4. Which of the following is true?以下哪一個説法正確？‘Deep Learning’ is a subfield of ‘Machine Learning’. 「深度學習」涵蓋於「機器學習」當中。‘Machine Learning’ is also known as ‘Deep Learning’. 「機器學習」是「深度學習」的另一種叫法。There is no relation among ‘AI’, ‘Machine Learning’ and ‘Deep Learning’.「人工智能」、「機器學習」和「深度學習」是三種沒有關係的概念。‘Machine Learning’ is a subfield of ‘Deep Learning’. 「機器學習」涵蓋於「深度學習」當中。

Please select the correct answer. 請選出正確答案。1. Which of the following is NOT a major sub-field of AI?以下哪樣不是人工智能的主要子領域？Deep Learning 深度學習Supervised Learning 監督學習Machine Learning 機器學習Electronic Learning 電子學習2. Which of the following statements is a correct description about strong AI and weak AI?以下哪個對強人工智能和弱人工智能的描述是正確的？Weak AI is a theoretical concept that does not yet exist. 弱人工智能至今仍屬理論性概念，現時並未在世上實現。Weak AI emulates human behaviours and understands the meaning of actions. 弱人工智能模擬人類的行為表現，並能理解動作本身的意義。The chess-playing computer program AlphaGo belongs to strong AI. 下棋電腦程式AlphaGo屬於強人工智能。Strong AI possesses self-consciousness and displays affective responses similar to those of human beings. 強人工智能擁有人類的自我意識和情感。3. Which of the following is true?以下哪一個説法正確？Only ‘feature’ is necessary in unsupervised learning. 非監督式學習只需用到「特徵」。Only ‘label’ is necessary in unsupervised learning. 非監督式學習只需用到「標籤」。Whether ‘feature’ and ‘label’ are necessary in unsupervised learning depends on different contexts and situations. 進行非監督式學習時，用到「標籤」和「特徵」與否取決於不同情況和背景。Both ‘label’ and ‘feature’ are necessary in unsupervised learning. 非監督式學習需用到「標籤」和「特徵」。4. Which of the following is true?以下哪一個説法正確？‘Deep Learning’ is a subfield of ‘Machine Learning’. 「深度學習」涵蓋於「機器學習」當中。‘Machine Learning’ is also known as ‘Deep Learning’. 「機器學習」是「深度學習」的另一種叫法。There is no relation among ‘AI’, ‘Machine Learning’ and ‘Deep Learning’.「人工智能」、「機器學習」和「深度學習」是三種沒有關係的概念。‘Machine Learning’ is a subfield of ‘Deep Learning’. 「機器學習」涵蓋於「深度學習」當中。

Machine learning is a subset of_________? a) Data Learning b) Deep Learning c) Artificial Intelligence d) None of the above

(6) Which of the following is true?以下哪一個説法正確？The inferred results generated by Machine Learning are always correct.機器學習推斷出的結果總是正確的。The inferred results generated by Machine Learning are usually accompanied with probabilities, which indicate the confidence of the inference.機器學習除了提供推斷結果之外，通常還會附上該推斷結果發生的機率。這個機率表示對該推斷結果的信心。Machine Leaning is able to infer an absolutely correct result in some situations, while in some other situations, it can only provide probabilities of different possible options.機器學習在某些情況下能夠作出絕對正確的推斷，某些情況卻只能計算不同選項的機率。Machine Learning is not able to make inference and provide probabilities of different possible options.機器學習既無法作出推斷，也無法給出不同可能選項的機率。

4. Which of the following statements about artificial neural networks is wrong?以下哪一個關於人工神經網路的描述是錯誤的？Back propagation is an important feature of neural networks: information from the output layer will be fed back to the hidden layers and the input layer to further improve the performance of the model. 反向傳播是神經網路的一個重要特徵：輸出層會將資料反向傳送囘隱藏層和輸入層，從而進一步改善神經網路的表現。There is always at least one output layer. 一定至少有一個輸出層。In a fully connected layer, all neurons are connected to all the other neurons in the previous layer and those in the next layer. 在全連接層中，所有神經元都會連接到上一層以及下一層中的所有其他神經元。There are always more input layers than hidden layers. 輸入層一定比隱藏層多。

Question 8Based on the terminology defined in Video 4, which of the following statements do you agree with? (Select all that apply.)1 pointThe terms “Machine learning” and “data science” are used almost interchangeably.Deep learning is a type of machine learning.  (I.e., all deep learning algorithms are machine learning algorithms.)AI is a type of deep learning. (I.e., all AI algorithms are deep learning algorithms.)The terms “Deep learning” and “neural network” are used almost interchangeably.