Category: Python

Hi, I have attached below the instructions for this assignment in the zip file so please take a look at that to see what needs to be done for this assignment. Please make sure to follow the instructions/guidelines provided to complete the assignment! This is very important! Let me know if you have any questions or if there’s something that you find confusing about the instructions that you would like me to clear up with you! I can extend the time if needed.

Hi, I have attached below the instructions for this assignment in the zip file so please take a look at that to see what needs to be done for this assignment. Please make sure to follow the instructions/guidelines provided to complete the assignment! This is very important! Let me know if you have any questions or if there’s something that you find confusing about the instructions that you would like me to clear up with you! I can extend the time if needed.

Work on the “Final” Python file and for the time series regression model do the time series model for 20 companies separately.
and also do Fama Mac-beth for cross-sectional modeling.
I have attached the Fama Mac-beth file for your reference.
Also, create a Report from the Python file and Project proposal.
The final report should include the following:
Abstract
Introduction
Literature Review (you can combine them with an introduction too).
Data and Methodology (can be two separate sections too).
Result and Discussion (you can divide them into multiple sections or subsections based on the type of result you are reporting).
Conclusion
References
Appendix (if any)
Here, is the link to the data
https://we.tl/t-N2ab9xMPKp

finish statistical learning and conclusion. Finish this work by seeing my past assignment 3 as tutorial. Include chi-square, two sample t test. And do the A/B testing. Do not use AI for conclusion

There are 4 questions and can be found in details in the document attached. Note: (The last question needs a drawing graph)

I am working on forecasting orders for a floral shop using general forecasting techniques to determine the most accurate one. ( we have data for years 1 and 2 and 10 flower categories to forecast. we applied techniques in year 1 on each flower category to forecast orders for year 2 and measure the accuracy level and errors).I want to determine if using an AI forecasting technique would yield better results. I need help developing the code. Any data you may need to do so, I will send.

In this lab, you will work with a dataset of home sales and apply feature selection techniques to build linear regression models for predicting sale prices.

Hi, I have attached below the instructions for this assignment in the zip file so please take a look at that to see what needs to be done for this assignments. Please make sure to follow the instructions/guidelines provided to complete the assignment! This is very important! Let me know if you have any questions or if there’s something that you find confusing about the instructions that you would like me to clear up with you! I can extend the time if needed.

Create 3 DNN layers in a Jupyter notebook to do regression to predict NBA’s player salary using the attached dataset
Make sure you do data- processing
Do some data visualization
Handle the missing data
Using different activation function and highlight the difference
Build your model
Provide graph for the prediction
Provide the conclusion at the end of the code
Please follow the below rules:
only jupyter notebook Ipynb file will be accepted.
wirte your name and student id in the first cell
rename the file to your firstname_Assignment1
provide comments for each steps.

Hi, I have attached below the instructions for this assignments in the zip file so please take a look at that to see what needs to be done for this assignments. Please make sure to follow the instructions/guidelines provided to complete the assignment! This is very important! Let me know if you have any questions or if there’s something that you find confusing about the instructions that you would like me to clear up with you! I can extend the time if needed.