Hello all! Assembling a few sample performance and analytics dashboards, using randomized dummy data to keep client info private, to refine how reporting gets presented to design and brand partners.

When working on brand, web, or UI/UX projects, what metrics or visual insights do you actually find valuable in a report? Are you looking to see how visual changes impact user engagement and conversion paths, or do you prefer high-level ROI summaries to show clients the impact of your work?

Always open to connecting with designers, agencies, and growth strategists looking to partner on the performance and reporting side of client accounts.

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.