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.vscode
.vscode
 
 
Classification
Classification
 
 
Common
Common
 
 
Regression
Regression
 
 
Static images
Static images
 
 
__pycache__
__pycache__
 
 
output
output
 
 
.DS_Store
.DS_Store
 
 
Final EDA Classification.ipynb
Final EDA Classification.ipynb
 
 
Final EDA Regression.ipynb
Final EDA Regression.ipynb
 
 
README.md
README.md
 
 
Tested Classification.ipynb
Tested Classification.ipynb
 
 
Tested Regression.ipynb
Tested Regression.ipynb
 
 
da_rpc_regression_data1558504658.ipynb
da_rpc_regression_data1558504658.ipynb
 
 
da_rpc_regression_data1559117400.ipynb
da_rpc_regression_data1559117400.ipynb
 
 
data1532543947.ipynb
data1532543947.ipynb
 
 
data1559111992.ipynb
data1559111992.ipynb
 
 
db.sqlite3
db.sqlite3
 
 
final_xgboost_tree0.png
final_xgboost_tree0.png
 
 
global1.py
global1.py
 
 
hour_tree
hour_tree
 
 
hour_tree.png
hour_tree.png
 
 
make_jupyter_notebook.py
make_jupyter_notebook.py
 
 
make_jupyter_notebook_image.py
make_jupyter_notebook_image.py
 
 
manage.py
manage.py
 
 
train1616351865.ipynb
train1616351865.ipynb
 
 
train_test.py
train_test.py
 
 

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AutoAI

This project automates various machine learning tasks by providing a user friendly interface. It works on Django Framework and solves various use cases like, Regression, Classification, Feature Selection, Feature importance, etc.

1. Use Case Diagram

Use Case Diagram

2. Model Selection and processing

Model Selection and processing

3. Feature Importance

Feature Importance

Feature Importance

4. Flow diagram for feature selection

Flow diagram for feature selection

5. Various Use cases

Various Use cases

6. Plots

Plots

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