10,000 個「 keras and tensorflow 」的搜尋結果

依關聯性

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用TensorFlow負責任的AI（TF Dev Summit '20）。 (Responsible AI with TensorFlow (TF Dev Summit '20))

21:52

用TensorFlow負責任的AI（TF Dev Summit '20）。 (Responsible AI with TensorFlow (TF Dev Summit '20))

2

用PyCharm IDE為你的TensorFlow項目排憂解難（TensorFlow一週小貼士）。 (De-bug your TensorFlow projects with the PyCharm IDE (TensorFlow Tip of the Week))

03:12

用PyCharm IDE為你的TensorFlow項目排憂解難（TensorFlow一週小貼士）。 (De-bug your TensorFlow projects with the PyCharm IDE (TensorFlow Tip of the Week))

5

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

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

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

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

NMT概念和參數--用深度學習、Python和TensorFlow創建哈拉機器人第8頁。 (NMT Concepts and Parameters - Creating a Chatbot with Deep Learning, Python, and TensorFlow p.8)

28:17

NMT概念和參數--用深度學習、Python和TensorFlow創建哈拉機器人第8頁。 (NMT Concepts and Parameters - Creating a Chatbot with Deep Learning, Python, and TensorFlow p.8)

7

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

確定插入--用深度學習、Python和TensorFlow創建一個哈拉機器人第4頁。 (Determining insert - Creating a Chatbot with Deep Learning, Python, and TensorFlow p.4)

07:48

確定插入--用深度學習、Python和TensorFlow創建一個哈拉機器人第4頁。 (Determining insert - Creating a Chatbot with Deep Learning, Python, and TensorFlow p.4)

2

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

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

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

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

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

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

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

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

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

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

但以理與音海 (Daniel and the Sea of Sound)

05:16

但以理與音海 (Daniel and the Sea of Sound)

188

中文 A2 初級

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

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