10,000 個「 production machine learning pipeline 」的搜尋結果

依關聯性

VoiceTube 廣告

機器學習 - CS50播客，Ep.6。 (Machine Learning - CS50 Podcast, Ep. 6)

28:25

機器學習 - CS50播客，Ep.6。 (Machine Learning - CS50 Podcast, Ep. 6)

4

TensorFlow內部：tf.data - TF輸入管道 (Inside TensorFlow: tf.data - TF Input Pipeline)

53:52

TensorFlow內部：tf.data - TF輸入管道 (Inside TensorFlow: tf.data - TF Input Pipeline)

3

機器學習的7個步驟 (The 7 Steps of Machine Learning)

10:36

機器學習的7個步驟 (The 7 Steps of Machine Learning)

133

Dyad X Machina：將情感帶入機器學習（TensorFlow Meets）。 (Dyad X Machina: bringing emotion into machine learning (TensorFlow Meets))

10:48

Dyad X Machina：將情感帶入機器學習（TensorFlow Meets）。 (Dyad X Machina: bringing emotion into machine learning (TensorFlow Meets))

5

雲計算TPU（TensorFlow @ O'Reilly AI大會，18年舊金山）。 (Cloud TPUs (TensorFlow @ O’Reilly AI Conference, San Francisco '18))

22:09

雲計算TPU（TensorFlow @ O'Reilly AI大會，18年舊金山）。 (Cloud TPUs (TensorFlow @ O’Reilly AI Conference, San Francisco '18))

3

使用TensorFlow數據集(TensorFlow Meet) (Working with TensorFlow Datasets (TensorFlow Meets))

08:11

使用TensorFlow數據集(TensorFlow Meet) (Working with TensorFlow Datasets (TensorFlow Meets))

1

分佈式TensorFlow訓練（谷歌I/O'18 (Distributed TensorFlow training (Google I/O '18))

35:27

分佈式TensorFlow訓練（谷歌I/O'18 (Distributed TensorFlow training (Google I/O '18))

2

小組討論。機器學習的應用 (Panel Discussion: Applications of Machine Learning)

43:18

小組討論。機器學習的應用 (Panel Discussion: Applications of Machine Learning)

254

2016年CS50--第七週--機器學習 (CS50 2016 - Week 7 - Machine Learning)

82:56

2016年CS50--第七週--機器學習 (CS50 2016 - Week 7 - Machine Learning)

206

TensorFlow在生產中。TF Extended、TF Hub和TF Serving (Google I/O '18) (TensorFlow in production: TF Extended, TF Hub, and TF Serving (Google I/O '18))

36:49

TensorFlow在生產中。TF Extended、TF Hub和TF Serving (Google I/O '18) (TensorFlow in production: TF Extended, TF Hub, and TF Serving (Google I/O '18))

4

遊戲開發者的機器學習(Google I/O'19) (Machine Learning for Game Developers (Google I/O'19))

32:20

遊戲開發者的機器學習(Google I/O'19) (Machine Learning for Game Developers (Google I/O'19))

2

機器學習介紹（ML Zero to Hero，第一部分 (Introducción a Machine Learning (ML Zero to Hero, parte 1))

06:19

機器學習介紹（ML Zero to Hero，第一部分 (Introducción a Machine Learning (ML Zero to Hero, parte 1))

3

你必須使用的5個開發者工具 (5 Developer Tools You NEED to Use)

13:03

你必須使用的5個開發者工具 (5 Developer Tools You NEED to Use)

6

Pixar in a Box概述 (Overview of Pixar in a Box)

05:20

Pixar in a Box概述 (Overview of Pixar in a Box)

251

中文 A2 初級

TensorFlow開發峰會2019生活流 (TensorFlow Dev Summit 2019 Livestream)

541:44

TensorFlow開發峰會2019生活流 (TensorFlow Dev Summit 2019 Livestream)

6

學習機器學習的最佳資源？ML到底是什麼？與ML工程師的問答 (Best Resources for Learning Machine Learning? What Is ML Anyway? Q&A with ML Engineers!)

12:01

學習機器學習的最佳資源？ML到底是什麼？與ML工程師的問答 (Best Resources for Learning Machine Learning? What Is ML Anyway? Q&A with ML Engineers!)

3

Live Perception的ML解決方案（TF Dev Summit '20）。 (ML solutions for Live Perception (TF Dev Summit '20))

16:40

Live Perception的ML解決方案（TF Dev Summit '20）。 (ML solutions for Live Perception (TF Dev Summit '20))

3

字幕已審核

機器學習與人類偏見 (Machine Learning and Human Bias)

02:33

機器學習與人類偏見 (Machine Learning and Human Bias)

12153

中文 B1 中級

TensorFlow Extended (TFX) & Hub (TensorFlow @ O Reilly AI Conference, San Francisco '18) (TensorFlow Extended (TFX) & Hub (TensorFlow @ O’Reilly AI Conference, San Francisco '18))

41:41

TensorFlow Extended (TFX) & Hub (TensorFlow @ O Reilly AI Conference, San Francisco '18) (TensorFlow Extended (TFX) & Hub (TensorFlow @ O’Reilly AI Conference, San Francisco '18))

2

機器學習與藝術--谷歌I/O 2016 (Machine learning & art - Google I/O 2016)

42:36

機器學習與藝術--谷歌I/O 2016 (Machine learning & art - Google I/O 2016)

141

聯邦學習。分散數據的機器學習(Google I/O'19) (Federated Learning: Machine Learning on Decentralized Data (Google I/O'19))

41:11

聯邦學習。分散數據的機器學習(Google I/O'19) (Federated Learning: Machine Learning on Decentralized Data (Google I/O'19))

4

TF Lite Lens (TF Dev Summit '20) (TF Lite Lens (TF Dev Summit '20))

07:44

TF Lite Lens (TF Dev Summit '20) (TF Lite Lens (TF Dev Summit '20))

2

有監督的機器學習。Crash Course Statistics #36 (Supervised Machine Learning: Crash Course Statistics #36)

11:51

有監督的機器學習。Crash Course Statistics #36 (Supervised Machine Learning: Crash Course Statistics #36)

2

什麼是人工智能（或機器學習）？ (What is Artificial Intelligence (or Machine Learning)?)

06:15

什麼是人工智能（或機器學習）？ (What is Artificial Intelligence (or Machine Learning)?)

342

中文 B1 中級

英特爾Python發行版亮點和概述｜英特爾軟件 (Intel Distribution for Python Highlights & Overview | Intel Software)

04:35

英特爾Python發行版亮點和概述｜英特爾軟件 (Intel Distribution for Python Highlights & Overview | Intel Software)

23

機器學習不是未來--2016年穀歌I/O大會。 (Machine learning is not the future - Google I/O 2016)

39:00

機器學習不是未來--2016年穀歌I/O大會。 (Machine learning is not the future - Google I/O 2016)

115

廁所裡的故事》由皮埃爾-保羅-福馬加里撰寫｜JSConf EU 2019 (Tales from the Toilet by Pier Paolo Fumagalli | JSConf EU 2019)

25:43

廁所裡的故事》由皮埃爾-保羅-福馬加里撰寫｜JSConf EU 2019 (Tales from the Toilet by Pier Paolo Fumagalli | JSConf EU 2019)

2

英特爾公司，馬紫雅 - WiDS 2018 (Ziya Ma, Intel Corporation | WiDS 2018)

17:39

英特爾公司，馬紫雅 - WiDS 2018 (Ziya Ma, Intel Corporation | WiDS 2018)

103

無監督的機器學習。Crash Course Statistics #37 (Unsupervised Machine Learning: Crash Course Statistics #37)

10:56

無監督的機器學習。Crash Course Statistics #37 (Unsupervised Machine Learning: Crash Course Statistics #37)

3

用TensorFlow負責任的AI（TF Dev Summit '20）。 (Responsible AI with TensorFlow (TF Dev Summit '20))

21:52

用TensorFlow負責任的AI（TF Dev Summit '20）。 (Responsible AI with TensorFlow (TF Dev Summit '20))

2

Tania的故事。莫爾斯碼遇上機器學習 (Tania’s Story: Morse code meets machine learning)

02:23

Tania的故事。莫爾斯碼遇上機器學習 (Tania’s Story: Morse code meets machine learning)

55

中文 A2 初級

機器學習如何讓我們的決策變得更聰明？ (How Machine Learning Makes Our Decisions Smarter)

06:46

機器學習如何讓我們的決策變得更聰明？ (How Machine Learning Makes Our Decisions Smarter)

7

使用ML預測1型糖尿病的胰島素使用情況（TensorFlow Meets）。 (Using ML to predict insulin use for Type 1 Diabetes (TensorFlow Meets))

12:48

使用ML預測1型糖尿病的胰島素使用情況（TensorFlow Meets）。 (Using ML to predict insulin use for Type 1 Diabetes (TensorFlow Meets))

4

深度學習框架對比 (Deep Learning Frameworks Compared)

05:45

深度學習框架對比 (Deep Learning Frameworks Compared)

85

機器學習如何幫助科學家追蹤小行星？ (How machine learning helps scientists track asteroids)

01:22

機器學習如何幫助科學家追蹤小行星？ (How machine learning helps scientists track asteroids)

9

機器學習API實例（Google Cloud Next'17 (Machine Learning APIs by Example (Google Cloud Next '17))

38:36

機器學習API實例（Google Cloud Next'17 (Machine Learning APIs by Example (Google Cloud Next '17))

154

可口可樂公司的應用人工智能（TensorFlow Dev Summit 2018）。 (Applied AI at The Coca-Cola Company (TensorFlow Dev Summit 2018))

10:35

可口可樂公司的應用人工智能（TensorFlow Dev Summit 2018）。 (Applied AI at The Coca-Cola Company (TensorFlow Dev Summit 2018))

2

TensorFlow Hub：重用機器學習模塊(TensorFlow Meets) (TensorFlow Hub: reusing machine learning modules (TensorFlow Meets))

04:50

TensorFlow Hub：重用機器學習模塊(TensorFlow Meets) (TensorFlow Hub: reusing machine learning modules (TensorFlow Meets))

2

Spell（用於雲端機器學習）介紹。 (Introduction to Spell (for Machine Learning in the Cloud))

26:08

Spell（用於雲端機器學習）介紹。 (Introduction to Spell (for Machine Learning in the Cloud))

3

回答你的TF Lite問題以及更多(#AskTensorFlow) (Answering your TF Lite questions and more! (#AskTensorFlow))

15:40

回答你的TF Lite問題以及更多(#AskTensorFlow) (Answering your TF Lite questions and more! (#AskTensorFlow))

2

機器學習。谷歌的願景--谷歌I/O 2016 (Machine Learning: Google's Vision - Google I/O 2016)

44:45

機器學習。谷歌的願景--谷歌I/O 2016 (Machine Learning: Google's Vision - Google I/O 2016)

407

TFX：TensorFlow的端到端機器學習平臺(TensorFlow Meets) (TFX: an end-to-end machine learning platform for TensorFlow (TensorFlow Meets))

06:24

TFX：TensorFlow的端到端機器學習平臺(TensorFlow Meets) (TFX: an end-to-end machine learning platform for TensorFlow (TensorFlow Meets))

5

07:00

特斯拉 (tesla)

198

編碼挑戰賽#151.Ukulele Tuner with Machine Learning Pitch Detection Model:使用機器學習音高檢測模型的尤克里裡調音器 (Coding Challenge #151: Ukulele Tuner with Machine Learning Pitch Detection Model)

35:55

編碼挑戰賽#151.Ukulele Tuner with Machine Learning Pitch Detection Model:使用機器學習音高檢測模型的尤克里裡調音器 (Coding Challenge #151: Ukulele Tuner with Machine Learning Pitch Detection Model)

5

為機器學習準備你的數據集（TensorFlow編碼）。 (Prepare your dataset for machine learning (Coding TensorFlow))

07:37

為機器學習準備你的數據集（TensorFlow編碼）。 (Prepare your dataset for machine learning (Coding TensorFlow))

2

#ProjectCleanMachine | Adobe MAX Sneaks 2024 | Adobe (#ProjectCleanMachine | Adobe MAX Sneaks 2024 | Adobe)

05:01

#ProjectCleanMachine | Adobe MAX Sneaks 2024 | Adobe (#ProjectCleanMachine | Adobe MAX Sneaks 2024 | Adobe)

1

中文 B1 中級