407 個「 LATAM tensorflow 」的搜尋結果

依關聯性

VoiceTube 廣告

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

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

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

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

尼科拉-約基奇為掘金第七場失利背鍋｜2019年NBA季後賽。 (Nikola Jokic takes the blame for Nuggets’ Game 7 loss | 2019 NBA Playoffs)

04:11

尼科拉-約基奇為掘金第七場失利背鍋｜2019年NBA季後賽。 (Nikola Jokic takes the blame for Nuggets’ Game 7 loss | 2019 NBA Playoffs)

3

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

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

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

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

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

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

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

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

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

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 Federated（TFF）。去中心化數據的機器學習（TF Dev Summit '19) (TensorFlow Federated (TFF): Machine Learning on Decentralized Data (TF Dev Summit ‘19))

13:26

TensorFlow Federated（TFF）。去中心化數據的機器學習（TF Dev Summit '19) (TensorFlow Federated (TFF): Machine Learning on Decentralized Data (TF Dev Summit ‘19))

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

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

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

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

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

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

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

PAI：阿里巴巴的A.I.平臺(19年TF開發峰會) (PAI: Platform of A.I. in Alibaba (TF Dev Summit '19))

05:14

PAI：阿里巴巴的A.I.平臺(19年TF開發峰會) (PAI: Platform of A.I. in Alibaba (TF Dev Summit '19))

1

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

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

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

2020年獲獎視頻的微觀世界｜深奧的科學 (The 2020 Award-Winning Videos Of The Microscopic World | Deep Science)

06:29

2020年獲獎視頻的微觀世界｜深奧的科學 (The 2020 Award-Winning Videos Of The Microscopic World | Deep Science)

10

中文 B1 中級