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Merge pull request #216759 from aahill/bigdata-update
removing bing content
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‎articles/cognitive-services/big-data/samples-python.md

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manager: nitinme
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ms.service: cognitive-services
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ms.topic: sample
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ms.date: 08/16/2022
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ms.date: 11/01/2022
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ms.author: marhamil
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ms.devlang: python
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---
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- Language service - get the sentiment (or mood) of a set of sentences.
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- Computer Vision - get the tags (one-word descriptions) associated with a set of images.
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- Bing Image Search - search the web for images related to a natural language query.
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- Speech-to-text - transcribe audio files to extract text-based transcripts.
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- Anomaly Detector - detect anomalies within a time series data.
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# A general Cognitive Services key for the Language service and Computer Vision (or use separate keys that belong to each service)
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service_key = "ADD_YOUR_SUBSCRIPION_KEY"
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# A Bing Search v7 subscription key
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bing_search_key = "ADD_YOUR_SUBSCRIPION_KEY"
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# An Anomaly Dectector subscription key
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anomaly_key = "ADD_YOUR_SUBSCRIPION_KEY"
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| https://raw.githubusercontent.com/Azure-Samples/cognitive-services-sample-data-files/master/ComputerVision/Images/house.jpg | ['outdoor' 'grass' 'house' 'building' 'old' 'home' 'front' 'small' 'church' 'stone' 'large' 'grazing' 'yard' 'green' 'sitting' 'leading' 'sheep' 'brick' 'bench' 'street' 'white' 'country' 'clock' 'sign' 'parked' 'field' 'standing' 'garden' 'water' 'red' 'horse' 'man' 'tall' 'fire' 'group']
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## Bing Image Search sample
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[Bing Image Search](../bing-image-search/overview.md) searches the web to retrieve images related to a user's natural language query. In this sample, we use a text query that looks for images with quotes. It returns a list of image URLs that contain photos related to our query.
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```python
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from pyspark.ml import PipelineModel
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# Number of images Bing will return per query
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imgsPerBatch = 10
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# A list of offsets, used to page into the search results
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offsets = [(i*imgsPerBatch,) for i in range(100)]
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# Since web content is our data, we create a dataframe with options on that data: offsets
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bingParameters = spark.createDataFrame(offsets, ["offset"])
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# Run the Bing Image Search service with our text query
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bingSearch = (BingImageSearch()
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.setSubscriptionKey(bing_search_key)
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.setOffsetCol("offset")
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.setQuery("Martin Luther King Jr. quotes")
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.setCount(imgsPerBatch)
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.setOutputCol("images"))
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# Transformer that extracts and flattens the richly structured output of Bing Image Search into a simple URL column
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getUrls = BingImageSearch.getUrlTransformer("images", "url")
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# This displays the full results returned, uncomment to use
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# display(bingSearch.transform(bingParameters))
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# Since we have two services, they are put into a pipeline
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pipeline = PipelineModel(stages=[bingSearch, getUrls])
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# Show the results of your search: image URLs
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display(pipeline.transform(bingParameters))
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```
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### Expected result
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| url |
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|:-------------------------------------------------------------------------------------------------------------------|
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| https://iheartintelligence.com/wp-content/uploads/2019/01/powerful-quotes-martin-luther-king-jr.jpg |
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| http://everydaypowerblog.com/wp-content/uploads/2014/01/Martin-Luther-King-Jr.-Quotes-16.jpg |
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| http://www.sofreshandsogreen.com/wp-content/uploads/2012/01/martin-luther-king-jr-quote-sofreshandsogreendotcom.jpg |
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| https://everydaypowerblog.com/wp-content/uploads/2014/01/Martin-Luther-King-Jr.-Quotes-18.jpg |
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| https://tsal-eszuskq0bptlfh8awbb.stackpathdns.com/wp-content/uploads/2018/01/MartinLutherKingQuotes.jpg |
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## Speech-to-Text sample
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The [Speech-to-text](../speech-service/index-speech-to-text.yml) service converts streams or files of spoken audio to text. In this sample, we transcribe two audio files. The first file is easy to understand, and the second is more challenging.
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‎articles/cognitive-services/big-data/samples-scala.md

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@@ -6,7 +6,7 @@ author: mhamilton723
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manager: nitinme
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ms.service: cognitive-services
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ms.topic: sample
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ms.date: 10/28/2021
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ms.date: 11/01/2022
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ms.author: marhamil
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ms.devlang: scala
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---
@@ -19,7 +19,6 @@ The samples use these Cognitive Services:
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- Language service - get the sentiment (or mood) of a set of sentences.
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- Computer Vision - get the tags (one-word descriptions) associated with a set of images.
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- Bing Image Search - search the web for images related to a natural language query.
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- Speech-to-text - transcribe audio files to extract text-based transcripts.
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- Anomaly Detector - detect anomalies within a time series data.
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| https://raw.githubusercontent.com/Azure-Samples/cognitive-services-sample-data-files/master/ComputerVision/Images/dog.jpg | ['dog' 'outdoor' 'fence' 'wooden' 'small' 'brown' 'building' 'sitting' 'front' 'bench' 'standing' 'table' 'walking' 'board' 'beach' 'white' 'holding' 'bridge' 'track']
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| https://raw.githubusercontent.com/Azure-Samples/cognitive-services-sample-data-files/master/ComputerVision/Images/house.jpg | ['outdoor' 'grass' 'house' 'building' 'old' 'home' 'front' 'small' 'church' 'stone' 'large' 'grazing' 'yard' 'green' 'sitting' 'leading' 'sheep' 'brick' 'bench' 'street' 'white' 'country' 'clock' 'sign' 'parked' 'field' 'standing' 'garden' 'water' 'red' 'horse' 'man' 'tall' 'fire' 'group']
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## Bing Image Search
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[Bing Image Search](../bing-image-search/overview.md) searches the web to retrieve images related to a user's natural language query. In this sample, we use a text query that looks for images with quotes. It returns a list of image URLs that contain photos related to our query.
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```scala
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import org.apache.spark.ml.Pipeline
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// Number of images Bing will return per query
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val imgsPerBatch = 10
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// A list of offsets, used to page into the search results
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val df = (0 until 100).map(o => Tuple1(o*imgsPerBatch)).toSeq.toDF("offset")
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// Run the Bing Image Search service with our text query
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val bingSearch = new BingImageSearch()
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.setSubscriptionKey(bingSearchKey)
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.setOffsetCol("offset")
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.setQuery("Martin Luther King Jr. quotes")
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.setCount(imgsPerBatch)
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.setOutputCol("images")
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// Transformer that extracts and flattens the richly structured output of Bing Image Search into a simple URL column
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val getUrls = BingImageSearch.getUrlTransformer("images", "url")
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// This displays the full results returned, uncomment to use
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// display(bingSearch.transform(bingParameters))
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// Since we have two services, they are put into a pipeline
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val pipeline = new Pipeline().setStages(Array(bingSearch, getUrls))
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// Show the results of your search: image URLs
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display(pipeline.fit(df).transform(df))
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```
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### Expected result
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| url |
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|:-------------------------------------------------------------------------------------------------------------------|
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| https://iheartintelligence.com/wp-content/uploads/2019/01/powerful-quotes-martin-luther-king-jr.jpg |
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| http://everydaypowerblog.com/wp-content/uploads/2014/01/Martin-Luther-King-Jr.-Quotes-16.jpg |
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| http://www.sofreshandsogreen.com/wp-content/uploads/2012/01/martin-luther-king-jr-quote-sofreshandsogreendotcom.jpg |
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| https://everydaypowerblog.com/wp-content/uploads/2014/01/Martin-Luther-King-Jr.-Quotes-18.jpg |
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| https://tsal-eszuskq0bptlfh8awbb.stackpathdns.com/wp-content/uploads/2018/01/MartinLutherKingQuotes.jpg |
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## Speech-to-Text
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The [Speech-to-text](../speech-service/index-speech-to-text.yml) service converts streams or files of spoken audio to text. In this sample, we transcribe two audio files. The first file is easy to understand, and the second is more challenging.

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