406 個「 keras tensorflow 」的搜尋結果

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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

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1課：編碼人員的實用深度學習 (Lesson 1: Practical Deep Learning for Coders)

98:46

第1課：編碼人員的實用深度學習 (Lesson 1: Practical Deep Learning for Coders)

504

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

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

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

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

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

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

TF-Agents.A Flexible Reinforcement Learning Library for TensorFlow (Google I/O'19)TensorFlow的靈活強化學習庫（Google I/O'19) (TF-Agents: A Flexible Reinforcement Learning Library for TensorFlow (Google I/O'19))

39:10

TF-Agents.A Flexible Reinforcement Learning Library for TensorFlow (Google I/O'19)TensorFlow的靈活強化學習庫（Google I/O'19) (TF-Agents: A Flexible Reinforcement Learning Library for TensorFlow (Google I/O'19))

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

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

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

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

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

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

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

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

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

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

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

雷諾鑫｜火花峰會2017 (Reynold Xin | Spark Summit 2017)

15:03

雷諾鑫｜火花峰會2017 (Reynold Xin | Spark Summit 2017)

115

皮膚癌影像分類（2017年TensorFlow發展峰會）。 (Skin Cancer Image Classification (TensorFlow Dev Summit 2017))

08:39

皮膚癌影像分類（2017年TensorFlow發展峰會）。 (Skin Cancer Image Classification (TensorFlow Dev Summit 2017))

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)

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

簡單明瞭的估算器(AI歷險記) (Plain and Simple Estimators (AI Adventures))

05:47

簡單明瞭的估算器(AI歷險記) (Plain and Simple Estimators (AI Adventures))

57

如何開始使用AI/ML，重新訓練模型等!(#AskTensorFlow) (How to get started with AI/ML, retraining models, & more! (#AskTensorFlow))

05:54

如何開始使用AI/ML，重新訓練模型等!(#AskTensorFlow) (How to get started with AI/ML, retraining models, & more! (#AskTensorFlow))

3

像跳舞一樣，是一款利用機器學習幫助用戶學習舞蹈的應用。 (Dance Like, an app that helps users learn how to dance using machine learning)

01:18

像跳舞一樣，是一款利用機器學習幫助用戶學習舞蹈的應用。 (Dance Like, an app that helps users learn how to dance using machine learning)

7

構建一個神經網絡來運行分類（葡萄牙語編碼TensorFlow）。 (Construa uma rede neural para executar a classificação (Coding TensorFlow em português))

07:31

構建一個神經網絡來運行分類（葡萄牙語編碼TensorFlow）。 (Construa uma rede neural para executar a classificação (Coding TensorFlow em português))

4

TensorFlow.js將機器學習帶入網絡及其他領域，由Nick Kreeger和Nikhil Thorat撰寫。 (TensorFlow.js Bringing Machine Learning to the Web and Beyond by Nick Kreeger & Nikhil Thorat)

20:21

TensorFlow.js將機器學習帶入網絡及其他領域，由Nick Kreeger和Nikhil Thorat撰寫。 (TensorFlow.js Bringing Machine Learning to the Web and Beyond by Nick Kreeger & Nikhil Thorat)

3

可口可樂公司的應用人工智能（TensorFlow Dev Summit 2018）。 (Applied AI at The Coca-Cola Company (TensorFlow Dev Summit 2018))

10:35

可口可樂公司的應用人工智能（TensorFlow Dev Summit 2018）。 (Applied AI at The Coca-Cola Company (TensorFlow Dev Summit 2018))

2

機器學習導論（英文編碼TensorFlow) (Introduction à l'apprentissage automatique (Coding TensorFlow en français))

08:21

機器學習導論（英文編碼TensorFlow) (Introduction à l'apprentissage automatique (Coding TensorFlow en français))

2

雲端AI平臺上的分佈式TensorFlow模型訓練（TF Dev Summit '20）。 (Distributed TensorFlow model training on Cloud AI Platform (TF Dev Summit '20))

14:21

雲端AI平臺上的分佈式TensorFlow模型訓練（TF Dev Summit '20）。 (Distributed TensorFlow model training on Cloud AI Platform (TF Dev Summit '20))

2

沒有博士學位的TensorFlow和深度學習，第二部分（Google Cloud Next '17）。 (TensorFlow and Deep Learning without a PhD, Part 2 (Google Cloud Next '17))

56:06

沒有博士學位的TensorFlow和深度學習，第二部分（Google Cloud Next '17）。 (TensorFlow and Deep Learning without a PhD, Part 2 (Google Cloud Next '17))

235

可差異化的凸優化層（TF Dev Summit '20）。 (Differentiable convex optimization layers (TF Dev Summit '20))

09:20

可差異化的凸優化層（TF Dev Summit '20）。 (Differentiable convex optimization layers (TF Dev Summit '20))

2