644 個「 TensorFlow Dev 」的搜尋結果

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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

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

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

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

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

TFX:使用TensorFlow生產ML管道(TF World '19) (TFX: Production ML pipelines with TensorFlow (TF World '19))

41:46

TFX:使用TensorFlow生產ML管道(TF World '19) (TFX: Production ML pipelines with TensorFlow (TF World '19))

4

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

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

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

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

與TFLite代表一起加速模型（TF開發峰會'20）。 (Accelerate models with TFLite Delegates (TF Dev Summit '20))

15:20

與TFLite代表一起加速模型（TF開發峰會'20）。 (Accelerate models with TFLite Delegates (TF Dev Summit '20))

4

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

TensorFlow.js:網絡和其他領域的ML(TF Dev Summit '20) (TensorFlow.js: ML for the web and beyond (TF Dev Summit '20))

11:15

TensorFlow.js:網絡和其他領域的ML(TF Dev Summit '20) (TensorFlow.js: ML for the web and beyond (TF Dev Summit '20))

1

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

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WebAssembly和線程(Chrome開發峰會2018) (Using WebAssembly and Threads (Chrome Dev Summit 2018))

22:13

使用WebAssembly和線程(Chrome開發峰會2018) (Using WebAssembly and Threads (Chrome Dev Summit 2018))

18

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

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

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

安卓設計支持庫（谷歌開發100天》）。 (Android Design Support Library (100 Days of Google Dev))

05:17

安卓設計支持庫（谷歌開發100天》）。 (Android Design Support Library (100 Days of Google Dev))

502

中文 B2 中高級

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

在Codice Ratio。梵蒂岡祕密檔案中的機器轉錄(TF Dev Summit '19) (In Codice Ratio: Machine Transcription in the Vatican Secret Archive (TF Dev Summit '19))

11:22

在Codice Ratio。梵蒂岡祕密檔案中的機器轉錄(TF Dev Summit '19) (In Codice Ratio: Machine Transcription in the Vatican Secret Archive (TF Dev Summit '19))

9

用於氣候分析的Exascale深度學習(TF Dev Summit '19) (Exascale Deep Learning for Climate Analytics (TF Dev Summit ‘19))

14:54

用於氣候分析的Exascale深度學習(TF Dev Summit '19) (Exascale Deep Learning for Climate Analytics (TF Dev Summit ‘19))

2

為什麼我需要元數據？(TensorFlow Extended) (Why do I need metadata? (TensorFlow Extended))

05:32

為什麼我需要元數據？(TensorFlow Extended) (Why do I need metadata? (TensorFlow Extended))

1

使用神經網絡和ML迴歸模型進行分類(#AskTensorFlow) (Classification using neural networks & ML regression models (#AskTensorFlow))

06:56

使用神經網絡和ML迴歸模型進行分類(#AskTensorFlow) (Classification using neural networks & ML regression models (#AskTensorFlow))

2

BINARY CLASSIFIER WITH TENSORFLOW - CS50 on Twitch, EP.7 (BINARY CLASSIFIER WITH TENSORFLOW - CS50 on Twitch, EP. 7)

138:46

BINARY CLASSIFIER WITH TENSORFLOW - CS50 on Twitch, EP.7 (BINARY CLASSIFIER WITH TENSORFLOW - CS50 on Twitch, EP. 7)

2

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

TFX管道是如何工作的？(TensorFlow Extended) (How do TFX pipelines work? (TensorFlow Extended))

05:00

TFX管道是如何工作的？(TensorFlow Extended) (How do TFX pipelines work? (TensorFlow Extended))

3

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

構建影像分類器(法語編碼TensorFlow) (Construire un classifieur d'images (Coding TensorFlow en français))

05:42

構建影像分類器(法語編碼TensorFlow) (Construire un classifieur d'images (Coding TensorFlow en français))

2

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

設計神經網絡｜文本分類教程Pt.2 (編碼TensorFlow) (Designing a neural network | Text Classification Tutorial Pt. 2 (Coding TensorFlow))

06:03

設計神經網絡｜文本分類教程Pt.2 (編碼TensorFlow) (Designing a neural network | Text Classification Tutorial Pt. 2 (Coding TensorFlow))

5

DevByte:Google Play服務7.8 (Google開發100天) (DevByte: Google Play services 7.8 (100 Days of Google Dev))

05:35

DevByte:Google Play服務7.8 (Google開發100天) (DevByte: Google Play services 7.8 (100 Days of Google Dev))

93

與Brillo & Weave團隊的爐邊哈拉（2016年Ubiquity開發峰會）。 (Fireside Chat with the Brillo & Weave Team (Ubiquity Dev Summit 2016))

46:45

與Brillo & Weave團隊的爐邊哈拉（2016年Ubiquity開發峰會）。 (Fireside Chat with the Brillo & Weave Team (Ubiquity Dev Summit 2016))

101

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

第2天主題演講（TF World '19) (Day 2 Keynote (TF World '19))

89:35

第2天主題演講（TF World '19) (Day 2 Keynote (TF World '19))

3

如何編寫用戶故事、史詩和角色--發展生活 (How To Write User Stories, Epics, & Personas - Dev Life)

07:39

如何編寫用戶故事、史詩和角色--發展生活 (How To Write User Stories, Epics, & Personas - Dev Life)

7

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

TensorFlow中的神經結構化學習(TF World '19) (Neural structured learning in TensorFlow (TF World '19))

42:30

TensorFlow中的神經結構化學習(TF World '19) (Neural structured learning in TensorFlow (TF World '19))

1

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

2019年穀歌I/O大會上的ML與AI沙盒演示。 (ML & AI sandbox demos at Google I/O 2019)

02:44

2019年穀歌I/O大會上的ML與AI沙盒演示。 (ML & AI sandbox demos at Google I/O 2019)

4

YANDEREDEV YANDEREDEV!!!(Yandere Simulator Parody Song) [мoм0кι] 。 (YANDEREDEV YANDEREDEV!!! (Yandere Simulator Parody Song) [мoм0кι])

02:07

YANDEREDEV YANDEREDEV!!!(Yandere Simulator Parody Song) [мoм0кι] 。 (YANDEREDEV YANDEREDEV!!! (Yandere Simulator Parody Song) [мoм0кι])

128

中文 A2 初級

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