8,555 個「 tensorflow user groups 」的搜尋結果

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使用TensorFlow.js為你的JavaScript應用釋放ML的力量（TF World '19）。 (Unlocking the power of ML for your JavaScript applications with TensorFlow.js (TF World '19))

43:36

使用TensorFlow.js為你的JavaScript應用釋放ML的力量（TF World '19）。 (Unlocking the power of ML for your JavaScript applications with TensorFlow.js (TF World '19))

2

Kotlin介紹（Google I/O'17 (Introduction to Kotlin (Google I/O '17))

38:39

Kotlin介紹（Google I/O'17 (Introduction to Kotlin (Google I/O '17))

157

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

用戶體驗設計介紹。重新思考設計過程 (Intro to User Experience Design: Rethinking the Design Process)

47:09

用戶體驗設計介紹。重新思考設計過程 (Intro to User Experience Design: Rethinking the Design Process)

433

聯邦學習。分散數據的機器學習(Google I/O'19) (Federated Learning: Machine Learning on Decentralized Data (Google I/O'19))

41:11

聯邦學習。分散數據的機器學習(Google I/O'19) (Federated Learning: Machine Learning on Decentralized Data (Google I/O'19))

4

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

用Python訓練模型並加載到TensorFlow.js中 - TensorFlow.js p.4 (Training model in Python and Loading into TensorFlow.js - TensorFlow.js p.4)

19:54

用Python訓練模型並加載到TensorFlow.js中 - TensorFlow.js p.4 (Training model in Python and Loading into TensorFlow.js - TensorFlow.js p.4)

2

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

如何從USB安裝Windows 11 (How To Install Windows 11 From USB)

02:14

如何從USB安裝Windows 11 (How To Install Windows 11 From USB)

5

中文 B1 中級

提花。將ML無縫嵌入到日常物品中（TF開發峰會'20) (Jacquard: Embedding ML seamlessly into everyday objects (TF Dev Summit '20))

10:15

提花。將ML無縫嵌入到日常物品中（TF開發峰會'20) (Jacquard: Embedding ML seamlessly into everyday objects (TF Dev Summit '20))

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

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

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

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

機器學習在你的設備上。選項（Google I/O'19 (Machine Learning on Your Device: The Options (Google I/O'19))

38:32

機器學習在你的設備上。選項（Google I/O'19 (Machine Learning on Your Device: The Options (Google I/O'19))

4

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

5個神奇的食物群 (The 5 Fabulous Food Groups)

04:32

5個神奇的食物群 (The 5 Fabulous Food Groups)

760

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

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

蘇珊-溫申克博士的《用戶體驗的投資回報率》。 (The ROI of User Experience with Dr. Susan Weinschenk)

05:52

蘇珊-溫申克博士的《用戶體驗的投資回報率》。 (The ROI of User Experience with Dr. Susan Weinschenk)

83

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

擺好姿勢--JavaScript中的手勢識別/ML與Arduino--Charlie Gerard--2019年美國JSConf大會。 (Strike a Pose - Gesture recognition in JavaScript w/ ML & Arduino - Charlie Gerard - JSConf US 2019)

27:53

擺好姿勢--JavaScript中的手勢識別/ML與Arduino--Charlie Gerard--2019年美國JSConf大會。 (Strike a Pose - Gesture recognition in JavaScript w/ ML & Arduino - Charlie Gerard - JSConf US 2019)

1

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

機器學習。谷歌的願景--谷歌I/O 2016 (Machine Learning: Google's Vision - Google I/O 2016)

44:45

機器學習。谷歌的願景--谷歌I/O 2016 (Machine Learning: Google's Vision - Google I/O 2016)

407

用tf.text建立模型(TF World '19) (Building models with tf.text (TF World '19))

39:33

用tf.text建立模型(TF World '19) (Building models with tf.text (TF World '19))

2

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

第16講--如何進行用戶訪談（Emmett Shear）。 (Lecture 16 - How to Run a User Interview (Emmett Shear))

46:28

第16講--如何進行用戶訪談（Emmett Shear）。 (Lecture 16 - How to Run a User Interview (Emmett Shear))

211

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

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

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

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

帕洛阿爾託網絡公司防火牆演示界面第2部分(WeSecure) (Palo Alto Networks Firewall Demo Interface part 2 (WeSecure))

09:51

帕洛阿爾託網絡公司防火牆演示界面第2部分(WeSecure) (Palo Alto Networks Firewall Demo Interface part 2 (WeSecure))

76

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

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

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

為什麼恐怖組織不可能永遠存在？ (Why Terrorist Groups Can't Last Forever)

02:47

為什麼恐怖組織不可能永遠存在？ (Why Terrorist Groups Can't Last Forever)

94