Automated Machine Learning Framework for Data Analysis

Key Features

• Automated Model Selection: The framework automatically selects the most suitable machine learning model based on the characteristics of the dataset.
• Feature Engineering: It automatically applies various feature engineering techniques to preprocess the data and enhance the predictive power of the models.
• Hyperparameter Optimization: The library performs hyperparameter optimization to fine-tune the models and improve their performance.
• Performance Evaluation: It provides comprehensive evaluation metrics to assess the performance of the models and compare different approaches.

Usage

• Make sure you have Python installed in your system.
• Run Following command in the Terminal.

 pip install UAutoml

Example

# test.py
import UAutoml

## Make sure u have follwing paramters
dataset = '/Path'
Target = 'Column_Name'

(this are optional)
Hyper_optimazation: If needed set value to 1 or in default 0
epochs: IN default its 5 you can set your requirements

## To run

# To get full automated process
r = UAutoml.process_data(dataset,Target) 

# To get the features data
features = UAutoml.feature(dataset,Target)

Run the following Script.

 python test.py

Note

• I have tried to implement all the functionality, it might have some bugs also. Ignore that or please try to solve that bug.