Modify and Run Cohere Analysis Notebook
Budget: $30 – $250 CAD
NOTE
Work is very specific. Only bid if you know the task please.
NOTE
I'm looking for a proficient Python dev who can help me run a specific Jupyter notebook on Google Colab. The notebook is designed for analyzing Airbnb's financial metrics from their 10-K report using Cohere and RAG.
The project has three key milestones:
1. Successfully running the notebook on Colab or any other platform (https://github.com/cohere-ai/cohere-developer-experience/blob/main/notebooks/guides/Analysis_of_Form_10_K_Using_Cohere_and_RAG.ipynb)
2. Modifying the notebook to incorporate a loop for multiple URLs (Step 1, line 3-5)
3. Testing and debugging the notebook to ensure its accuracy and efficiency
The section of the notebook that will need modification for milestone 2 involves loading the 10-K report from the SEC. You'll need to replace the current URL with a loop that can pull from an array of URLs. A sample array will be provided for you.
The primary goal of this project is to extract financial metrics from the data. Therefore, the ideal candidate should have:
- Proficiency in Python programming
- Experience working with Jupyter notebooks and Google Colab
Please note that I do not require any visualizations or charts for the financial metrics, just the raw data. This is a straightforward data analysis project, but attention to detail and the ability to troubleshoot and debug are essential for success.
Lines to be modified to use in a loop
# Load up Airbnb's 10-K from this past fiscal year (filed in 2024)
# Feel free to fill in some other EDGAR path
url = "https://www.sec.gov/Archives/edgar/data/1559720/000155972024000006/abnb-20231231.htm"
Work is very specific. Only bid if you know the task please.
NOTE
I'm looking for a proficient Python dev who can help me run a specific Jupyter notebook on Google Colab. The notebook is designed for analyzing Airbnb's financial metrics from their 10-K report using Cohere and RAG.
The project has three key milestones:
1. Successfully running the notebook on Colab or any other platform (https://github.com/cohere-ai/cohere-developer-experience/blob/main/notebooks/guides/Analysis_of_Form_10_K_Using_Cohere_and_RAG.ipynb)
2. Modifying the notebook to incorporate a loop for multiple URLs (Step 1, line 3-5)
3. Testing and debugging the notebook to ensure its accuracy and efficiency
The section of the notebook that will need modification for milestone 2 involves loading the 10-K report from the SEC. You'll need to replace the current URL with a loop that can pull from an array of URLs. A sample array will be provided for you.
The primary goal of this project is to extract financial metrics from the data. Therefore, the ideal candidate should have:
- Proficiency in Python programming
- Experience working with Jupyter notebooks and Google Colab
Please note that I do not require any visualizations or charts for the financial metrics, just the raw data. This is a straightforward data analysis project, but attention to detail and the ability to troubleshoot and debug are essential for success.
Lines to be modified to use in a loop
# Load up Airbnb's 10-K from this past fiscal year (filed in 2024)
# Feel free to fill in some other EDGAR path
url = "https://www.sec.gov/Archives/edgar/data/1559720/000155972024000006/abnb-20231231.htm"