【2022年】十大TensorFlow課程熱門排行推薦與優惠精選!

 

本文章推薦「Python深度学习与Tensorflow2实战(2020新版)」、「動手做非監督式機器學習:使用TensorFlow 2.0」、「Complete Guide to TensorFlow for Deep Learning with Python」等相關TensorFlow線上課程,讓您滿足學習的慾望。

你是否想透過線上學習得到更多的技能,增加自己的技能樹?現在是學生的您,透過線上學習可以將更多專業知識用在課業學習上更加強所學。還是您是朝九晚五的上班族,尋找可以為工作上帶來更上一層樓的技能?或您是因為興趣或想培養其他興趣?

線上課程不受地理位置影響,不受時間早晚影響,老師來自世界各地,也不受學習程度影響的特色,讓您無時無刻想學都可以,想多看幾次增加熟悉度也可以。不同領域的老師將針對不同主題滿足您的學習目的,推薦的課程項目會陸續更新,絕對提供您最熱門人氣高的線上課程。

  • 線上課程老師來自於全球,文章推薦的熱門課程除了繁中課程以外還會有機會看到簡中和英文課程,可以針對自己喜好挑選。
  • 呈現的價錢會因為一些活動而有折扣,但折扣有可能一段時間後結束而調整回原價,最終價錢煩請到課程頁面進行確認。





TensorFlow課程總覽

為了節省您的時間,本列表整理每個課程精要,讓您可以快速瀏覽這文章所提供的課程是否是您所需要的,點選您有興趣課程的「課程名稱」或「課程圖示」可以進一步跳到文章所屬課程的介紹區塊瞭解更多資訊。

課程名稱Complete Guide to TensorFlow for Deep Learning with PythonA Complete Guide on TensorFlow 2.0 using Keras APIComplete Tensorflow 2 and Keras Deep Learning BootcampDeep Learning with TensorFlow 2.0 [2021]TensorFlow Developer Certificate in 2021: Zero to MasteryCrash Course in Deep Learning with Google TensorFlow|PythonTensorFlow 2.0 Practical AdvancedTensorFlow 2.0 PracticalPython深度学习与Tensorflow2实战(2020新版)動手做非監督式機器學習:使用TensorFlow 2.0
課程圖示
1

Complete Guide to TensorFlow for Deep Learning with Python

2

A Complete Guide on TensorFlow 2.0 using Keras API

3

Complete Tensorflow 2 and Keras Deep Learning Bootcamp

4

Deep Learning with TensorFlow 2.0 [2021]

5

TensorFlow Developer Certificate in 2021: Zero to Mastery

6

Crash Course in Deep Learning with Google TensorFlow|Python

7

TensorFlow 2.0 Practical Advanced

8

TensorFlow 2.0 Practical

9

Python深度学习与Tensorflow2实战(2020新版)

10

動手做非監督式機器學習:使用TensorFlow 2.0

課程原價NT$ 2,990NT$ 2,790NT$ 2,790NT$ 2,790NT$ 2,690NT$ 990NT$ 2,790NT$ 2,690NT$ 3,190NT$ 990
課程售價NT$ 490NT$ 470NT$ 490NT$ 470NT$ 470NT$ 470NT$ 470NT$ 470NT$ 570NT$ 470
課程評價(人數)4.5 分(16,124 個評分)4.5 分(1,709 個評分)4.7 分(5,222 個評分)4.7 分(2,112 個評分)4.7 分(1,436 個評分)4.9 分(266 個評分)4.5 分(306 個評分)4.7 分(551 個評分)4.3 分(55 個評分)4.4 分(8 個評分)
課程時長14 小時13 小時19 小時6 小時63 小時4 小時12.5 小時11.5 小時18 小時2.5 小時
學生人數89,790 人52,128 人31,013 人18,752 人12,768 人8,662 人5,018 人4,927 人391 人55 人
課程特色Learn how to use Google’s Deep Learning Framework – TensorFlow with Python! Solve problems with cutting edge techniques!Build Amazing Applications of Deep Learning and Artificial Intelligence in TensorFlow 2.0Learn to use Python for Deep Learning with Google’s latest Tensorflow 2 library and Keras!Build Deep Learning Algorithms with TensorFlow 2.0, Dive into Neural Networks and Apply Your Skills in a Business CasePass the TensorFlow Developer Certification Exam by Google. Become an AI, Machine Learning, and Deep Learning expert!Google TensorFlow : Learn, Implement Deep Learning & master one of the cornerstone skills of a Data Scientist.Master Tensorflow 2.0, Google’s most powerful Machine Learning Library, with 5 advanced practical projectsMaster Tensorflow 2.0, Google’s most powerful Machine Learning Library, with 10 practical projectstensorflow2版本实战實作各種學習模型的實務應用程式,來學習Python非監督式學習吧!
連結UdemyUdemyUdemyUdemyUdemyUdemyUdemyUdemyUdemyUdemy



TensorFlow課程介紹

推薦的課程以倒序的方式呈現,越往下查看會看到越熱門的,期望您能找到滿意的學習主題!

10

動手做非監督式機器學習:使用TensorFlow 2.0

實作各種學習模型的實務應用程式,來學習Python非監督式學習吧!
NT$ 990
NT$ 470

點擊看Udemy

課程老師博碩文化 DrMaster
課程評價4.4 分(8 個評分)
課程時長2.5 小時
學生人數55 人

課程介紹

在當今的企業環境中,機器學習可以說是變得越來越重要了。它使用了監督式和非監督式的演算法,來解決各式各樣的商業問題。在非監督式學習中,AI人工智慧系統嘗試根據數據之間的「相似性」和「差異性」,來對「未標記」和「未分類」的數據進行分類。在這種情況下,和以「監督式學習」為基礎的功能相比,以模型為基礎的「非監督式學習方法」,其功能可以處理更複雜且更困難的問題。在本課程中,我們將研究不同的非監督式學習方法,並使用TensorFlow平台解決實際的問題。此外,使用TensorFlow解決現實世界中的問題,這

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哪些人適合這堂課?

  • 資料科學家
  • 資料分析師
  • 機器學習工程師
  • IT專案經理
  • 人工智慧從業人員

學習目標

  • TensorFlow 2.0
  • 實作各種非監督式學習演算法
  • 分群法Clustering
  • PCA主成分分析
  • DBN深度信念網絡
  • GAN生成對抗網路

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9

Python深度学习与Tensorflow2实战(2020新版)

tensorflow2版本实战
NT$ 3,190
NT$ 570

點擊看Udemy

課程老師唐宇迪 唐
課程評價4.3 分(55 個評分)
課程時長18 小時
學生人數391 人

課程介紹

课程主要包括两大模块(原理和实战),首先会通俗讲解深度学习中各大经典网络架构并基于tensorflow2版本进行实例演示,详解网络模型训练方法与策略。项目实战全部基于真实数据集与实际任务进行展开,零基础入门深度学习与TF框架并进行进阶提升!

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哪些人適合這堂課?

  • 人工智能深度学习方向的同学们

學習目標

  • Tensorflow基础操作
  • Tensorflow核心Api
  • 数据集制作方法
  • 图像数据与文本数据预处理实战
  • 图像识别模型构建
  • 文本分类模型构建
  • 神经网络基础
  • 卷积神经网络原理
  • 递归神经网络
  • 对抗生成网络架构及其实战
  • CycleGan图像融合
  • 基于Tensorflow构建各大经典网络模型
  • 基于TF的开源项目实战

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8

TensorFlow 2.0 Practical

Master Tensorflow 2.0, Google’s most powerful Machine Learning Library, with 10 practical projects
NT$ 2,690
NT$ 470

點擊看Udemy

課程老師Dr. Ryan Ahmed, Ph.D., MBA
課程評價4.7 分(551 個評分)
課程時長11.5 小時
學生人數4,927 人

課程介紹

Artificial Intelligence (AI) revolution is here and TensorFlow 2.0 is finally here to make it happen much faster! TensorFlow 2.0 is Google’s most powerful, recently released open source platform to build and deploy AI models in practice.

AI technolo

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哪些人適合這堂課?

  • Data Scientists who want to apply their knowledge on Real World Case Studies
  • AI Developers
  • AI Researchers

學習目標

  • Master Google’s newly released TensorFlow 2.0 to build, train, test and deploy Artificial Neural Networks (ANNs) models.
  • Learn how to develop ANNs models and train them in Google’s Colab while leveraging the power of GPUs and TPUs.
  • Deploy ANNs models in practice using TensorFlow 2.0 Serving.
  • Learn how to visualize models graph and assess their performance during training using Tensorboard.
  • Understand the underlying theory and mathematics behind Artificial Neural Networks and Convolutional Neural Networks (CNNs).
  • Learn how to train network weights and biases and select the proper transfer functions.
  • Train Artificial Neural Networks (ANNs) using back propagation and gradient descent methods.
  • Optimize ANNs hyper parameters such as number of hidden layers and neurons to enhance network performance.
  • Apply ANNs to perform regression tasks such as house prices predictions and sales/revenue predictions.
  • Assess the performance of trained ANN models for regression tasks using KPI (Key Performance indicators) such as Mean Absolute error, Mean squared Error, and Root Mean Squared Error, R-Squared, and Adjusted R-Squared.
  • Assess the performance of trained ANN models for classification tasks using KPI such as accuracy, precision and recall.
  • Apply Convolutional Neural Networks to classify images.
  • Sample real-world, practical projects:
  • Project #1: Train Simple ANN to convert Celsius temperature reading to Fahrenheit
  • Project #2 (Exercise): Train Feedforward ANN to predict Revenue/sales
  • Project #3: As a real-estate consultant, predict house prices using ANNs (Regression Task)
  • Project #4 (Exercise): As a business owner, predict Bike rental usage (Regression Task)
  • Project #5: Develop Artificial Neural Networks in the medical field to perform classification tasks such as diabetes detection (Classification task)
  • Project #6: Develop AI models to perform sentiment analysis and analyze online customer reviews.
  • Project #7: Train LeNet Deep Learning models to perform traffic signs classification.
  • Project #8: Train CNN to perform fashion classification
  • Project #9: Train CNN to perform image classification using Cifar-10 dataset
  • Project #10: Deploy deep learning image classification model using TF serving

關注這課程的人也購買了這些…

7

TensorFlow 2.0 Practical Advanced

Master Tensorflow 2.0, Google’s most powerful Machine Learning Library, with 5 advanced practical projects
NT$ 2,790
NT$ 470

點擊看Udemy

課程老師Dr. Ryan Ahmed, Ph.D., MBA
課程評價4.5 分(306 個評分)
課程時長12.5 小時
學生人數5,018 人

課程介紹

Google has recently released TensorFlow 2.0 which is Google’s most powerful open source platform to build and deploy AI models in practice. Tensorflow 2.0 release is a huge win for AI developers and enthusiast since it enabled the development of supe

瞭解更多細節

哪些人適合這堂課?

  • Data Scientists who want to apply their knowledge on Real World Case Studies
  • AI Developers
  • AI Researchers

學習目標

  • Build, train, test and deploy Advanced Artificial Neural Networks (ANNs) models using Google’s newly released TensorFlow 2.0.
  • Understand the underlying theory and mathematics behind Generative Adversarial Neural Networks (GANs).
  • Apply revolutionary GANs to generate brand new images using Keras API in TF 2.0.
  • Understand the underlying theory and mathematics behind Auto encoders and Variational Auto Encoders (VAEs).
  • Train and test Auto-Encoders to perform image compression and de-noising using Keras API in TF 2.0.
  • Understand the underlying theory and mathematics behind DeepDream algorithm. Develop, train, and test State-of-the art DeepDream algorithm to create AI-based art masterpieces using Keras API in TF 2.0!
  • Understand the intuition behind Long Short Term Memory (LSTM) Recurrent Neural Networks (RNNs).
  • Train Long Short Term Memory (LSTM) networks to generate new Shakespeare-style text using Keras API in TF 2.0!
  • Apply transfer learning to transfer knowledge from pre-trained MobileNet and ResNet networks to classify new images using TensorFlow 2.0 Hub.
  • Develop ANNs models and train them in Google’s Colab while leveraging the power of GPUs and TPUs.
  • Deploy AI models in practice using TensorFlow 2.0 Serving.

關注這課程的人也購買了這些…



6

Crash Course in Deep Learning with Google TensorFlow|Python

Google TensorFlow : Learn, Implement Deep Learning & master one of the cornerstone skills of a Data Scientist.
NT$ 990
NT$ 470

點擊看Udemy

課程老師UNP United Network of Professionals
課程評價4.9 分(266 個評分)
課程時長4 小時
學生人數8,662 人

課程介紹

This course lays a solid foundation to TensorFlow, a leading machine learning library from Google AI team. You’ll see how TensorFlow can create a range of machine learning models, custom deep neural networks to transfer learning models built by big t

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哪些人適合這堂課?

  • Anyone who wants to study and build neural networks and deep learning using Google Tensorflow

學習目標

  • TensorFlow installation
  • Different TensorFlow Environments
  • Computation graphs
  • Artificial Neural Networks (ANN)
  • Convolutional Neural networks (CNN)
  • Regularization in Neural Networks – Dropout and Max Pooling
  • Keras & TfLearn
  • Building a custom Image Classifier on ANY Dataset
  • Extensive Assignments :Test your Understanding & Periodic Updates on the Subject
  • Transfer learning and how to use Google inception

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5

TensorFlow Developer Certificate in 2021: Zero to Mastery

Pass the TensorFlow Developer Certification Exam by Google. Become an AI, Machine Learning, and Deep Learning expert!
NT$ 2,690
NT$ 470

點擊看Udemy

課程老師Andrei Neagoie
課程評價4.7 分(1,436 個評分)
課程時長63 小時
學生人數12,768 人

課程介紹

Just launched with all modern best practices for working with TensorFlow and passing the TensorFlow Developer Certificate exam! Join a live online community of over 500,000+ students and a course taught by a TensorFlow certified expert. This course w

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哪些人適合這堂課?

  • Anyone who wants to pass the TensorFlow Developer exam so they can join Google’s Certificate Network and display their certificate and badges on their resume, GitHub, and social media platforms including LinkedIn, making it easy to share their level of TensorFlow expertise with the world
  • Students, developers, and data scientists who want to demonstrate practical machine learning skills through the building and training of models using TensorFlow
  • Anyone looking to expand their knowledge when it comes to AI, Machine Learning and Deep Learning
  • Anyone looking to master building ML models with the latest version of TensorFlow

學習目標

  • Learn to pass Google’s official TensorFlow Developer Certificate exam (and add it to your resume)
  • Build TensorFlow models using Computer Vision, Convolutional Neural Networks and Natural Language Processing
  • Complete access to ALL interactive notebooks and ALL course slides as downloadable guides
  • Increase your skills in Machine Learning and Deep Learning, to test your abilities with the TensorFlow assessment exam
  • Understand how to integrate Machine Learning into tools and applications
  • Learn to build all types of Machine Learning Models using the latest TensorFlow 2
  • Build image recognition, object detection, text recognition algorithms with deep neural networks and convolutional neural networks
  • Using real world images to visualize the journey of an image through convolutions to understand how a computer “sees” information, plot loss and accuracy
  • Applying Deep Learning for Time Series Forecasting
  • Gain the skills you need to become a TensorFlow Certified Developer
  • Be recognized as a top candidate for recruiters seeking TensorFlow developers

關注這課程的人也購買了這些…



4

Deep Learning with TensorFlow 2.0 [2021]

Build Deep Learning Algorithms with TensorFlow 2.0, Dive into Neural Networks and Apply Your Skills in a Business Case
NT$ 2,790
NT$ 470

點擊看Udemy

課程老師365 Careers
課程評價4.7 分(2,112 個評分)
課程時長6 小時
學生人數18,752 人

課程介紹

Data scientists, machine learning engineers, and AI researchers all have their own skillsets. But what is that one special thing they have in common?

They are all masters of deep learning.

We often hear about AI, or self-driving cars, or the ‘algor

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哪些人適合這堂課?

  • Aspiring data scientists
  • People interested in Machine Learning, Deep Learning, Business, and Artificial Intelligence,
  • Anyone who wants to learn how to code and build machine and deep learning algorithms from scratch

學習目標

  • Gain a Strong Understanding of TensorFlow – Google’s Cutting-Edge Deep Learning Framework
  • Build Deep Learning Algorithms from Scratch in Python Using NumPy and TensorFlow
  • Set Yourself Apart with Hands-on Deep and Machine Learning Experience
  • Grasp the Mathematics Behind Deep Learning Algorithms
  • Understand Backpropagation, Stochastic Gradient Descent, Batching, Momentum, and Learning Rate Schedules
  • Know the Ins and Outs of Underfitting, Overfitting, Training, Validation, Testing, Early Stopping, and Initialization
  • Competently Carry Out Pre-Processing, Standardization, Normalization, and One-Hot Encoding

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3

Complete Tensorflow 2 and Keras Deep Learning Bootcamp

Learn to use Python for Deep Learning with Google’s latest Tensorflow 2 library and Keras!
NT$ 2,790
NT$ 490

點擊看Udemy

課程老師Jose Portilla
課程評價4.7 分(5,222 個評分)
課程時長19 小時
學生人數31,013 人

課程介紹

This course will guide you through how to use Google’s latest TensorFlow 2 framework to create artificial neural networks for deep learning! This course aims to give you an easy to understand guide to the complexities of Google’s TensorFlow 2 framewo

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哪些人適合這堂課?

  • Python developers interested in learning about TensorFlow 2 for deep learning and artificial intelligence

學習目標

  • Learn to use TensorFlow 2.0 for Deep Learning
  • Leverage the Keras API to quickly build models that run on Tensorflow 2
  • Perform Image Classification with Convolutional Neural Networks
  • Use Deep Learning for medical imaging
  • Forecast Time Series data with Recurrent Neural Networks
  • Use Generative Adversarial Networks (GANs) to generate images
  • Use deep learning for style transfer
  • Generate text with RNNs and Natural Language Processing
  • Serve Tensorflow Models through an API
  • Use GPUs for accelerated deep learning

關注這課程的人也購買了這些…



2

A Complete Guide on TensorFlow 2.0 using Keras API

Build Amazing Applications of Deep Learning and Artificial Intelligence in TensorFlow 2.0
NT$ 2,790
NT$ 470

點擊看Udemy

課程老師Hadelin de Ponteves
課程評價4.5 分(1,709 個評分)
課程時長13 小時
學生人數52,128 人

課程介紹

Welcome to Tensorflow 2.0!

TensorFlow 2.0 has just been released, and it introduced many features that simplify the model development and maintenance processes. From the educational side, it boosts people’s understanding by simplifying many compl

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哪些人適合這堂課?

  • Deep Learning Engineers who want to learn Tensorflow 2.0
  • Artificial Intelligence Engineers who want to expand their Deep Learning stack skills
  • Computer Scientists who want to enter the exciting area of Deep Learning and Artificial Intelligence
  • Data Scientists who want to take their AI Skills to the next level
  • AI experts who want to expand on the field of applications
  • Python Developers who want to enter the exciting area of Deep Learning and Artificial Intelligence
  • Engineers who work in technology and automation
  • Businessmen and companies who want to get ahead of the game
  • Students in tech-related programs who want to pursue a career in Data Science, Machine Learning, or Artificial Intelligence
  • Anyone passionate about Artificial Intelligence

學習目標

  • How to use Tensorflow 2.0 in Data Science
  • Important differences between Tensorflow 1.x and Tensorflow 2.0
  • How to implement Artificial Neural Networks in Tensorflow 2.0
  • How to implement Convolutional Neural Networks in Tensorflow 2.0
  • How to implement Recurrent Neural Networks in Tensorflow 2.0
  • How to build your own Transfer Learning application in Tensorflow 2.0
  • How to build a stock market trading bot using Reinforcement Learning (Deep-Q Network)
  • How to build Machine Learning Pipeline in Tensorflow 2.0
  • How to conduct Data Validation and Dataset Preprocessing using TensorFlow Data Validation and TensorFlow Transform.
  • Putting a TensorFlow 2.0 model into production
  • How to create a Fashion API with Flask and TensorFlow 2.0
  • How to serve a TensorFlow model with RESTful API

關注這課程的人也購買了這些…

1

Complete Guide to TensorFlow for Deep Learning with Python

Learn how to use Google’s Deep Learning Framework – TensorFlow with Python! Solve problems with cutting edge techniques!
NT$ 2,990
NT$ 490

點擊看Udemy

課程老師Jose Portilla
課程評價4.5 分(16,124 個評分)
課程時長14 小時
學生人數89,790 人

課程介紹

Welcome to the Complete Guide to TensorFlow for Deep Learning with Python!

This course will guide you through how to use Google’s TensorFlow framework to create artificial neural networks for deep learning! This course aims to give you an easy to u

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哪些人適合這堂課?

  • Python students eager to learn the latest Deep Learning Techniques with TensorFlow

學習目標

  • Understand how Neural Networks Work
  • Build your own Neural Network from Scratch with Python
  • Use TensorFlow for Classification and Regression Tasks
  • Use TensorFlow for Image Classification with Convolutional Neural Networks
  • Use TensorFlow for Time Series Analysis with Recurrent Neural Networks
  • Use TensorFlow for solving Unsupervised Learning Problems with AutoEncoders
  • Learn how to conduct Reinforcement Learning with OpenAI Gym
  • Create Generative Adversarial Networks with TensorFlow
  • Become a Deep Learning Guru!

關注這課程的人也購買了這些…



TensorFlow課程總覽

看完了一連串課程的介紹後,你是否還想要再一次進行課程總比較呢?

課程名稱Complete Guide to TensorFlow for Deep Learning with PythonA Complete Guide on TensorFlow 2.0 using Keras APIComplete Tensorflow 2 and Keras Deep Learning BootcampDeep Learning with TensorFlow 2.0 [2021]TensorFlow Developer Certificate in 2021: Zero to MasteryCrash Course in Deep Learning with Google TensorFlow|PythonTensorFlow 2.0 Practical AdvancedTensorFlow 2.0 PracticalPython深度学习与Tensorflow2实战(2020新版)動手做非監督式機器學習:使用TensorFlow 2.0
課程圖示
1

Complete Guide to TensorFlow for Deep Learning with Python

2

A Complete Guide on TensorFlow 2.0 using Keras API

3

Complete Tensorflow 2 and Keras Deep Learning Bootcamp

4

Deep Learning with TensorFlow 2.0 [2021]

5

TensorFlow Developer Certificate in 2021: Zero to Mastery

6

Crash Course in Deep Learning with Google TensorFlow|Python

7

TensorFlow 2.0 Practical Advanced

8

TensorFlow 2.0 Practical

9

Python深度学习与Tensorflow2实战(2020新版)

10

動手做非監督式機器學習:使用TensorFlow 2.0

課程原價NT$ 2,990NT$ 2,790NT$ 2,790NT$ 2,790NT$ 2,690NT$ 990NT$ 2,790NT$ 2,690NT$ 3,190NT$ 990
課程售價NT$ 490NT$ 470NT$ 490NT$ 470NT$ 470NT$ 470NT$ 470NT$ 470NT$ 570NT$ 470
課程評價(人數)4.5 分(16,124 個評分)4.5 分(1,709 個評分)4.7 分(5,222 個評分)4.7 分(2,112 個評分)4.7 分(1,436 個評分)4.9 分(266 個評分)4.5 分(306 個評分)4.7 分(551 個評分)4.3 分(55 個評分)4.4 分(8 個評分)
課程時長14 小時13 小時19 小時6 小時63 小時4 小時12.5 小時11.5 小時18 小時2.5 小時
學生人數89,790 人52,128 人31,013 人18,752 人12,768 人8,662 人5,018 人4,927 人391 人55 人
課程特色Learn how to use Google’s Deep Learning Framework – TensorFlow with Python! Solve problems with cutting edge techniques!Build Amazing Applications of Deep Learning and Artificial Intelligence in TensorFlow 2.0Learn to use Python for Deep Learning with Google’s latest Tensorflow 2 library and Keras!Build Deep Learning Algorithms with TensorFlow 2.0, Dive into Neural Networks and Apply Your Skills in a Business CasePass the TensorFlow Developer Certification Exam by Google. Become an AI, Machine Learning, and Deep Learning expert!Google TensorFlow : Learn, Implement Deep Learning & master one of the cornerstone skills of a Data Scientist.Master Tensorflow 2.0, Google’s most powerful Machine Learning Library, with 5 advanced practical projectsMaster Tensorflow 2.0, Google’s most powerful Machine Learning Library, with 10 practical projectstensorflow2版本实战實作各種學習模型的實務應用程式,來學習Python非監督式學習吧!
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從老師查找更多課程

以上推薦的課程還沒挑到自己有興趣的嗎?
還是您有熱衷某個老師開的課程呢?
本頁除了提供TensorFlow的課程以外,也列出這些課程所屬的老師的主要資訊頁,您可以從下列選單中了解更多相關介紹或看他們開的其他課程,期望您最終能找到自己想學習的項目。



【2022年】十大TensorFlow課程熱門排行推薦與優惠精選!

參考其他資料科學線上課程

除了本文介紹的課程種類以外,想要瞭解資料科學領域還有哪些不同類型的課程值得一探究竟嗎?讓您可以從不同面向更紮實的學習,點擊參考以下其他熱門主題文章。絕對提供您最優惠人氣滿檔的課程,歡迎繼續延伸閱讀。


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