10,000 個「 contribute to tensorflow 」的搜尋結果

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TensorFlow：開源的機器學習 (TensorFlow: Open source machine learning)

02:18

TensorFlow：開源的機器學習 (TensorFlow: Open source machine learning)

98

在瀏覽器中使用TensorFlow.js (用英文編碼TensorFlow) (Utilize o TensorFlow.js no seu navegador (Coding TensorFlow em português))

09:29

在瀏覽器中使用TensorFlow.js (用英文編碼TensorFlow) (Utilize o TensorFlow.js no seu navegador (Coding TensorFlow em português))

7

Inside TensorFlow: Graph rewriting (Macros, not functions) (Inside TensorFlow: Graph rewriting (Macros, not functions))

44:03

Inside TensorFlow: Graph rewriting (Macros, not functions) (Inside TensorFlow: Graph rewriting (Macros, not functions))

5

用Keras使用TensorBoard（TensorFlow一週小技巧）。 (Using TensorBoard with Keras (TensorFlow Tip of the Week))

01:58

用Keras使用TensorBoard（TensorFlow一週小技巧）。 (Using TensorBoard with Keras (TensorFlow Tip of the Week))

3

TensorFlow內部：控制流 (Inside TensorFlow: Control Flow)

46:59

TensorFlow內部：控制流 (Inside TensorFlow: Control Flow)

6

在Android Things上使用谷歌雲和TensorFlow（Google I/O'17）。 (Using Google Cloud and TensorFlow on Android Things (Google I/O '17))

32:59

在Android Things上使用谷歌雲和TensorFlow（Google I/O'17）。 (Using Google Cloud and TensorFlow on Android Things (Google I/O '17))

109

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

TensorFlow內部：TF-Agent (Inside TensorFlow: TF-Agents)

49:59

TensorFlow內部：TF-Agent (Inside TensorFlow: TF-Agents)

5

用PyCharm IDE為你的TensorFlow項目排憂解難（TensorFlow一週小貼士）。 (De-bug your TensorFlow projects with the PyCharm IDE (TensorFlow Tip of the Week))

03:12

用PyCharm IDE為你的TensorFlow項目排憂解難（TensorFlow一週小貼士）。 (De-bug your TensorFlow projects with the PyCharm IDE (TensorFlow Tip of the Week))

5

為Keras快速獲取CSV到數據集中（TensorFlow本週小技巧）。 (Quickly get CSV into datasets for Keras (TensorFlow Tip of the Week))

01:58

為Keras快速獲取CSV到數據集中（TensorFlow本週小技巧）。 (Quickly get CSV into datasets for Keras (TensorFlow Tip of the Week))

3

由TensorFlow提供技術支持：利用機器學習幫助醫生檢測呼吸系統疾病。 (Powered by TensorFlow: Helping doctors detect respiratory diseases using machine learning)

03:12

由TensorFlow提供技術支持：利用機器學習幫助醫生檢測呼吸系統疾病。 (Powered by TensorFlow: Helping doctors detect respiratory diseases using machine learning)

7

TensorFlow的公平性指標（TF Dev Summit '20) (Fairness Indicators for TensorFlow (TF Dev Summit '20))

06:17

TensorFlow的公平性指標（TF Dev Summit '20) (Fairness Indicators for TensorFlow (TF Dev Summit '20))

4

TensorFlow內部：摘要和TensorBoard (Inside TensorFlow: Summaries and TensorBoard)

43:23

TensorFlow內部：摘要和TensorBoard (Inside TensorFlow: Summaries and TensorBoard)

1

在5分鐘內開始使用TensorFlow的高級API | Google I/O 2018 (Get started with TensorFlow's High-Level APIs in 5 mins | Google I/O 2018)

05:15

在5分鐘內開始使用TensorFlow的高級API | Google I/O 2018 (Get started with TensorFlow's High-Level APIs in 5 mins | Google I/O 2018)

3

由TensorFlow提供支持：Airbnb使用機器學習幫助其房源照片分類 (Powered by TensorFlow: Airbnb uses machine learning to help categorize its listing photos)

02:38

由TensorFlow提供支持：Airbnb使用機器學習幫助其房源照片分類 (Powered by TensorFlow: Airbnb uses machine learning to help categorize its listing photos)

2

模型理解和業務現實（TensorFlow擴展 (Model Understanding and Business Reality (TensorFlow Extended))

08:53

模型理解和業務現實（TensorFlow擴展 (Model Understanding and Business Reality (TensorFlow Extended))

2

TensorFlow和深度強化學習，不需要博士學位（Google I/O '18）。 (TensorFlow and deep reinforcement learning, without a PhD (Google I/O '18))

40:47

TensorFlow和深度強化學習，不需要博士學位（Google I/O '18）。 (TensorFlow and deep reinforcement learning, without a PhD (Google I/O '18))

2

Inside TensorFlow: tf.Keras (part 2) (Inside TensorFlow: tf.Keras (part 2))

51:34

Inside TensorFlow: tf.Keras (part 2) (Inside TensorFlow: tf.Keras (part 2))

5

Magenta項目（2018年TensorFlow發展峰會）。 (Project Magenta (TensorFlow Dev Summit 2018))

13:57

Magenta項目（2018年TensorFlow發展峰會）。 (Project Magenta (TensorFlow Dev Summit 2018))

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

感知型深度學習研究（TensorFlow遇見了 (Affective Deep Learning Research (TensorFlow Meets))

08:02

感知型深度學習研究（TensorFlow遇見了 (Affective Deep Learning Research (TensorFlow Meets))

1

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tf.data、tf.function和tf.distribution在TensorFlow 2中建立高性能、可擴展的模型 (TF World '19) (Performant, scalable models in TensorFlow 2 with tf.data, tf.function & tf.distribute (TF World '19))

40:35

使用tf.data、tf.function和tf.distribution在TensorFlow 2中建立高性能、可擴展的模型 (TF World '19) (Performant, scalable models in TensorFlow 2 with tf.data, tf.function & tf.distribute (TF World '19))

1

從原型到生產，輕鬆實現設備上的ML（TF Dev Summit '20）。 (Easy on-device ML from prototype to production (TF Dev Summit '20))

16:30

從原型到生產，輕鬆實現設備上的ML（TF Dev Summit '20）。 (Easy on-device ML from prototype to production (TF Dev Summit '20))

1

TensorFlow內部：tf.Keras(第1部分) (Inside TensorFlow: tf.Keras (part 1))

53:37

TensorFlow內部：tf.Keras(第1部分) (Inside TensorFlow: tf.Keras (part 1))

7

用Tensorflow進行深度學習--張力器、變量和佔位符。 (Deep Learning with Tensorflow - Tensors, Variables and Placeholders)

04:51

用Tensorflow進行深度學習--張力器、變量和佔位符。 (Deep Learning with Tensorflow - Tensors, Variables and Placeholders)

96

Tensor2Tensor (TensorFlow @ O'Reilly AI Conference, San Francisco '18) (Tensor2Tensor (TensorFlow @ O’Reilly AI Conference, San Francisco '18))

39:01

Tensor2Tensor (TensorFlow @ O'Reilly AI Conference, San Francisco '18) (Tensor2Tensor (TensorFlow @ O’Reilly AI Conference, San Francisco '18))

5

解決你的模型的過擬合和欠擬合問題--Pt.2（編碼TensorFlow）。 (Solve your model’s overfitting and underfitting problems - Pt.2 (Coding TensorFlow))

04:52

解決你的模型的過擬合和欠擬合問題--Pt.2（編碼TensorFlow）。 (Solve your model’s overfitting and underfitting problems - Pt.2 (Coding TensorFlow))

2

阿育吠陀認為婆羅米（Bacopa monnieri）、印度楝樹和 Guggul 有助於健康？ (How do Brahmi (Bacopa monnieri) , Neem, and Guggul believed to contribute to health in Ayurveda?)

00:59

阿育吠陀認為婆羅米（Bacopa monnieri）、印度楝樹和 Guggul 有助於健康？ (How do Brahmi (Bacopa monnieri) , Neem, and Guggul believed to contribute to health in Ayurveda?)

4

中文 B2 中高級

由TensorFlow提供支持：利用機器學習幫助古籍整理者轉錄中世紀文本。 (Powered by TensorFlow: helping paleographers transcribe medieval text using machine learning)

02:59

由TensorFlow提供支持：利用機器學習幫助古籍整理者轉錄中世紀文本。 (Powered by TensorFlow: helping paleographers transcribe medieval text using machine learning)

1

TensorFlow Extended（TFX）。機器學習管道和模型理解（Google I/O'19) (TensorFlow Extended (TFX): Machine Learning Pipelines and Model Understanding (Google I/O'19))

37:51

TensorFlow Extended（TFX）。機器學習管道和模型理解（Google I/O'19) (TensorFlow Extended (TFX): Machine Learning Pipelines and Model Understanding (Google I/O'19))

2

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

解決你的模型的過擬合和欠擬合問題--Pt.1（編碼TensorFlow）。 (Solve your model’s overfitting and underfitting problems - Pt.1 (Coding TensorFlow))

04:43

解決你的模型的過擬合和欠擬合問題--Pt.1（編碼TensorFlow）。 (Solve your model’s overfitting and underfitting problems - Pt.1 (Coding TensorFlow))

3

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

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

使用TensorFlow的自然語言處理2--初級課程 (Natural Language Processing with TensorFlow 2 - Beginner's Course)

95:44

使用TensorFlow的自然語言處理2--初級課程 (Natural Language Processing with TensorFlow 2 - Beginner's Course)

3

準備你的數據的ML | 文本分類教程Pt.1 (編碼TensorFlow) (Prepare your data for ML | Text Classification Tutorial Pt. 1 (Coding TensorFlow))

04:25

準備你的數據的ML | 文本分類教程Pt.1 (編碼TensorFlow) (Prepare your data for ML | Text Classification Tutorial Pt. 1 (Coding TensorFlow))

1

沒有博士學位的TensorFlow和深度學習，第一部分（Google Cloud Next '17）。 (TensorFlow and Deep Learning without a PhD, Part 1 (Google Cloud Next '17))

55:52

沒有博士學位的TensorFlow和深度學習，第一部分（Google Cloud Next '17）。 (TensorFlow and Deep Learning without a PhD, Part 1 (Google Cloud Next '17))

186

開始使用Google Colaboratory（編碼TensorFlow）。 (Get started with Google Colaboratory (Coding TensorFlow))

03:10

開始使用Google Colaboratory（編碼TensorFlow）。 (Get started with Google Colaboratory (Coding TensorFlow))

2

使用TensorFlow進行廣度和深度學習 - 機器學習 (Wide & Deep Learning with TensorFlow - Machine Learning)

03:25

使用TensorFlow進行廣度和深度學習 - 機器學習 (Wide & Deep Learning with TensorFlow - Machine Learning)

145

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

用Python、TensorFlow和Keras進行深度學習教程 (Deep Learning with Python, TensorFlow, and Keras tutorial)

20:34

用Python、TensorFlow和Keras進行深度學習教程 (Deep Learning with Python, TensorFlow, and Keras tutorial)

67

TF 2.x on Kaggle (TF Dev Summit '20) (TF 2.x on Kaggle (TF Dev Summit '20))

05:33

TF 2.x on Kaggle (TF Dev Summit '20) (TF 2.x on Kaggle (TF Dev Summit '20))

1

tf.function和Autograph (TF Dev Summit '19) (tf.function and Autograph (TF Dev Summit ‘19))

14:38

tf.function和Autograph (TF Dev Summit '19) (tf.function and Autograph (TF Dev Summit ‘19))

1

充分利用Colab (TF開發峰會'20) (Making the most of Colab (TF Dev Summit '20))

06:44

充分利用Colab (TF開發峰會'20) (Making the most of Colab (TF Dev Summit '20))

7

機器學習和TensorFlow的進展（Google I/O '18）。 (Advances in machine learning and TensorFlow (Google I/O '18))

42:15

機器學習和TensorFlow的進展（Google I/O '18）。 (Advances in machine learning and TensorFlow (Google I/O '18))

2