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AI Career Development

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Learning   Prompts  Python Pycharm  Pytotch R Copilot  Tuning With Data Kaggle  || Papers Statistics Calculus Machine Learning Deep Learning AGI Super GI

1. Define the problem
2. Gather and preprocess data
3. Select the appropriate algorithm
4. Train the model
5. Evaluate and fine-tune the model
6. Test the model
7. Deploy the model
8. Monitor and maintain the mode

AI will fragment society further. Best to bury it from the masses.
They have already been sabotaged.
Our political situation is sub optimal.
existential risk
Covid burned up credibility
Individual Schooling
Licensing of levels of access.
Wishy Washy Society




Creative development of real applications.
Creative Prompting
Team Incentives
Product Development
Customer Experience
Identifying New Markets Locally Nationally Internationally.
Advertising
Event Planing


Python Level Access
Feeding data to models.
1000 lines by 24 cells

How large a data set is practical to upload to Bard for consideration in a prompt? How many rows and items per row or total number of characters?
A name is    characters   a number is typically around 6.
A customer number is around 6 characters.
There are ways to shrink  the size of those number by combining letters and reporting in 100s 1000s ...
Locations can be coded by lat and longitude.  20 characters
establish a code for address
Name Date Address Type Dollars Spent Fequency Tentative Goal

• While I don't have explicit size restrictions for text processing, my optimal performance typically involves:
  • Individual texts up to around 10,000 characters.
  • Multiple text inputs up to a collective total of around 40,000 characters.

Training AI...