【2022年】十大深度學習課程熱門排行推薦與優惠精選!

 

本文章推薦「Deep Learning A-Z™:人工神经网络实践」、「Deep Learning A-Z™: Hands-On Artificial Neural Networks」、「Complete Guide to TensorFlow for Deep Learning with Python」等相關深度學習線上課程,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。





深度學習課程總覽

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Deep Learning A-Z™: Hands-On Artificial Neural NetworksComplete Guide to TensorFlow for Deep Learning with PythonData Science: Deep Learning and Neural Networks in PythonNatural Language Processing with Deep Learning in PythonAdvanced AI: Deep Reinforcement Learning in PythonTensorflow 2.0: Deep Learning and Artificial IntelligenceDeep Learning: Convolutional Neural Networks in PythonDeep Learning: Advanced Computer Vision (GANs, SSD, +More!)Deep Learning: Advanced Natural Language Processing and RNNsDeep Learning A-Z™:人工神经网络实践
課程圖示
1

Deep Learning A-Z™: Hands-On Artificial Neural Networks

2

Complete Guide to TensorFlow for Deep Learning with Python

3

Data Science: Deep Learning and Neural Networks in Python

4

Natural Language Processing with Deep Learning in Python

5

Advanced AI: Deep Reinforcement Learning in Python

6

Tensorflow 2.0: Deep Learning and Artificial Intelligence

7

Deep Learning: Convolutional Neural Networks in Python

8

Deep Learning: Advanced Computer Vision (GANs, SSD, +More!)

9

Deep Learning: Advanced Natural Language Processing and RNNs

10

Deep Learning A-Z™:人工神经网络实践

課程原價NT$ 2,990NT$ 2,990NT$ 2,790NT$ 3,990NT$ 2,790NT$ 3,990NT$ 2,990NT$ 3,190
課程售價NT$ 530NT$ 490NT$ 470NT$ 1,390NT$ 990NT$ 690NT$ 470NT$ 690NT$ 530NT$ 530
課程評價(人數)4.6 分(38,080 個評分)4.5 分(16,124 個評分)4.6 分(7,609 個評分)4.5 分(6,548 個評分)4.6 分(4,022 個評分)4.6 分(5,733 個評分)4.6 分(3,730 個評分)4.6 分(4,035 個評分)4.6 分(3,621 個評分)4.3 分(121 個評分)
課程時長22.5 小時14 小時11 小時12 小時10.5 小時21.5 小時12 小時15 小時8.5 小時22.5 小時
學生人數313,427 人89,790 人47,032 人40,069 人33,337 人30,805 人27,356 人25,273 人21,274 人804 人
課程特色Learn to create Deep Learning Algorithms in Python from two Machine Learning & Data Science experts. Templates included.Learn how to use Google’s Deep Learning Framework – TensorFlow with Python! Solve problems with cutting edge techniques!The MOST in-depth look at neural network theory, and how to code one with pure Python and TensorflowComplete guide on deriving and implementing word2vec, GloVe, word embeddings, and sentiment analysis with recursive netsThe Complete Guide to Mastering Artificial Intelligence using Deep Learning and Neural NetworksNeural Networks for Computer Vision, Time Series Forecasting, NLP, GANs, Reinforcement Learning, and More!Use CNNs for Image Recognition, Natural Language Processing (NLP) +More! For Data Science, Machine Learning, and AIVGG, ResNet, Inception, SSD, RetinaNet, Neural Style Transfer, GANs +More in Tensorflow, Keras, and PythonNatural Language Processing (NLP) with Sequence-to-sequence (seq2seq), Attention, CNNs, RNNs, and Memory Networks!跟着两位机器学习与数据科学专家,学习用Python创建深度学习算法。包含模板。(英文原音)
連結UdemyUdemyUdemyUdemyUdemyUdemyUdemyUdemyUdemyUdemy



深度學習課程介紹

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

Deep Learning A-Z™:人工神经网络实践

跟着两位机器学习与数据科学专家,学习用Python创建深度学习算法。包含模板。(英文原音)
NT$ 3,190
NT$ 530

點擊看Udemy

課程老師Kirill Eremenko
課程評價4.3 分(121 個評分)
課程時長22.5 小時
學生人數804 人

課程介紹

*** 如Kickstarter所示 ***

人工智能正呈指数级增长。这点毫无疑问。自动驾驶汽车的驾驶里程已经能够达到数百万英里,IBM Watson对患者的诊断比许多医生都好,谷歌Deepmind的AlphaGo在Go上击败了世界围棋冠军 – 围棋是一种直觉起着关键作用的游戏。

但是,随着人工智能的进一步发展,需要解决的问题就越复杂。只有深度学习可以解决这些复杂的问题,这就是为什么它是人工智能的核心。

— 为什么选择Deep Learning A-Z?—

以下是我们认为Deep

瞭解更多細節

哪些人適合這堂課?

  • 对深度学习感兴趣的人
  • 至少具有高中数学知识并希望开始进行深度学习的学生
  • 任何了解机器学习或深度学习基础知识(包括线性回归或逻辑回归等经典算法以及人工神经网络等更高级的主题),但希望了解更多知识并探索深度学习所有不同领域的中级水平人士
  • 任何对编码不甚熟悉但对深度学习感兴趣并希望在数据集上轻松应用深度学习的人士
  • 任何想要开始从事数据科学职业的在校大学生
  • 任何想要在深度学习中更上一层楼的数据分析师
  • 任何对自己的工作不满意并希望成为数据科学家的人士
  • 任何想要通过使用强大的深度学习工具为其业务创造附加价值的人士
  • 任何想要了解如何在其企业中利用深度学习的指数技术的企业主
  • 任何希望利用最前沿的深度学习算法颠覆行业认知的企业家

學習目標

  • 理解人工神经网络背后的直觉
  • 在实践中应用人工神经网络
  • 理解卷积神经网络背后的直觉
  • 在实践中应用卷积神经网络
  • 理解递归神经网络背后的直觉
  • 在实践中应用递归神经网络
  • 理解自组织映射背后的直觉
  • 在实践中应用自组织映射
  • 理解玻尔兹曼机背后的直觉
  • 在实践中应用玻尔兹曼机
  • 理解自编码器背后的直觉
  • 在实践中应用自编码器

關注這課程的人也購買了這些…

9

Deep Learning: Advanced Natural Language Processing and RNNs

Natural Language Processing (NLP) with Sequence-to-sequence (seq2seq), Attention, CNNs, RNNs, and Memory Networks!
NT$ 2,990
NT$ 530

點擊看Udemy

課程老師Lazy Programmer Inc.
課程評價4.6 分(3,621 個評分)
課程時長8.5 小時
學生人數21,274 人

課程介紹

It’s hard to believe it’s been been over a year since I released my first course on Deep Learning with NLP (natural language processing).

A lot of cool stuff has happened since then, and I’ve been deep in the trenches learning, researching, and accu

瞭解更多細節

哪些人適合這堂課?

  • Students in machine learning, deep learning, artificial intelligence, and data science
  • Professionals in machine learning, deep learning, artificial intelligence, and data science
  • Anyone interested in state-of-the-art natural language processing

學習目標

  • Build a text classification system (can be used for spam detection, sentiment analysis, and similar problems)
  • Build a neural machine translation system (can also be used for chatbots and question answering)
  • Build a sequence-to-sequence (seq2seq) model
  • Build an attention model
  • Build a memory network (for question answering based on stories)

關注這課程的人也購買了這些…



8

Deep Learning: Advanced Computer Vision (GANs, SSD, +More!)

VGG, ResNet, Inception, SSD, RetinaNet, Neural Style Transfer, GANs +More in Tensorflow, Keras, and Python
NT$ 3,990
NT$ 690

點擊看Udemy

課程老師Lazy Programmer Inc.
課程評價4.6 分(4,035 個評分)
課程時長15 小時
學生人數25,273 人

課程介紹

Latest update: Instead of SSD, I show you how to use RetinaNet, which is better and more modern. I show you both how to use a pretrained model and how to train one yourself with a custom dataset on Google Colab.

This is one of the most exciting cour

瞭解更多細節

哪些人適合這堂課?

  • Students and professionals who want to take their knowledge of computer vision and deep learning to the next level
  • Anyone who wants to learn about object detection algorithms like SSD and YOLO
  • Anyone who wants to learn how to write code for neural style transfer
  • Anyone who wants to use transfer learning
  • Anyone who wants to shorten training time and build state-of-the-art computer vision nets fast

學習目標

  • Understand and apply transfer learning
  • Understand and use state-of-the-art convolutional neural nets such as VGG, ResNet and Inception
  • Understand and use object detection algorithms like SSD
  • Understand and apply neural style transfer
  • Understand state-of-the-art computer vision topics
  • Class Activation Maps
  • GANs (Generative Adversarial Networks)
  • Object Localization Implementation Project

關注這課程的人也購買了這些…

7

Deep Learning: Convolutional Neural Networks in Python

Use CNNs for Image Recognition, Natural Language Processing (NLP) +More! For Data Science, Machine Learning, and AI
NT$ 2,790
NT$ 470

點擊看Udemy

課程老師Lazy Programmer Inc.
課程評價4.6 分(3,730 個評分)
課程時長12 小時
學生人數27,356 人

課程介紹

*** NOW IN TENSORFLOW 2 and PYTHON 3 ***

Learn about one of the most powerful Deep Learning architectures yet!

The Convolutional Neural Network (CNN) has been used to obtain state-of-the-art results in computer vision tasks such as object detection

瞭解更多細節

哪些人適合這堂課?

  • Students, professionals, and anyone else interested in Deep Learning, Computer Vision, or NLP
  • Software Engineers and Data Scientists who want to level up their career

學習目標

  • Understand convolution and why it’s useful for Deep Learning
  • Understand and explain the architecture of a convolutional neural network (CNN)
  • Implement a CNN in TensorFlow 2
  • Apply CNNs to challenging Image Recognition tasks
  • Apply CNNs to Natural Language Processing (NLP) for Text Classification (e.g. Spam Detection, Sentiment Analysis)

關注這課程的人也購買了這些…



6

Tensorflow 2.0: Deep Learning and Artificial Intelligence

Neural Networks for Computer Vision, Time Series Forecasting, NLP, GANs, Reinforcement Learning, and More!
NT$ 3,990
NT$ 690

點擊看Udemy

課程老師Lazy Programmer Inc.
課程評價4.6 分(5,733 個評分)
課程時長21.5 小時
學生人數30,805 人

課程介紹

Welcome to Tensorflow 2.0!

What an exciting time. It’s been nearly 4 years since Tensorflow was released, and the library has evolved to its official second version.

Tensorflow is Google’s library for deep learning and artificial intelligence.

瞭解更多細節

哪些人適合這堂課?

  • Beginners to advanced students who want to learn about deep learning and AI in Tensorflow 2.0

學習目標

  • Artificial Neural Networks (ANNs) / Deep Neural Networks (DNNs)
  • Predict Stock Returns
  • Time Series Forecasting
  • Computer Vision
  • How to build a Deep Reinforcement Learning Stock Trading Bot
  • GANs (Generative Adversarial Networks)
  • Recommender Systems
  • Image Recognition
  • Convolutional Neural Networks (CNNs)
  • Recurrent Neural Networks (RNNs)
  • Use Tensorflow Serving to serve your model using a RESTful API
  • Use Tensorflow Lite to export your model for mobile (Android, iOS) and embedded devices
  • Use Tensorflow’s Distribution Strategies to parallelize learning
  • Low-level Tensorflow, gradient tape, and how to build your own custom models
  • Natural Language Processing (NLP) with Deep Learning
  • Demonstrate Moore’s Law using Code
  • Transfer Learning to create state-of-the-art image classifiers

關注這課程的人也購買了這些…

5

Advanced AI: Deep Reinforcement Learning in Python

The Complete Guide to Mastering Artificial Intelligence using Deep Learning and Neural Networks
NT$ 990

點擊看Udemy

課程老師Lazy Programmer Team
課程評價4.6 分(4,022 個評分)
課程時長10.5 小時
學生人數33,337 人

課程介紹

This course is all about the application of deep learning and neural networks to reinforcement learning.

If you’ve taken my first reinforcement learning class, then you know that reinforcement learning is on the bleeding edge of what we can do with

瞭解更多細節

哪些人適合這堂課?

  • Professionals and students with strong technical backgrounds who wish to learn state-of-the-art AI techniques

學習目標

  • Build various deep learning agents (including DQN and A3C)
  • Apply a variety of advanced reinforcement learning algorithms to any problem
  • Q-Learning with Deep Neural Networks
  • Policy Gradient Methods with Neural Networks
  • Reinforcement Learning with RBF Networks
  • Use Convolutional Neural Networks with Deep Q-Learning

關注這課程的人也購買了這些…



4

Natural Language Processing with Deep Learning in Python

Complete guide on deriving and implementing word2vec, GloVe, word embeddings, and sentiment analysis with recursive nets
NT$ 1,390

點擊看Udemy

課程老師Lazy Programmer Team
課程評價4.5 分(6,548 個評分)
課程時長12 小時
學生人數40,069 人

課程介紹

In this course we are going to look at NLP (natural language processing) with deep learning.

Previously, you learned about some of the basics, like how many NLP problems are just regular machine learning and data science problems in disguise, and si

瞭解更多細節

哪些人適合這堂課?

  • Students and professionals who want to create word vector representations for various NLP tasks
  • Students and professionals who are interested in state-of-the-art neural network architectures like recursive neural networks
  • SHOULD NOT: Anyone who is not comfortable with the prerequisites.

學習目標

  • Understand and implement word2vec
  • Understand the CBOW method in word2vec
  • Understand the skip-gram method in word2vec
  • Understand the negative sampling optimization in word2vec
  • Understand and implement GloVe using gradient descent and alternating least squares
  • Use recurrent neural networks for parts-of-speech tagging
  • Use recurrent neural networks for named entity recognition
  • Understand and implement recursive neural networks for sentiment analysis
  • Understand and implement recursive neural tensor networks for sentiment analysis
  • Use Gensim to obtain pretrained word vectors and compute similarities and analogies

關注這課程的人也購買了這些…

3

Data Science: Deep Learning and Neural Networks in Python

The MOST in-depth look at neural network theory, and how to code one with pure Python and Tensorflow
NT$ 2,790
NT$ 470

點擊看Udemy

課程老師Lazy Programmer Inc.
課程評價4.6 分(7,609 個評分)
課程時長11 小時
學生人數47,032 人

課程介紹

This course will get you started in building your FIRST artificial neural network using deep learning techniques. Following my previous course on logistic regression, we take this basic building block, and build full-on non-linear neural networks rig

瞭解更多細節

哪些人適合這堂課?

  • Students interested in machine learning – you’ll get all the tidbits you need to do well in a neural networks course
  • Professionals who want to use neural networks in their machine learning and data science pipeline. Be able to apply more powerful models, and know its drawbacks.

學習目標

  • Learn how Deep Learning REALLY works (not just some diagrams and magical black box code)
  • Learn how a neural network is built from basic building blocks (the neuron)
  • Code a neural network from scratch in Python and numpy
  • Code a neural network using Google’s TensorFlow
  • Describe different types of neural networks and the different types of problems they are used for
  • Derive the backpropagation rule from first principles
  • Create a neural network with an output that has K > 2 classes using softmax
  • Describe the various terms related to neural networks, such as “activation”, “backpropagation” and “feedforward”
  • Install TensorFlow

關注這課程的人也購買了這些…



2

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

瞭解更多細節

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…

1

Deep Learning A-Z™: Hands-On Artificial Neural Networks

Learn to create Deep Learning Algorithms in Python from two Machine Learning & Data Science experts. Templates included.
NT$ 2,990
NT$ 530

點擊看Udemy

課程老師Kirill Eremenko
課程評價4.6 分(38,080 個評分)
課程時長22.5 小時
學生人數313,427 人

課程介紹

*** As seen on Kickstarter ***

Artificial intelligence is growing exponentially. There is no doubt about that. Self-driving cars are clocking up millions of miles, IBM Watson is diagnosing patients better than armies of doctors and Google Deepmind’s

瞭解更多細節

哪些人適合這堂課?

  • Anyone interested in Deep Learning
  • Students who have at least high school knowledge in math and who want to start learning Deep Learning
  • Any intermediate level people who know the basics of Machine Learning or Deep Learning, including the classical algorithms like linear regression or logistic regression and more advanced topics like Artificial Neural Networks, but who want to learn more about it and explore all the different fields of Deep Learning
  • Anyone who is not that comfortable with coding but who is interested in Deep Learning and wants to apply it easily on datasets
  • Any students in college who want to start a career in Data Science
  • Any data analysts who want to level up in Deep Learning
  • Any people who are not satisfied with their job and who want to become a Data Scientist
  • Any people who want to create added value to their business by using powerful Deep Learning tools
  • Any business owners who want to understand how to leverage the Exponential technology of Deep Learning in their business
  • Any Entrepreneur who wants to create disruption in an industry using the most cutting edge Deep Learning algorithms

學習目標

  • Understand the intuition behind Artificial Neural Networks
  • Apply Artificial Neural Networks in practice
  • Understand the intuition behind Convolutional Neural Networks
  • Apply Convolutional Neural Networks in practice
  • Understand the intuition behind Recurrent Neural Networks
  • Apply Recurrent Neural Networks in practice
  • Understand the intuition behind Self-Organizing Maps
  • Apply Self-Organizing Maps in practice
  • Understand the intuition behind Boltzmann Machines
  • Apply Boltzmann Machines in practice
  • Understand the intuition behind AutoEncoders
  • Apply AutoEncoders in practice

關注這課程的人也購買了這些…



深度學習課程總覽

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Deep Learning A-Z™: Hands-On Artificial Neural NetworksComplete Guide to TensorFlow for Deep Learning with PythonData Science: Deep Learning and Neural Networks in PythonNatural Language Processing with Deep Learning in PythonAdvanced AI: Deep Reinforcement Learning in PythonTensorflow 2.0: Deep Learning and Artificial IntelligenceDeep Learning: Convolutional Neural Networks in PythonDeep Learning: Advanced Computer Vision (GANs, SSD, +More!)Deep Learning: Advanced Natural Language Processing and RNNsDeep Learning A-Z™:人工神经网络实践
課程圖示
1

Deep Learning A-Z™: Hands-On Artificial Neural Networks

2

Complete Guide to TensorFlow for Deep Learning with Python

3

Data Science: Deep Learning and Neural Networks in Python

4

Natural Language Processing with Deep Learning in Python

5

Advanced AI: Deep Reinforcement Learning in Python

6

Tensorflow 2.0: Deep Learning and Artificial Intelligence

7

Deep Learning: Convolutional Neural Networks in Python

8

Deep Learning: Advanced Computer Vision (GANs, SSD, +More!)

9

Deep Learning: Advanced Natural Language Processing and RNNs

10

Deep Learning A-Z™:人工神经网络实践

課程原價NT$ 2,990NT$ 2,990NT$ 2,790NT$ 3,990NT$ 2,790NT$ 3,990NT$ 2,990NT$ 3,190
課程售價NT$ 530NT$ 490NT$ 470NT$ 1,390NT$ 990NT$ 690NT$ 470NT$ 690NT$ 530NT$ 530
課程評價(人數)4.6 分(38,080 個評分)4.5 分(16,124 個評分)4.6 分(7,609 個評分)4.5 分(6,548 個評分)4.6 分(4,022 個評分)4.6 分(5,733 個評分)4.6 分(3,730 個評分)4.6 分(4,035 個評分)4.6 分(3,621 個評分)4.3 分(121 個評分)
課程時長22.5 小時14 小時11 小時12 小時10.5 小時21.5 小時12 小時15 小時8.5 小時22.5 小時
學生人數313,427 人89,790 人47,032 人40,069 人33,337 人30,805 人27,356 人25,273 人21,274 人804 人
課程特色Learn to create Deep Learning Algorithms in Python from two Machine Learning & Data Science experts. Templates included.Learn how to use Google’s Deep Learning Framework – TensorFlow with Python! Solve problems with cutting edge techniques!The MOST in-depth look at neural network theory, and how to code one with pure Python and TensorflowComplete guide on deriving and implementing word2vec, GloVe, word embeddings, and sentiment analysis with recursive netsThe Complete Guide to Mastering Artificial Intelligence using Deep Learning and Neural NetworksNeural Networks for Computer Vision, Time Series Forecasting, NLP, GANs, Reinforcement Learning, and More!Use CNNs for Image Recognition, Natural Language Processing (NLP) +More! For Data Science, Machine Learning, and AIVGG, ResNet, Inception, SSD, RetinaNet, Neural Style Transfer, GANs +More in Tensorflow, Keras, and PythonNatural Language Processing (NLP) with Sequence-to-sequence (seq2seq), Attention, CNNs, RNNs, and Memory Networks!跟着两位机器学习与数据科学专家,学习用Python创建深度学习算法。包含模板。(英文原音)
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