[Deadline Saturday 5pm EST] Python Loan Data Model Project
Budget: $10 – $30 USD
[Deadline Saturday 5 pm EST]
Hello, I am trying to create some supervised models in Python based on this Kaggle data set
https://www.kaggle.com/datasets/williecosta/sba-7a-loan-data
I have started however struggling to finalize the code;
Preliminary Data Exploration: Explore the data, and provide some basic summary statistics and two or three visualizations.
Describe/show something interesting and/or surprising about the data. This exploration should not be exhaustive, just a highlight of a few interesting things about your data set. If you need to reduce the size of your data to fit now is the time to do that.
Data Exploration: shall include a bulleted or numbered list of proposed specific data explorations you intend to carry out (include visualization). These insights are things that can be determined by examining the data through statistical analysis or other means.
Predictions: shall include a prediction component (supervised learning) - include clustering, decision tree logistic regression, and k means (must have visualizations)
The goal is to identify the best loans; most profitable, and load status for being paid off
DELIVERABLES
Finished code with all steps detailed below, data preprocessing and data cleaning, EDA including visualization, Supervised Data Model (Clustering, Decision Tree, Kmeans and Logistic Regression) the models must have visualizations
CSV file link: https://we.tl/t-AoaQv8WR0j
[Deadline Saturday 5 pm EST]
Hello, I am trying to create some supervised models in Python based on this Kaggle data set
https://www.kaggle.com/datasets/williecosta/sba-7a-loan-data
I have started however struggling to finalize the code;
Preliminary Data Exploration: Explore the data, and provide some basic summary statistics and two or three visualizations.
Describe/show something interesting and/or surprising about the data. This exploration should not be exhaustive, just a highlight of a few interesting things about your data set. If you need to reduce the size of your data to fit now is the time to do that.
Data Exploration: shall include a bulleted or numbered list of proposed specific data explorations you intend to carry out (include visualization). These insights are things that can be determined by examining the data through statistical analysis or other means.
Predictions: shall include a prediction component (supervised learning) - include clustering, decision tree logistic regression, and k means (must have visualizations)
The goal is to identify the best loans; most profitable, and load status for being paid off
DELIVERABLES
Finished code with all steps detailed below, data preprocessing and data cleaning, EDA including visualization, Supervised Data Model (Clustering, Decision Tree, Kmeans and Logistic Regression) the models must have visualizations
CSV file link: https://we.tl/t-AoaQv8WR0j
[Deadline Saturday 5 pm EST]
Related categories:
Python
Machine Learning (ML)
Statistical Analysis
Artificial Intelligence
Deep Learning