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.
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Updated
Aug 20, 2024 - Jupyter Notebook
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.
Automatically Build Multiple ML Models with a Single Line of Code. Created by Ram Seshadri. Collaborators Welcome. Permission Granted upon Request.
Product Categorization with Machine Learning
Computational experiments for the paper "A Comparison of AutoML Tools for Machine Learning, Deep Learning and XGBoost" (IJCNN 2021)
Diego: Data in, IntElliGence Out. A fast framework that supports the rapid construction of automated learning tasks. Simply create an automated learning study (Study) and generate correlated trials (Trial). Then run the code and get a machine learning model. Implemented using Scikit-learn API glossary, using Bayesian optimization and genetic alg…
Benchmark of current ML automation frameworks
My Thesis: Auto-ML Tool for IoT Applications Version 1.0
Tutorial on Auto_TS : Automatically build ARIMA, SARIMAX, VAR, FB Prophet and ML Models on Time Series data sets with a Single Line of Code
This repo contains analysis of Lending Club Credit rates and also case study for a client to get a fully funded loan at the lowest credit rate with a desired duration.
This repository includes sample code for AutoML tools AutoGluon, AutoKeras, AutoSklearn, H2O, PyCaret, TPOT
Development of a credit scoring model
This project implements functions for building an ensemble of classifiers and regressors using the TPOT and auto-sklearn libraries with the help of a genetic algorithm evolved using the deap library.
This repo's main purpose is to automate the ML process using scikit learn. I have performed the automation process in both classification and Regression
Predicting Chronic Kidney Disease using AutoML (AutoSklearn) on Docker container
Predicting future winners of the Ingeborg-Bachmann-Preis with the help of NLP. Has a Flask app and a Rasa chatbot!
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