ztonege / automl

AutoML is a distributed machine learning pipeline designed to scale to large datasets. AutoML aims to automate the entire process of solving a classification problem. It just requires the dataset and the target column as an input and then the system takes care of the rest. Efficient cleaning of the dataset is performed, which imputes all the missing values and gives better structure to the dataset. The system is capable of detecting categorical values, thus performing One-Hot Encoding where required. Further, in the preprocessing stage, it also takes care of feature engineering, dimensionality reduction, sampling and removal of outliers which affect the accuracy of the model. After the preprocessing stage, the ready data is trained on several models, with multiple different hyperparameters. The output of the system is the name, accuracy and code of the best model, which is judged based on its accuracy. The system is tested on over 30 datasets, both binary and multi-class classification and there is a robust system to quickly train any dataset given to it.

Auto-ML

It is a simple, easy to use web app which allows users to upload their dataset and fill the name of target field.

Then our app preprocesses the dataset and applies various Machine learning Regression and classification algorithms depending on the case.

After processing our system will return a model with highest perform which the user can download and use.

Tech Stack: React JS , Flask , Python , Tensorflow , sklearn