10,000 個「 tensorflow with datasets 」的搜尋結果

依關聯性

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Arun Subramaniyan討論概率建模(TensorFlow Meets) (Arun Subramaniyan discusses probabilistic modeling (TensorFlow Meets))

08:19

Arun Subramaniyan討論概率建模(TensorFlow Meets) (Arun Subramaniyan discusses probabilistic modeling (TensorFlow Meets))

2

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

如何將你的ML模型轉換為TensorFlow Lite（TensorFlow本週小技巧）。 (How to convert your ML model to TensorFlow Lite (TensorFlow Tip of the Week))

02:37

如何將你的ML模型轉換為TensorFlow Lite（TensorFlow本週小技巧）。 (How to convert your ML model to TensorFlow Lite (TensorFlow Tip of the Week))

8

在TensorFlow與核物理學的交叉點上（TensorFlow遇見 (At the intersection of TensorFlow & nuclear physics (TensorFlow Meets))

07:57

在TensorFlow與核物理學的交叉點上（TensorFlow遇見 (At the intersection of TensorFlow & nuclear physics (TensorFlow Meets))

3

Swift for TensorFlow (TF World '19) (Swift for TensorFlow (TF World '19))

39:21

Swift for TensorFlow (TF World '19) (Swift for TensorFlow (TF World '19))

2

TFX這個東西到底是什麼？(TensorFlow Extended) (What exactly is this TFX thing? (TensorFlow Extended))

05:46

TFX這個東西到底是什麼？(TensorFlow Extended) (What exactly is this TFX thing? (TensorFlow Extended))

2

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

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

機器學習如何幫助識別洛杉磯道路上的坑洞？ (How machine learning helps identify potholes on Los Angeles roads)

01:01

機器學習如何幫助識別洛杉磯道路上的坑洞？ (How machine learning helps identify potholes on Los Angeles roads)

109

中文 A2 初級

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

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

英特爾Naveen Rao博士 - SXSW 2017 - #IntelAI - #theCUBE (Dr. Naveen Rao, Intel - SXSW 2017 - #IntelAI - #theCUBE)

16:50

英特爾Naveen Rao博士 - SXSW 2017 - #IntelAI - #theCUBE (Dr. Naveen Rao, Intel - SXSW 2017 - #IntelAI - #theCUBE)

46

訓練模型--用深度學習、Python和TensorFlow創建哈拉機器人 p.7 (Training a Model - Creating a Chatbot with Deep Learning, Python, and TensorFlow p.7)

17:21

訓練模型--用深度學習、Python和TensorFlow創建哈拉機器人 p.7 (Training a Model - Creating a Chatbot with Deep Learning, Python, and TensorFlow p.7)

2

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

Swift在機器學習中的威力（TensorFlow的遇見 (The Power of Swift for Machine Learning (TensorFlow Meets))

06:31

Swift在機器學習中的威力（TensorFlow的遇見 (The Power of Swift for Machine Learning (TensorFlow Meets))

3

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

46:59

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

6

數據分析讓複雜的地球過程變得有意義 (Data analytics making sense of complex earth processes)

02:09

數據分析讓複雜的地球過程變得有意義 (Data analytics making sense of complex earth processes)

112

用Colab中的TensorFlow在4分鐘內構建一個深度神經網絡。 (Build a deep neural network in 4 mins with TensorFlow in Colab)

03:54

用Colab中的TensorFlow在4分鐘內構建一個深度神經網絡。 (Build a deep neural network in 4 mins with TensorFlow in Colab)

2

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

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

49:59

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

5

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

與我們的哈拉機器人互動--用深度學習、Python和TensorFlow創建哈拉機器人 p.9 (Interacting with our Chatbot - Creating a Chatbot with Deep Learning, Python, and TensorFlow p.9)

20:31

與我們的哈拉機器人互動--用深度學習、Python和TensorFlow創建哈拉機器人 p.9 (Interacting with our Chatbot - Creating a Chatbot with Deep Learning, Python, and TensorFlow p.9)

4

數據結構--用深度學習、Python和TensorFlow創建哈拉機器人 p.2 (Data Structure - Creating a Chatbot with Deep Learning, Python, and TensorFlow p.2)

09:48

數據結構--用深度學習、Python和TensorFlow創建哈拉機器人 p.2 (Data Structure - Creating a Chatbot with Deep Learning, Python, and TensorFlow p.2)

2

MLIR：用編譯器加速TF的發展（TF開發峰會'20) (MLIR: Accelerating TF with compilers (TF Dev Summit '20))

10:19

MLIR：用編譯器加速TF的發展（TF開發峰會'20) (MLIR: Accelerating TF with compilers (TF Dev Summit '20))

1

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

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

緩衝數據集--用深度學習、Python和TensorFlow創建哈拉機器人 p.3 (Buffering dataset - Creating a Chatbot with Deep Learning, Python, and TensorFlow p.3)

11:37

緩衝數據集--用深度學習、Python和TensorFlow創建哈拉機器人 p.3 (Buffering dataset - Creating a Chatbot with Deep Learning, Python, and TensorFlow p.3)

10

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

構建數據庫--用深度學習、Python和TensorFlow創建哈拉機器人 p.5 (Building Database - Creating a Chatbot with Deep Learning, Python, and TensorFlow p.5)

18:57

構建數據庫--用深度學習、Python和TensorFlow創建哈拉機器人 p.5 (Building Database - Creating a Chatbot with Deep Learning, Python, and TensorFlow p.5)

9

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

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

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

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

從數據庫到訓練數據--用深度學習、Python和TensorFlow創建哈拉機器人 p.6 (Database to Training Data - Creating a Chatbot with Deep Learning, Python, and TensorFlow p.6)

12:29

從數據庫到訓練數據--用深度學習、Python和TensorFlow創建哈拉機器人 p.6 (Database to Training Data - Creating a Chatbot with Deep Learning, Python, and TensorFlow p.6)

7

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

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

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

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

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

參與到TF社區中來 (TF開發峰會'20) (Getting involved in the TF community (TF Dev Summit '20))

09:25

參與到TF社區中來 (TF開發峰會'20) (Getting involved in the TF community (TF Dev Summit '20))

2

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

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

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

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