Project started as a personal skill set development exercise.ĭistributed under the Apache License 2.0.Docker image distribution, with Apple M1 Tensorflow port.Created of JSON prediction model as an enhanced version of country model.Created country prediction model based on structured data.Creation of models using Python / Jupyter and TensorFlow / Keras.Docker Image bsantanna/iban-validator-model (x86_64 architecture only)Īs a possible future improvement, multiple models could be produced to move part of the algorithm which performs validation from runtime to model compilation time.Īs a closing note, the following resources served as references for this project:įor reporting errors or questions please contact me by e-mailĬopyright 2022 Bruno César Brito Sant’Anna ChangelogĬhange log is organized in chronological reverse order.Tensorflow / Keras model implementation. IBAN Calculator - Validate IBAN to Send Money Internationally - Xe Business IBAN Calculator Many countries use the International Bank Account Number (IBAN) as a standardized format for how bank account information is presented when sending an international money transfer.A IBAN / Country Regular Expression Dataset.The following items can be considered project deliverables: The project reached its original goal of designing and implementing an Artificial Neural Network for validating IBAN account numbers. $ mvn clean install $ java -jar target/rest-api.jar GET /validation : Returns validation and embedded predicted classificationīoth endpoints accept a single query parameter ibanĪssuming a Java Development Kit is available, there is a maven project under modules/prediction/rest-api, which can be built and executed using the following commands:.GET /json-prediction : Returns raw json classification predicted by model without regex validation.The implementation used official gRPC documentation as reference.Ī HTTP REST API is another deliverable of this project, it was created to simulate system integration scenario with gRPC client for the same contract served by the gRPC Service.OutputLabel object contains a single attribute json with type string.InputFeatures object contains a single attribute iban with type string.Contract publishes a service interface getPrediction which receives an InputFeatures object and returns an OutputLabel object.To run this image with Docker use the following command: This model was created for case study purposes and may predict incorrect results.The dataset may be outdated in comparison to the latest IBAN registry / country information.Table of contentsĪ Docker Image which can be used following The project source code is available at bsantanna/iban-validator-model Github repository. Runtime dependencies and is used now as basis example for cloud related projects. As a Notebook at Kaggle for interactive experimentation.The trained model is distributed in two forms: This is an open-source project which delivers a machine learning model for validating IBANĪccount numbers accessible via gRPC and REST APIs. ML model for validating IBAN account numbers. Iban-validator-model IBAN Validator Model
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