Practical Automated Machine Learning on Azure Using Azure Machine Learning to Quickly Build AI Solutions

Mukunthu, Deepak, Shah, Parashar, Tok, Wee Hyong

Practical Automated Machine Learning on Azure

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商品描述

Develop smart applications without spending days and weeks building machine-learning models. With this practical book, you'll learn how to apply automated machine learning (AutoML), a process that uses machine learning to help people build machine learning models. Deepak Mukunthu, Parashar Shah, and Wee Hyong Tok provide a mix of technical depth, hands-on examples, and case studies that show how customers are solving real-world problems with this technology.

Building machine-learning models is an iterative and time-consuming process. Even those who know how to create ML models may be limited in how much they can explore. Once you complete this book, you'll understand how to apply AutoML to your data right away.

  • Learn how companies in different industries are benefiting from AutoML
  • Get started with AutoML using Azure
  • Explore aspects such as algorithm selection, auto featurization, and hyperparameter tuning
  • Understand how data analysts, BI professions, developers can use AutoML in their familiar tools and experiences
  • Learn how to get started using AutoML for use cases including classification, regression, and forecasting.

商品描述(中文翻譯)

開發智能應用程式，無需花費數天或數週建立機器學習模型。這本實用書籍將教導您如何應用自動機器學習（AutoML），這是一個利用機器學習幫助人們建立機器學習模型的過程。Deepak Mukunthu、Parashar Shah和Wee Hyong Tok提供了技術深度、實際示例和案例研究的結合，展示了客戶如何使用這項技術解決現實世界的問題。

建立機器學習模型是一個迭代且耗時的過程。即使是那些知道如何創建機器學習模型的人，也可能受限於他們能夠探索的範圍。閱讀完這本書後，您將立即了解如何應用AutoML到您的數據中。

本書內容包括：
- 學習不同行業的公司如何從AutoML中受益
- 使用Azure開始使用AutoML
- 探索算法選擇、自動特徵提取和超參數調整等方面
- 了解數據分析師、商業智能專業人員和開發人員如何在他們熟悉的工具和經驗中使用AutoML
- 學習如何開始使用AutoML進行分類、回歸和預測等用例。

作者簡介

Deepak Mukunthu is a product leader with 16+ years of experience. With his experience in Big data, Analytics and AI, Deepak has played instrumental leadership roles in transforming organizations and teams become data driven and adopt machine learning. He brings a good mix of thought leadership, customer understanding and innovation to design and deliver compelling products that resonate well with customers. In his current role of Principal Program Manager on Automated ML in Azure AI platform group at Microsoft, Deepak drives product strategy and roadmap for Automated ML with the goal of accelerating AI for data scientists and democratizing AI for other personas interested in machine learning. In addition to shaping the product direction, he also plays an instrumental role in helping customers adopt Automated ML for their business-critical scenarios. Prior to joining Microsoft, Deepak worked at Trilogy where he played multiple roles - Consultant, Business development, Program manager, Engineering manager - successfully leading distributed teams across the globe and managing technical integration of acquisitions.

Parashar Shah works for Microsoft as a Data Scientist, Senior Program/Product Manager in Azure Machine Learning platform team within the Cloud + AI Platform organization. His first book, Hands-On Machine Learning with Azure: Build powerful models with cognitive machine learning and artificial intelligence, was published in Nov 2018. Prior to joining Microsoft, he worked for Alcatel-Lucent/Nokia Networks/Bell Labs where he helped global telecom operators (across North America, Europe, Middle East and APAC) as a solution architect/product manager. Parashar has a MBA from Indian Institute of Management Bangalore & B.E. (E.C.) from Nirma Institute of Technology, Ahmedabad. He has filed for 5 patents (in published state), he loves to work on new technologies and ideas. Parashar's experience and interests span across Artificial Intelligence, Machine Learning, Big Data, Data Science, Blockchain, Virtual Reality, Internet of Things (IoT), Advanced Analytics, Mobile application development, Wireless Technologies & Device Management.

Wee Hyong Tok is part of the AzureCAT team at Microsoft. He has extensive leadership experience leading multi-disciplinary team of engineers and data scientists, working on cutting-edge AI capabilities that are infused into products and services. He is a tech visionary with a background in product management, machine learning/deep learning and working on complex engagements with customers. Over the years, he has demonstrated that his early thought-leadership white papers on tech trends have become reality, and deeply integrated into many products. His ability to strategize, and turn strategy to execution, and hunting for customer adoption has enabled many projects that he works on to be successful. He is continuously pushing the boundaries of products for machine learning and deep learning. His team works extensively with deep learning frameworks, ranging from TensorFlow, CNTK, Keras, and PyTorch. 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 super powers to lead and define the strategy for high-performing Data and AI innovation teams. Throughout his career, he has been a trusted advisor to the C-suite, from Fortune 500 companies to startups.

作者簡介(中文翻譯)

Deepak Mukunthu是一位擁有16年以上經驗的產品領導者。憑藉他在大數據、分析和人工智能方面的經驗，Deepak在轉型組織和團隊成為數據驅動並采用機器學習方面發揮了重要的領導作用。他結合了思想領導力、客戶理解和創新，設計並交付與客戶高度共鳴的引人入勝的產品。在他目前在微軟的Azure AI平台團隊擔任的首席計劃經理的職位上，Deepak推動自動化機器學習的產品戰略和路線圖，旨在加速數據科學家的人工智能應用，並將人工智能民主化，讓其他對機器學習感興趣的人也能參與其中。除了塑造產品方向外，他還在幫助客戶應用自動化機器學習解決其業務關鍵場景方面發揮了重要作用。在加入微軟之前，Deepak在Trilogy工作，擔任多個角色 - 顧問、業務拓展、計劃經理、工程經理 - 成功領導全球分佈的團隊，並管理收購的技術整合。

Parashar Shah在微軟擔任資料科學家、高級計劃/產品經理，隸屬於Cloud + AI平台組織的Azure Machine Learning平台團隊。他的第一本書《Hands-On Machine Learning with Azure: Build powerful models with cognitive machine learning and artificial intelligence》於2018年11月出版。在加入微軟之前，他在Alcatel-Lucent/Nokia Networks/Bell Labs工作，擔任解決方案架構師/產品經理，幫助全球電信運營商（包括北美、歐洲、中東和亞太地區）解決方案。Parashar擁有印度管理學院班加羅爾分校的MBA學位和Nirma技術學院的B.E.（E.C.）學位。他已申請了5項專利（已公開發表），熱衷於研究新技術和新思想。Parashar的經驗和興趣涵蓋人工智能、機器學習、大數據、數據科學、區塊鏈、虛擬現實、物聯網（IoT）、高級分析、移動應用開發、無線技術和設備管理。

Wee Hyong Tok是微軟AzureCAT團隊的一員。他擁有豐富的領導經驗，領導著由工程師和數據科學家組成的多學科團隊，致力於將尖端人工智能能力融入產品和服務中。他是一位技術願景家，具有產品管理、機器學習/深度學習和與客戶合作的複雜項目的背景。多年來，他展示了他早期的技術趨勢思想領導力白皮書已成為現實，並深入融入許多產品中。他制定策略、將策略轉化為執行，並尋求客戶採用的能力使他參與的許多項目取得成功。他不斷推動機器學習和深度學習產品的界限。他的團隊廣泛使用深度學習框架，包括TensorFlow、CNTK、Keras和PyTorch。Wee Hyong在職業生涯中擔任過多種角色 - 開發人員、計劃/產品經理、數據科學家、研究員和策略家，他的經驗範圍使他具有領導和定義高效數據和人工智能創新團隊的策略的獨特超能力。在他的職業生涯中，他一直是C級高管的值得信賴的顧問，從財富500強公司到初創企業。

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