Coursera - Supervised Machine Learning: Regression and Classification - Week 1 - Section 2 - Supervised vs. Unsupervised Machine Learning
2025年01月21日
If Arthur Samuel's checkers-playing program had been allowed to play only 10 games against itself, how would this have affected its performance compared to when it was allowed to play over 10,000 games?
Types of Supervised learning algorithms:
Supervised learning is when we give our learning algorithm the right answer y for each example to learn from. Which is an example of supervised learning?
For instance, emails labeled as "spam" or "not spam" are examples used for training a supervised learning algorithm. The trained algorithm will then be able to predict with some degree of accuracy whether an unseen email is spam or not.
clustering
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Types of unsupervised learning algorithms:
Of the following examples, which would you address using an unsupervised learning algorithm? (Check all that apply.)
1&3: This a type of unsupervised learning called clustering
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Week 1: Introduction to Machine Learning
Section 1: Supervised vs. Unsupervised Machine Learning
1. Video: What is machine learning?
If Arthur Samuel's checkers-playing program had been allowed to play only 10 games against itself, how would this have affected its performance compared to when it was allowed to play over 10,000 games?
- Would have made it worse
- Would have made it better
2. Video: Supervised learning part 1
Types of Supervised learning algorithms:
- Regression
- Classification
3. Video: Supervised learning part 2
Supervised learning is when we give our learning algorithm the right answer y for each example to learn from. Which is an example of supervised learning?
- Spam filtering.
- Calculating the average age of a group of customers.
For instance, emails labeled as "spam" or "not spam" are examples used for training a supervised learning algorithm. The trained algorithm will then be able to predict with some degree of accuracy whether an unseen email is spam or not.
4. Video: Unsupervised learning part 1
-clustering
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5. Video: Unsupervised learning part 2
Types of unsupervised learning algorithms:
- Clustering
- Anomaly detection
- Dimensionality reduction
Of the following examples, which would you address using an unsupervised learning algorithm? (Check all that apply.)
- Given a set of news articles found on the web, group them into sets of articles about the same stories.
- Given email labeled as spam/not spam, learn a spam filter.
- Given a database of customer data, automatically discover market segments and group customers into different market segments.
- Given a dataset of patients diagnosed as either having diabetes or not, learn to classify new patients as having diabetes or not.
1&3: This a type of unsupervised learning called clustering
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6. Video: Jupyter Notebooks
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7. Lab: Python and Jupyter Notebooks
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