Category: Python

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.

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.

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.

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.

The Challenge:
The directory input contains three files each containing a list of US names and addresses:
input1.xml
input2.tsv
input3.txt
The file formats are not documented, but you can deduce the formats by examining their contents. The challenge is to write a python script challange.py, designed to be run from the command line, that accepts a list of pathnames of files in any of the above formats, parses them, and writes a JSON-encoded list of the combined addresses to standard output, sorted by ZIP code in ascending order. You can assume that the format of each file corresponds to its extension, as illustrated by the above examples. Your submission should consist of a single file, without any supporting documents. The output should be a pretty-printed JSON array of JSON objects, each having 5 or 6 properties, serialized in the given order
name: The person’s full name, if present, consisting of a list of one or more given names followed by the family name
organization: The company or organization name, if present
street: The street address, often just a house number followed by a direction indicator and a street name
city: The city name
county: The county name, if present
state: The US state name or abbreviation
zip: The ZIP code or ZIP+4, in the format 00000 or 00000-0000
A personal name or organization name will always be present, but not both. Here is a sample output:
[ { “name”: “Hilda Flores”,
“street”: “1509 Alberbrook Pl”,
“city”: “Garland”,
“county”: “DALLAS”,
“state”: “TX”,
“zip”: “75040” },
{ “organization”: “Central Trading Company Ltd.”,
“street”: “1501 North Division Street”,
“city”: “Plainfield”,
“state”: “Illinois”,
“zip”: “60544-3890”
}
]
The script shouldBe well-organized and easy to understand
Use only standard Python libraries
Be compatible with Python 3.11
Conform to PEP 8
Provide a –help option
Check for errors in the argument list
Check the input files to make sure they conform to the formats expemplified by the sample files
Output a list of addresses only if no errors were discovered in the above two steps
Write any error messages to stderr
Exit with status 0 or 1 to indicate success or failure
WarningStudy the data carefully: it’s not as easy as it looks.