Assignment # 11 due 12/5/25

Take 3 news articles and run thru sentiment and entity recognition modules and send the output to me in an email.

Using the Codelab on Sentiment Analysis

https://uconnstamfordslp.blogspot.com/p/nlp-codelab.html

NLP Codelab   Using the Natural Language API with Python Codelab NLP Welcome to Cloud Shell! Type "help" to get started. Your Cloud Platform project in ... uconnstamfordslp.blogspot.com

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Take each news article(3) in total 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% |           |

Assignment #10 due 11/21/25

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

Load 4 python routines that will use Google Vision API to scan 4
separate images.

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

Download images from the 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]:

4 Python routines 

Perform label detection

Perform text detection

Perform landmark detection

Perform face detection

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

Assignment 

Adjunct Professor John Iacovacci

University of Connecticut, Stamford

John.Iacovacci@uconn.edu

Assignment #9 Due 11/14/25

 Create a Linux shell program to state

Name

Major

Graduation Year

What you want to do?

High school you went to?

Town you live in?

Favorite subject growing up?

What are you passionate about?

Favorite band or musician?

Favorite song?

What company or organization would you like to for for?

Create a text file called mydata.txt that consist of the lesson 1

shell script exercise using standard output redirection

encrypt file

https://uconnstamfordslp.blogspot.com/p/encrypt-and-decrypt-data-with-cloud-kms.html

Leveraging Assignment 1

Copy the shell script code (in body),  and attached the plain text file and the encrpyted file to an email

john_iacovacci1@cloudshell:~/scripts (uconn-engr)$ ./my_profile
Hello my name is John Iacovacci

Email to john.iacovacci@uconn.edu

Adjunct Professor John Iacovacci

University of Connecticut, Stamford

John.Iacovacci@uconn.edu

Assignment #8 due Friday 11/7/25

 Set a firewall rule on your app engine project for assignment 6.

The rule will help in preventing denial of service attacks.

use sniping tool to copy firewall rule.

https://uconnstamfordslp.blogspot.com/p/firewall-rules.html

Send me app engine link and image from the firewall rule.

Assignment #7 due 10/31/25

 Build 8 graphs using matplotlib.

I want two separate publicly traded companies e.g. AAPL & AMZN

Volume and price graphs for a 1 year period 

Volume and price graphs for a 90 period

Send the code in email and links to the graphs on your cloud storage bucket.

https://uconnstamfordslp.blogspot.com/p/api-price-and-volume-graphs.html

Assignment # 6 due Friday 10/24/25

 https://uconnstamfordslp.blogspot.com/p/assignment-exercise-python-datastore.html

 Recreate the app engine project above and send me a working link from app engine screen.

 Create a datastore entity called Custinfo

 Load programs per link Add your name to the html that the program displays.

 Also, add Phone number and email address to the data along with the reading,

 writing and updating of those two new data items. 

Note: Need to have Google Translate API turned on in order to read data 

Email me the app engine link

e.g.

sentiment-analysis-379200.ue.r.appspot.com 

Adjunct Professor John Iacovacci

University of Connecticut, Stamford

John.Iacovacci@uconn.edu

Assignment #5 due Friday, October 17th

Assignment #5 due Friday, October 17th

 

All have been granted access to the project sentiment analysis

Create the tables and send me the SQL SELECT with your data on the customer and order details you used for the python homework.

Use select statements to list out contents of all 4 tables and copy the output of these select statements to email, along with all the SQL statements entered.

Take screen shot ourt output and send in an email.

https://uconnstamfordslp.blogspot.com/p/mysql-exercise.html