AutoML Forge is an end-to-end AutoML platform designed to simplify the machine learning workflow by automating key stages from data preparation to model evaluation.

The platform allows users to upload their datasets and build machine learning models without manually handling every step of the traditional ML pipeline.

Key Features

Automated data preprocessing and cleaning

Automatic feature handling and transformation

Classification and regression workflows

Anomaly detection

Model comparison and evaluation

Automated model selection

Hyperparameter optimization

Performance metrics and visualizations

Model prediction and inference

Easy-to-use interactive interface

Tech Stack

Python · PyCaret · FastAI · Scikit-learn · Pandas · NumPy · Streamlit

The project focuses on making machine learning more accessible while reducing repetitive experimentation and development time. It demonstrates practical experience in machine learning automation, model evaluation, data preprocessing, and building AI-powered applications.

Role: AI/ML Developer Project Type: Machine Learning / AutoML / Data Science

Impressive to see automated data preprocessing and cleaning built into AutoML Forge - eliminating that tedious step speeds up experimentation dramatically. The integrated model comparison and evaluation visualizations make it easy to spot the best performer quickly.

Self-Created Practice Project

I worked on a practice hotel booking dataset where multiple data fields were combined into a single raw-data column.

Work completed:

Separated unstructured data into individual columns using Text to Columns

Organized Booking ID, Guest Name, City, Check-In Date, Check-Out Date, Number of Pax, Amount and Status

Improved the structure and readability of the spreadsheet

Prepared the dataset for easier filtering and further use

Tool: Microsoft Excel

Skills: Data Entry | Data Cleaning | Text to Columns | Data Organization | Spreadsheet Formatting

This is a self-created practice project and not client work