Podcast
Questions and Answers
Which machine learning technique would be the most promising to start with for predicting whether a person is likely to develop cancer based on medical history, diet, and heredity factors?
Which machine learning technique would be the most promising to start with for predicting whether a person is likely to develop cancer based on medical history, diet, and heredity factors?
Which of the following is an example of an unsupervised learning algorithm?
Which of the following is an example of an unsupervised learning algorithm?
Which of the following is NOT a machine learning technique?
Which of the following is NOT a machine learning technique?
What does the term ETL stand for?
What does the term ETL stand for?
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What does the term OLAP stand for?
What does the term OLAP stand for?
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What is a database where all the values for a particular column are stored contiguously called?
What is a database where all the values for a particular column are stored contiguously called?
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What is data mining?
What is data mining?
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In unsupervised learning, what is the role of the outcome variable?
In unsupervised learning, what is the role of the outcome variable?
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What is the primary goal of unsupervised learning?
What is the primary goal of unsupervised learning?
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Which type of learning is regression analysis an example of?
Which type of learning is regression analysis an example of?
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If you want to predict future sales based on historical customer data, which technique would be most appropriate?
If you want to predict future sales based on historical customer data, which technique would be most appropriate?
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What is the primary difference between supervised and unsupervised learning?
What is the primary difference between supervised and unsupervised learning?
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Study Notes
Data Mining and Machine Learning
- Data Mining is a process designed to detect patterns in data sets.
- Unsupervised learning does not involve building a statistical model for predicting or estimating an output based on inputs.
- In unsupervised learning, the learning algorithm is not trained using data attributes paired with an outcome variable.
Regression Analysis
- Regression analysis involves developing a model where one or more inputs are used to predict an output variable.
- Regression represents supervised learning.
Predicting Future Sales
- To predict future sales using a dataset with sales data for every customer over several years, the most appropriate technique to investigate is Regression.
Determining Cancer Likelihood
- To determine whether a person is likely to develop cancer using data including medical history, diet, and heredity factors, the most promising technique to start with is Classification.
Unsupervised Learning Algorithm
- K-Means is an example of an unsupervised learning algorithm.
Prediction Outcome Variable
- A prediction outcome variable does not have to be categorical.
Machine Learning Techniques
- Linear Components Analytics is not a machine learning technique.
- Regression, Clustering, and Neural Networks are machine learning techniques.
Bias in Supervised Learning
- In a supervised learning model, Bias does not refer to the error introduced from the assumptions of the data analyst.
Data Mining Objective
- The objective of Data Mining is to identify valid, novel, and potentially useful and understandable correlations and patterns in existing data.
NOSQL Analytics Database
- Cassandra is an example of a NOSQL Analytics database.
ETL
- ETL stands for Extract, Transform, Load.
Data Warehouse
- Unidimensional data is not stored in a star schema format in a data warehouse.
OLAP
- OLAP stands for Online Analytical Processing.
Column-oriented Storage
- A database where all values for a particular column are stored contiguously is called Column-oriented storage.
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Description
Test your knowledge on data mining and machine learning with this True or False quiz. Questions cover topics such as detecting patterns in data sets and unsupervised learning algorithms.
