Data Science -- 3
Budget: $250 – $750 USD
**text me if you are really willing to do it**
Payment: $250
The project has two parts—besides, this project payment for $250 (with due on April 03)
I will give you an extended dataset for more features and more years for next week's task for another $200.
The due date for this phase: April 03 - in the evening US central time
Work you need to do: you will use the description provided in the word file later. You will make different models or combinations of models.
Data: we have around 110 rows of data with around 15 features
Target variable: numerical (you can change it to a category to consider it as a categorical target)
Report and code direction:
(1) tell me what you will use to run the code (Jupyter notebook, collab,..) to not have the package problem for running the code again. And tell me what we need to install.
(2) Also, return the code in Jupyter Notebook and .HTML file
(3) Any explanation of code (for data cleaning, preprocessing, modeling, prediction and validation) and intuition about the results and analysis should be written in the Jupyter Notebook
Payment: $250
The project has two parts—besides, this project payment for $250 (with due on April 03)
I will give you an extended dataset for more features and more years for next week's task for another $200.
The due date for this phase: April 03 - in the evening US central time
Work you need to do: you will use the description provided in the word file later. You will make different models or combinations of models.
Data: we have around 110 rows of data with around 15 features
Target variable: numerical (you can change it to a category to consider it as a categorical target)
Report and code direction:
(1) tell me what you will use to run the code (Jupyter notebook, collab,..) to not have the package problem for running the code again. And tell me what we need to install.
(2) Also, return the code in Jupyter Notebook and .HTML file
(3) Any explanation of code (for data cleaning, preprocessing, modeling, prediction and validation) and intuition about the results and analysis should be written in the Jupyter Notebook