ML for webpage classification on AI integrated webapp
Budget: $250 – $750 USD
Webpage classification on AI integrated Erasmus web app. I already have app. We will add 5 ML algorithms to the model section. We will select and run them one by one in the model section. What we call web page classification is classifying URLs in the entire domain when the University is given as input.
You should add the algorithms to the model section and run the project one by one. We should select and run it. We should create a dataset and it gives us the URL related to Erasmus (we select the required documents or academic calendar, then the university, city, country and model, then we run it and it gives us the relevant link)
Finally, we need to write in word format which one is better by making a comparison (f1 score, precision, ...), explain the application and the algorithms we added. In short, there should be a methodology section, and a result section.
I seek a skilled developer to integrate 5 Machine Learning (ML) algorithms into the model section of my existing Erasmus web app.
- Additional Section: We will develop a new section on the app's existing UI to house these algorithms. This section should seamlessly integrate with the current design and user experience.
- Algorithm Selection: The developer is responsible for identifying and integrating 5 ML algorithms. This selection should be made after consideration of the app's requirements and in consultation with me.
- Algorithm Execution: The selected algorithms should execute one by one in the model section. The developer should ensure that the algorithms run correctly and provide the intended value to the app.
Ideal Experiences and Skills:
- Proficiency in Machine Learning and AI.
- Prior experience of integrating ML algorithms into web applications.
- Strong understanding of UI/UX principles for seamless integration.
- Effective communication and collaborative skills.
You should add the algorithms to the model section and run the project one by one. We should select and run it. We should create a dataset and it gives us the URL related to Erasmus (we select the required documents or academic calendar, then the university, city, country and model, then we run it and it gives us the relevant link)
Finally, we need to write in word format which one is better by making a comparison (f1 score, precision, ...), explain the application and the algorithms we added. In short, there should be a methodology section, and a result section.
I seek a skilled developer to integrate 5 Machine Learning (ML) algorithms into the model section of my existing Erasmus web app.
- Additional Section: We will develop a new section on the app's existing UI to house these algorithms. This section should seamlessly integrate with the current design and user experience.
- Algorithm Selection: The developer is responsible for identifying and integrating 5 ML algorithms. This selection should be made after consideration of the app's requirements and in consultation with me.
- Algorithm Execution: The selected algorithms should execute one by one in the model section. The developer should ensure that the algorithms run correctly and provide the intended value to the app.
Ideal Experiences and Skills:
- Proficiency in Machine Learning and AI.
- Prior experience of integrating ML algorithms into web applications.
- Strong understanding of UI/UX principles for seamless integration.
- Effective communication and collaborative skills.