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Wednesday, November 20, 2024

Assignment #11 due 12/6/24

  Using the Codelab on Sentiment Analysis




Take any paragraph of text and score it for sentiment and entity recognition.

Send me the output via email

Example

text = """Artificial intelligence may be one of the biggest technological leaps in history. It is poised to unlock new business models, transform industries, reshape people’s jobs, and boost economic productivity. Goldman Sachs is uniquely positioned to understand this fast-moving revolution. With our research across markets as well as our work with clients, we aim to provide meaningful analysis of this radical change and its implications for investors, companies, and the global economy."""


results


In [16]: show_text_sentiment(analyze_sentiment_response)

At sentence level:
   score | sentence
---------+--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
    +0.5 | Artificial intelligence may be one of the biggest technological leaps in history.
    +0.2 | It is poised to unlock new business models, transform industries, reshape people’s jobs, and boost economic productivity.
    +0.3 | Goldman Sachs is uniquely positioned to understand this fast-moving revolution.
    +0.4 | With our research across markets as well as our work with clients, we aim to provide meaningful analysis of this radical change and its implications for investors, companies, and the global economy.

At document level:
   score |   magnitude | language
---------+-------------+------------
    +0.4 |        +1.6 | en

In [17]:

for name

In [20]: show_text_entities(analyze_entities_response)
 name                    | type          |   salience | mid       | wikipedia_url
-------------------------+---------------+------------+-----------+---------------------------------------------
 Artificial intelligence | OTHER         |        22% |           |
 one                     | PERSON        |        22% |           |
 leaps                   | OTHER         |        18% |           |
 history                 | OTHER         |         7% |           |
 business models         | CONSUMER_GOOD |         3% |           |
 analysis                | OTHER         |         3% |           |
 productivity            | OTHER         |         2% |           |
 industries              | OTHER         |         2% |           |
 jobs                    | OTHER         |         2% |           |
 people                  | PERSON        |         2% |           |
 revolution              | OTHER         |         2% |           |
 research                | OTHER         |         2% |           |
 markets                 | OTHER         |         2% |           |
 change                  | OTHER         |         2% |           |
 implications            | OTHER         |         2% |           |
 Goldman Sachs           | ORGANIZATION  |         1% | /m/01xdn1 | https://en.wikipedia.org/wiki/Goldman_Sachs
 investors               | PERSON        |         1% |           |
 companies               | ORGANIZATION  |         1% |           |
 economy                 | OTHER         |         1% |           |
 work                    | OTHER         |         1% |           |
 clients                 | PERSON        |         1% |           |
 one                     | NUMBER        |         0% |           |

Wednesday, November 13, 2024

Assignment #10 due 11/22/24

  Assignment #10 due 11/22/24


https://uconnstamfordslp.blogspot.com/p/vision-example-explained.html

Load 5 python programs that will use Google Vision API to scan 5
separate images.


Note: need to use your own images and store them on your Google Storage Bucket

Download images from internet and store on your cloud storage bucket.

image_uri = 'gs://cloud-samples-data/vision/using_curl/shanghai.jpeg'

Example image_uri = "gs://jiacovacci/knicks.jpg"

Using text detect

'sphere\nNYC\nNEW YORK\n30\nNYC'           | (224,171),(403,171),(403,411),(224,411)
'sphere'                                   | (329,181),(350,180),(350,187),(329,188)
'NYC'                                      | (235,181),(267,179),(268,195),(236,197)
'NEW'                                      | (227,225),(285,217),(291,255),(232,264)
'YORK'                                     | (296,215),(363,206),(369,244),(301,254)
'30'                                       | (254,270),(345,267),(347,327),(256,330)
'NYC'                                      | (372,397),(399,389),(403,403),(376,411)

In [23]:

Send me the output from each run of the function in an email
Assignment 


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