39 Questions
What type of data is growing 50 times faster than other types according to the text?
Machine generated data
Which cloud service is specifically designed for time series and graph databases?
Timestream
In cloud computing, what does ETL stand for?
Extract, Transform, Load
Which AWS service is suitable for real-time data analytics?
Kinesis Data Analytics
What type of data is mentioned as examples of unstructured data in the text?
Audio, video, images
Which cloud service mentioned allows users to pay only for database access?
Amazon Aurora Serverless
What is one purpose of Glue in cloud computing as described in the text?
Data preparation automation
Which type of database is provided by Neptune among the AWS cloud data services?
Graph database
Which technique can be used for forecasting, time series modelling, and finding causal effect relationships between variables?
Negative Relationship (Social) Network Analysis
What does Sentiment Analysis primarily aim to do?
Identify customer sentiment towards products
Which algorithm is specifically mentioned as derived from Network Analysis?
Google Pagerank Algorithm
What is the main purpose of Emotion Detection Sentiment Analysis?
Interpreting and classifying emotions in text data
In which area is Aspect Based Sentiment Analysis commonly applied?
Identifying customer reviews sentiment
What does Degree Centrality measure in Network Analysis?
The influence or importance of a node within a network
What does Betweeness Centrality focus on in Network Analysis?
How often a node appears on the shortest paths between others
What is the primary goal of machine learning?
Predicting unknown values based on algorithms
Which term is sometimes used as a slang for machine learning applications?
Prediction machines
What do search engine algorithms monitor when refining search results?
User responses to search results
What does a virtual personal assistant do based on your previous interactions?
Collect and refine information
What does machine learning analyze to make predictions?
Relationships between data points
How are 'models' trained in machine learning?
Based on algorithms
What term is sometimes used to refer to machine learning applications predicting sales?
'Prediction machines'
How does a virtual personal assistant customize its results?
Recalling related queries from previous interactions
What is the primary goal of data analysis?
Searching large stores of data to discover patterns and trends
Which machine learning technique involves evaluating the probability of future events?
Regression Analysis
What does Regression Analysis investigate?
Relationship between a dependent and independent variable
Which technique involves classifying data into predefined categories?
Decision Trees
What is the purpose of Naive Bayes Analysis?
Classifying data into predefined categories
Which technique focuses on identifying relationships between variables?
Pattern Recognition
What does Outlier detection aim to identify?
Identifying unusual or rare data points in a dataset
Which technique focuses on segmenting data using complex mathematical algorithms?
Clustering Analysis
What technique does Pinterest use to recommend similar pins based on images?
Computer vision
Which Microsoft Azure option allows building ML models using a drag and drop interface with pre-configured models?
Azure cognitive services
What is the main benefit of using Azure cognitive services from Microsoft Azure?
Accessing intelligent features via APIs
In the context of Machine Learning, what is meant by 'Model Preparation & Training'?
Getting data ready and training ML models
Which social media platform uses face recognition technology to recognize friends in uploaded pictures?
What does the term 'Cloud options' refer to in the context of Microsoft Azure Machine Learning?
Training and deploying models using command line and Python
'Train ML models – data sub-set' as mentioned in the text refers to:
Preparing a subset of data for model training
'Typically models work on large data sets – data and compute intensive' implies that machine learning models usually require:
Scalable data and significant computing power
Test your knowledge on algorithms based on graph theory and their applications in network analysis. Explore concepts such as degree centrality, betweenness centrality, and clustering coefficient, commonly used in social media and Google pagerank algorithm.
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