Teams

 dedeep.singu@uconn.edu

haris.mahmood@uconn.edu

rauni.machado-filho@uconn.edu

charlton.toussaint@uconn.edu

MOHAMED.OTHMAN@UCONN.EDU

IGNACIO.DELEON@UCONN.EDU

AMID.QAZI@UCONN.EDU

SHALINI.KUZHIPPAT@UCONN.EDU

ARIANNA.AZIZI@UCONN.EDU

ananya.jonnakuti@uconn.edu

david.keenan@uconn.edu

YOUNG.NAM@UCONN.EDU

AKHIL.JANNU@UCONN.EDU

EDWARD.KURYLUK@UCONN.EDU

KENNETH.MAEDA@UCONN.EDU

Scoring

The table mentioned below is ‘only for information’ purpose;

it gives summary of ‘number of words’ in each category in the matrix,

and they are not the weights. For example, there are total 18 words in ‘Financial Metric’ category

– of which 7 words are ‘Very Important’ and 6 words are ‘ Important’

and 5 words ‘Less so important’. The table is only for broader understanding.

For our Project purpose:

We have divided all words into three categories namely ‘Very Important’,

‘Important’ and ‘Less so important’ - please refer to attachment and the

color coding. The category classification is to allow the student to ascribe a “weight”

to each of the key words. For example, a key word that has been assign

as ‘Very Important’ should have more weight/importance in the sentiment

score than a key word that is ‘Less so important’.

 

Here’s an illustration of the weight for each of the category.

Very Important -> 2x

Important -> 1x

Less so Important -> 0.5x

Using these weights, the sentiment model score should be more “robust”.

 

We can advise students to be flexible with weights (while maintaining the

priority order) if they find better correlation/relation among peer group.

 

Hope this helps. Let me know if you have any questions.

 

Project Notes 2/18/24

 

To all;

Expecting everyone to report progress and ask questions.

I will be building out more detailed specifications today.

As per prior emails SDP team will be focusing on SSGA deliverables while the 4095 will do the production build.

For build out lets try to get base line programs in place. No need to complete or load all data at this point just get me the code that you are working on explained ASAP.

Key components.

Sentiment Model

This needs to be moved to our Google VM

Haris and Dedeep will need to assist Shalini and Arianna with getting 

sample program running. Does not have to run exactly like it does now. Just get small proof of concept code to work.

Graphs

This is key for the next presentation. Analysts want to see various graphs and comparison. This is how they are vetting the data. We will run graphs from summary tables. Again we need small base line python code. David Keenan and Rauni need to help David Young Nam and Akhil with getting started. Take the data points from the last graphs and pull code out so we can create small samples.

Front end Flask

These should be strait forward and I will build specs. Hopefully team has begun working. Charleton will be helping Mohammed and  Ignacio with the forms. These will run on app engine to load data in tables.

Linux Machine

Charlie and Kenneth will get this machine ready. It is crucial to the project that this gets done ASAP.

Data Loads.

Need to get the Topics data, CompanyInfo, scoring details and scoring totals in tables so programs can work dynamically. Ananya will work with Shalini, Arianna, Amid and Akhil to build and execute loader programs. 

Please provide status and questions as we are half way thru the term and we need to measure our progress.

Topics load

 First task. CRUD - Charlton help Mohammed and Ignacio

Ananya Datastore - Help Shalini and Arianna

Create a CRUD program to store the Datastore table for topics

Leverage the example

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

Topics is key

Topics	Classification	Sector	weight
Inflation	Macro	All	Important
Interest rate	Macro	All	Important
Raw Materials inflation	Macro	Industrials	Less so important
Volume	Sector trend	All	Less so important

Create a load program to load the topics spreadsheet into the Datastore table

https://uconn-sa.blogspot.com/p/datastore.html

Leverage the datastore load process 

Note:file is custom keyed

Link to topics spread in share that needs to be loaded.

https://docs.google.com/spreadsheets/d/1N7HwetkXOOaqBDyPWZp1CS0LmOySo0DpzWe3NPpvTpY/edit?usp=sharing

Adjunct Professor John Iacovacci

University of Connecticut, Stamford

John.Iacovacci@uconn.edu

Notes 2/13/24

 I will be combining the SDP meeting and the 4095 class into one long meeting in room 305G and on webex.

The SDP team will continue to work with State Street on project requirements while the 4095 class will focus on developing modules for the overall application.

Linux Machine build out.

EDWARD.KURYLUK@UCONN.EDU

KENNETH.MAEDA@UCONN.EDU

Machine needs to be setup to run python on the google cloud platform

https://cloud.google.com/python/docs/getting-started/getting-started-on-compute-engine

Access the compute engine and SSH into machine sentiment-prod

Front end team will work with Flask.

Will have multiple tables to maintain. First two being CompanyInfo and Topics.

Example below can be used as reference.

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

Assignment Exercise: Python Datastore CRUD NoSQL Python Datastore CRUD NoSQL Enable APIS and SERVICES Click Enable Select Datastore on left hand side  Note: You can pin any selection so it ... uconnstamfordslp.blogspot.com



MOHAMED.OTHMAN@UCONN.EDU

IGNACIO.DELEON@UCONN.EDU

AMID.QAZI@UCONN.EDU

Mathplotlib 

This team will start driving the graphs.

Need small program developed and explained.

YOUNG.NAM@UCONN.EDU

AKHIL.JANNU@UCONN.EDU

Model team will work with Haris and Dedeep to get the sentiment models running on the Linux machine and create documentation around how it works. Also write small examples to utlize in other cases.

David will help go thru current code and help document.

david.keenan@uconn.edu

SHALINI.KUZHIPPAT@UCONN.EDU

ARIANNA.AZIZI@UCONN.EDU

Adjunct Professor John Iacovacci

University of Connecticut, Stamford

John.Iacovacci@uconn.edu