Practical Weak Supervision: Doing More with Less Data
暫譯: 實用的弱監督：用更少的數據做更多的事

Tok, Wee Hyong, Bahree, Amit, Filipi, Senja

Practical Weak Supervision: Doing More with Less Data
  • 出版商: O'Reilly
  • 出版日期: 2021-11-09
  • 定價: $2,800
  • 售價: 8.8 折 $2,464 (限時優惠至 2025-03-31)
  • 語言: 英文
  • 頁數: 192
  • 裝訂: Quality Paper - also called trade paper
  • ISBN: 1492077062
  • ISBN-13: 9781492077060
  • 相關分類: 人工智慧、大數據 Big-data、Machine Learning

    • 立即出貨 (庫存 < 4)

商品描述

Most data scientists and engineers today rely on quality labeled data to train machine learning models. But building a training set manually is time-consuming and expensive, leaving many companies with unfinished ML projects. There's a more practical approach. In this book, Wee Hyong Tok, Amit Bahree, and Senja Filipi show you how to create products using weakly supervised learning models.

You'll learn how to build natural language processing and computer vision projects using weakly labeled datasets from Snorkel, a spin-off from the Stanford AI Lab. Because so many companies have pursued ML projects that never go beyond their labs, this book also provides a guide on how to ship the deep learning models you build.

  • Get up to speed on the field of weak supervision, including ways to use it as part of the data science process
  • Use Snorkel AI for weak supervision and data programming
  • Get code examples for using Snorkel to label text and image datasets
  • Use a weakly labeled dataset for text and image classification
  • Learn practical considerations for using Snorkel with large datasets and using Spark clusters to scale labeling

商品描述(中文翻譯)

大多數數據科學家和工程師今天依賴高品質的標記數據來訓練機器學習模型。然而，手動建立訓練集既耗時又昂貴，導致許多公司無法完成機器學習專案。本書提供了一種更實用的方法。在這本書中，Wee Hyong Tok、Amit Bahree 和 Senja Filipi 將向您展示如何使用弱監督學習模型來創建產品。

您將學習如何使用來自斯坦福人工智慧實驗室衍生的 Snorkel 的弱標記數據集來構建自然語言處理和計算機視覺專案。由於許多公司追求的機器學習專案從未超出實驗室，本書還提供了如何部署您所構建的深度學習模型的指南。

- 了解弱監督領域的最新進展，包括如何將其作為數據科學過程的一部分
- 使用 Snorkel AI 進行弱監督和數據編程
- 獲取使用 Snorkel 標記文本和圖像數據集的代碼範例
- 使用弱標記數據集進行文本和圖像分類
- 學習在使用大型數據集和使用 Spark 集群進行標記擴展時的實用考量

作者簡介

is a product and AI leader with a background in product management, machine learning/deep learning, research, and working on complex technical engagements with customers. Over the years, he has demonstrated that the early thought-leadership whitepapers he wrote on tech trends have become reality, and are deeply integrated into many products. Wee Hyong has worn many hats in his career--developer, program/product manager, data scientist, researcher, and strategist, and his range of experience has given him unique superpowers to lead and define the strategy for high-performing data and AI innovation teams.

作者簡介(中文翻譯)

是一位產品和人工智慧領導者，擁有產品管理、機器學習/深度學習、研究的背景，並在與客戶進行複雜技術合作方面有豐富的經驗。多年來，他所撰寫的有關技術趨勢的早期思想領導白皮書已經變成現實，並深度整合到許多產品中。Wee Hyong 在他的職業生涯中擔任過多種角色——開發者、計畫/產品經理、數據科學家、研究員和策略家，他的廣泛經驗賦予了他獨特的超能力，能夠引領並定義高效能數據和人工智慧創新團隊的策略。

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