智慧顧問。

作者簡介

Barry Walsh is a software-delivery consultant and AI trainer at Pairview with a background in exploiting complex business data to optimize and de-risk energy assets at ABB/Ventyx, Infosys, E.ON, Centrica, and his own start-up ce.tech. He has a proven track record of providing consultancy services in Data Science, BI, and Business Analysis to businesses in Energy, IT, FinTech, Telco, Retail, and Healthcare, Barry has been at the apex of analytics and AI solutions delivery for 20 years. Besides being passionate about Enterprise AI, Barry spends his spare time with his wife and 8-year-old son, playing the piano, riding long bike rides (and a marathon on a broken toe this year), eating out whenever possible or getting his daily coffee fix.

作者簡介(中文翻譯)

巴里·沃爾什是Pairview的軟體交付顧問和人工智慧訓練師，擁有利用複雜商業數據來優化和降低ABB/Ventyx、Infosys、E.ON、Centrica及他自己的創業公司ce.tech的能源資產風險的背景。他在數據科學、商業智慧（BI）和商業分析方面為能源、資訊科技、金融科技、電信、零售和醫療保健等行業的企業提供顧問服務，擁有良好的業績記錄。巴里在分析和人工智慧解決方案交付方面已有20年的經驗。除了對企業人工智慧充滿熱情外，巴里還會在空閒時間與妻子和8歲的兒子一起彈鋼琴、騎長途自行車（今年因為腳趾受傷參加馬拉松），盡可能外出用餐或享受每日的咖啡。

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