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自動(dòng)機(jī)器學(xué)習(xí)

自動(dòng)機(jī)器學(xué)習(xí)

出版社：電子工業(yè)出版社出版時(shí)間：2023-06-01
開本： 其他 頁數(shù)： 188
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自動(dòng)機(jī)器學(xué)習(xí) 版權(quán)信息

自動(dòng)機(jī)器學(xué)習(xí) 內(nèi)容簡介

本書重點(diǎn)講解基于云平臺(tái)的超參數(shù)優(yōu)化、神經(jīng)構(gòu)架搜索以及算法選擇等內(nèi)容，是自動(dòng)機(jī)器學(xué)習(xí)的基本任務(wù)。介紹了基于三個(gè)主要云服務(wù)提供商（包括 Microsoft Azure、Amazon Web Services (AWS) 和 Google Cloud Platform）進(jìn)行 AutoML，同時(shí)部署 ML 模型和管道，具有較強(qiáng)的實(shí)用性。在應(yīng)用場(chǎng)景中評(píng)估 AutoML 方面，例如算法選擇、自動(dòng)特征化和超參數(shù)調(diào)整，并區(qū)分云和 OSS 產(chǎn)品等。本書適用于從事機(jī)器學(xué)習(xí)或人工智能方向的數(shù)據(jù)科學(xué)家或工程師學(xué)習(xí)，也適合學(xué)生或行業(yè)初學(xué)者進(jìn)行入門學(xué)習(xí)實(shí)踐。

自動(dòng)機(jī)器學(xué)習(xí) 目錄

第 1 章 走進(jìn)自動(dòng)機(jī)器學(xué)習(xí)··············································································.1
1.1 機(jī)器學(xué)習(xí)開發(fā)生命周期 ·······································································.1
1.2 自動(dòng)機(jī)器學(xué)習(xí)簡介 ·············································································.2
1.3 自動(dòng)機(jī)器學(xué)習(xí)的工作原理 ····································································.3
1.4 數(shù)據(jù)科學(xué)的大眾化 ·············································································.5
1.5 揭穿自動(dòng)機(jī)器學(xué)習(xí)的迷思 ····································································.5
1.6 自動(dòng)機(jī)器學(xué)習(xí)生態(tài)系統(tǒng) ·······································································.6
1.7 小結(jié) ·······························································································11
第 2 章 自動(dòng)機(jī)器學(xué)習(xí)、算法和技術(shù)··································································12
2.1 自動(dòng)機(jī)器學(xué)習(xí)概述 ·············································································12
2.2 自動(dòng)特征工程 ···················································································15
2.3 超參數(shù)優(yōu)化 ······················································································16
2.4 神經(jīng)架構(gòu)搜索 ···················································································18
2.5 小結(jié) ·······························································································19
第 3 章 使用開源工具和庫進(jìn)行自動(dòng)機(jī)器學(xué)習(xí)······················································20
3.1 技術(shù)要求 ·························································································20
3.2 自動(dòng)機(jī)器學(xué)習(xí)的開源生態(tài)系統(tǒng) ······························································21
3.3 TPOT······························································································22
3.4 Featuretools ······················································································29
3.5 Microsoft NNI ···················································································32
3.6 auto-sklearn ······················································································38
3.7 AutoKeras ························································································41
3.8 Ludwig ····························································································44
3.9 AutoGluon························································································44
3.10 小結(jié)······························································································44
第 4 章 Azure Machine Learning········································································45
4.1 Azure Machine Learning 入門 ································································45
4.2 Azure Machine Learning 棧 ···································································46
4.3 Azure Machine Learning 服務(wù) ································································50
4.4 使用 Azure Machine Learning 建模 ·························································56
4.5 使用 Azure Machine Learning 部署和測(cè)試模型 ··········································68
4.6 小結(jié) ·······························································································70
第 5 章 使用 Azure 進(jìn)行自動(dòng)機(jī)器學(xué)習(xí) ·······························································71
5.1 Azure 中的自動(dòng)機(jī)器學(xué)習(xí) ·····································································71
5.2 使用自動(dòng)機(jī)器學(xué)習(xí)進(jìn)行時(shí)間序列預(yù)測(cè) ·····················································85
5.3 小結(jié) ·······························································································97
第 6 章 使用 AWS 進(jìn)行機(jī)器學(xué)習(xí) ······································································98
6.1 AWS 環(huán)境中的機(jī)器學(xué)習(xí)······································································98
6.2 開始使用 AWS ···············································································.101
6.3 使用 Amazon SageMaker Autopilot·······················································.109
6.4 使用 Amazon SageMaker JumpStart······················································.111
6.5 小結(jié) ····························································································.111
第 7 章 使用 Amazon SageMaker Autopilot 進(jìn)行自動(dòng)機(jī)器學(xué)習(xí)······························.113
7.1 技術(shù)要求 ······················································································.113
7.2 創(chuàng)建 Amazon SageMaker Autopilot
展開全部

自動(dòng)機(jī)器學(xué)習(xí) 作者簡介

Adnan Masood，工程師、教師、研究員，在金融技術(shù)和開發(fā)大型系統(tǒng)方面擁有超過20年的全球經(jīng)驗(yàn)。被微軟評(píng)為微軟區(qū)域總監(jiān)和微軟人工智能領(lǐng)域最有價(jià)值專家。擔(dān)任UST-Global的首席人工智能官和首席架構(gòu)師，負(fù)責(zé)公司在認(rèn)知計(jì)算、人工智能、機(jī)器學(xué)習(xí)和學(xué)術(shù)關(guān)系方面的整體戰(zhàn)略。與斯坦福人工智能實(shí)驗(yàn)室、麻省理工學(xué)院CSAIL合作，領(lǐng)導(dǎo)數(shù)據(jù)科學(xué)家和工程師團(tuán)隊(duì)構(gòu)建人工智能解決方案，以產(chǎn)生影響一系列業(yè)務(wù)、產(chǎn)品和計(jì)劃的商業(yè)價(jià)值和見解。在帕克大學(xué)教授數(shù)據(jù)科學(xué)，并在加州大學(xué)圣地亞哥分校教授Windows WCF課程。擔(dān)任《財(cái)富》500強(qiáng)企業(yè)和初創(chuàng)企業(yè)顧問。曾出版亞馬遜編程語言暢銷書《f#函數(shù)編程》。
Adnan Masood，工程師、教師、研究員，在金融技術(shù)和開發(fā)大型系統(tǒng)方面擁有超過20年的全球經(jīng)驗(yàn)。被微軟評(píng)為微軟區(qū)域總監(jiān)和微軟人工智能領(lǐng)域最有價(jià)值專家。擔(dān)任UST-Global的首席人工智能官和首席架構(gòu)師，負(fù)責(zé)公司在認(rèn)知計(jì)算、人工智能、機(jī)器學(xué)習(xí)和學(xué)術(shù)關(guān)系方面的整體戰(zhàn)略。與斯坦福人工智能實(shí)驗(yàn)室、麻省理工學(xué)院CSAIL合作，領(lǐng)導(dǎo)數(shù)據(jù)科學(xué)家和工程師團(tuán)隊(duì)構(gòu)建人工智能解決方案，以產(chǎn)生影響一系列業(yè)務(wù)、產(chǎn)品和計(jì)劃的商業(yè)價(jià)值和見解。在帕克大學(xué)教授數(shù)據(jù)科學(xué)，并在加州大學(xué)圣地亞哥分校教授Windows WCF課程。擔(dān)任《財(cái)富》500強(qiáng)企業(yè)和初創(chuàng)企業(yè)顧問。曾出版亞馬遜編程語言暢銷書《f#函數(shù)編程》。

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