Term
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Definition
A false positive is an error in binary classification in which a test result incorrectly indicates the presence of a condition (such as a disease when the disease is not present). They are also called a "Type II error"
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- https://en.wikipedia.org/wiki/False_positives_and_false_negatives |
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Term
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Definition
A false negative is the opposite error, where the test result incorrectly indicates the absence of a condition when it is actually present. They are also called a "Type I error"
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https://en.wikipedia.org/wiki/False_positives_and_false_negatives |
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Term
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Definition
Used in supervised learning (*generally*) to visualize your model's performance.
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- https://en.wikipedia.org/wiki/Confusion_matrix |
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Term
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Definition
F-score or F-measure is a measure of a test's accuracy. It is calculated from the precision and recall of the test, where the precision is the number of true positive results divided by the number of all positive results, including those not identified correctly, and the recall is the number of true positive results divided by the number of all samples that should have been identified as positive.
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- https://en.wikipedia.org/wiki/F-score |
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Term
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Definition
| Amazon Kinesis is a significant feature in AWS for easy collection, processing, and analysis of video and data streams in real-time environments |
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Term
| What are AWS Kinesis Data Streams |
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Definition
- real-time data streaming service
- high scalability and durability
- capturing multiple gigabytes of data every second from multiple sources
- can be configuring storage for one to seven days |
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Term
| What is AWS Kinesis Data Firehose |
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Definition
Load data streams into AWS data stores. - Simplest approach for capturing, transforming, and loading data streams into AWS data stores.
- No option for data storage. |
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Term
Data stream vs Data Firehose
- What are the objectives? |
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Definition
DS = streaming and data ingestion at scale
DF = Data transfer service for loading streaming data into Amazon S3, Splunk, ElasticSearch, and RedShift |
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