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

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Inside TensorFlow：TF模型優化工具包（量化和剪枝）。 (Inside TensorFlow: TF Model Optimization Toolkit (Quantization and Pruning))

42:35

Inside TensorFlow：TF模型優化工具包（量化和剪枝）。 (Inside TensorFlow: TF Model Optimization Toolkit (Quantization and Pruning))

2

神經結構化學習--第3部分：用合成圖訓練 (Neural Structured Learning - Part 3: Training with synthesized graphs)

05:16

神經結構化學習--第3部分：用合成圖訓練 (Neural Structured Learning - Part 3: Training with synthesized graphs)

4

AutoGraph。簡單的圖形控制流程（TensorFlow本週提示 (AutoGraph: Easy control flow for graphs (TensorFlow Tip of the Week))

02:26

AutoGraph。簡單的圖形控制流程（TensorFlow本週提示 (AutoGraph: Easy control flow for graphs (TensorFlow Tip of the Week))

3

TensorFlow內部：函數，而不是會話 (Inside TensorFlow: Functions, not sessions)

46:09

TensorFlow內部：函數，而不是會話 (Inside TensorFlow: Functions, not sessions)

4

如何對火山進行分類 (How to Classify Volcanoes)

06:52

如何對火山進行分類 (How to Classify Volcanoes)

92

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

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

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

利用高性能計算進行基礎科學的深度學習（O'Reilly AI Conference）。 (Deep learning for fundamental sciences using high-performance computing (O’Reilly AI Conference))

26:36

利用高性能計算進行基礎科學的深度學習（O'Reilly AI Conference）。 (Deep learning for fundamental sciences using high-performance computing (O’Reilly AI Conference))

1

卷積神經網絡介紹(ML Zero to Hero，第三部分) (Introducing convolutional neural networks (ML Zero to Hero, part 3))

05:33

卷積神經網絡介紹(ML Zero to Hero，第三部分) (Introducing convolutional neural networks (ML Zero to Hero, part 3))

1

兩分鐘論文--利用深度學習產生幻覺的影像 (Two Minute Papers - Hallucinating Images With Deep Learning)

03:14

兩分鐘論文--利用深度學習產生幻覺的影像 (Two Minute Papers - Hallucinating Images With Deep Learning)

82

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

TensorFlow模型優化。量化和修剪(TF World'19) (TensorFlow model optimization: Quantization and pruning (TF World '19))

40:50

TensorFlow模型優化。量化和修剪(TF World'19) (TensorFlow model optimization: Quantization and pruning (TF World '19))

1

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

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

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

思想到現實。Portal Telemedicina，技術幫助農村患者獲得關鍵的醫療服務。 (Ideas to Reality: Portal Telemedicina, technology helping rural patients get crucial medical care)

02:59

思想到現實。Portal Telemedicina，技術幫助農村患者獲得關鍵的醫療服務。 (Ideas to Reality: Portal Telemedicina, technology helping rural patients get crucial medical care)

4

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

詛咒的Minecraft影像。 (CURSED Minecraft Images.)

07:50

詛咒的Minecraft影像。 (CURSED Minecraft Images.)

21

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

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

公司結構 (Corporate structure)

05:00

公司結構 (Corporate structure)

105

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

為你的JavaScript應用提供機器學習魔力（Google I/O'19) (Machine Learning Magic for Your JavaScript Application (Google I/O'19))

39:02

為你的JavaScript應用提供機器學習魔力（Google I/O'19) (Machine Learning Magic for Your JavaScript Application (Google I/O'19))

1

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

前端開發的機器學習，查理-傑拉德｜JSConf.Asia 2019年。 (Machine Learning for Front-End Developers by Charlie Gerard | JSConf.Asia 2019)

34:05

前端開發的機器學習，查理-傑拉德｜JSConf.Asia 2019年。 (Machine Learning for Front-End Developers by Charlie Gerard | JSConf.Asia 2019)

3

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

第8講 | 深度學習軟件 (Lecture 8 | Deep Learning Software)

78:07

第8講 | 深度學習軟件 (Lecture 8 | Deep Learning Software)

65

理想到現實。Gringgo垃圾技術 (Ideas to Reality: Gringgo Trash Tech)

03:30

理想到現實。Gringgo垃圾技術 (Ideas to Reality: Gringgo Trash Tech)

4

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

介紹Google Coral：構建設備上的AI（Google I/O'19）。 (Introducing Google Coral: Building On-Device AI (Google I/O'19))

45:00

介紹Google Coral：構建設備上的AI（Google I/O'19）。 (Introducing Google Coral: Building On-Device AI (Google I/O'19))

3

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

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

機器學習的公平性。經驗教訓(Google I/O'19) (Machine Learning Fairness: Lessons Learned (Google I/O'19))

36:23

機器學習的公平性。經驗教訓(Google I/O'19) (Machine Learning Fairness: Lessons Learned (Google I/O'19))

10

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