Automated dataset classification and model architecture selection using Neural Architecture Search (NAS). Built with AutoKeras and Python.

A user-friendly system that uses NLP and AutoKeras to automatically generate neural network architectures from natural language input. It leverages Neural Architecture Search (NAS) to build optimized deep learning models for tasks like image/text classification, time series forecasting, regression, and sentiment analysis.

This the final project for CPSC 483 (Introduction to Machine Learning). We developed a machine learning model for classifying medical images.

Collection of hands-on projects developed during my journey to master data science concepts and techniques.

🤖 An automated machine learning framework for audio, text, image, video, or .CSV files (50+ featurizers and 15+ model trainers). Python 3.6 required.

Automatically Build Multiple ML Models with a Single Line of Code. Created by Ram Seshadri. Collaborators Welcome. Permission Granted upon Request.

This project explores how AutoML simplifies machine learning workflows by automating model selection, hyperparameter tuning, and evaluation, comparing tools like TPOT, H2O, and AutoKeras, and culminating in a custom-built AutoML system from scratch.

Automatically build ARIMA, SARIMAX, VAR, FB Prophet and XGBoost Models on Time Series data sets with a Single Line of Code. Created by Ram Seshadri. Collaborators welcome.

This repo contains all background of the : HAM1000 Dataset balancing / Proposed CNN architectures / Various proposed and benchmarked CNN models

Build tensorflow keras model pipelines in a single line of code. Now with mlflow tracking. Created by Ram Seshadri. Collaborators welcome. Permission granted upon request.

This repository includes sample code for AutoML tools AutoGluon, AutoKeras, AutoSklearn, H2O, PyCaret, TPOT

2022년 2학기 팀 프로젝트 : 도금공정 데이터 셋 분석(k-인공지능 제조데이터 분석 경진대회)

Medical Image Classification with On-Premise AutoML

Automated & Augmented ML Toolbox for Image Classification

MNIST Live Detection using OpenCV, Tensorflow Lite and AutoKeras

Example of how to setup a NVIDIA DevContainer with GPU Support for Tensorflow/Keras, that follows the page https://alankrantas.medium.com/setup-a-nvidia-devcontainer-with-gpu-support-for-tensorflow-keras-on-windows-d00e6e204630

Evaluating the Performance of Automated Machine Learning (AutoML) Tools for Heart Disease Diagnosis and Prediction

A hands-on tutorial for using AutoKeras to train an image classification model for the identification of wildfires in satellite images.

A research project involving the development of an explainable data-driven machine learning model to aid in geothermal drilling.

Convolutional Neural Network vs Multilayer Perceptron in Image Classification