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raflidmr (raflidmr)

 

 

Helloooo, my name is Rafli Damara. I am a highly motivated Software Engineering student with a strong interest in data science, especially machine learning. I am passionate about processing data, analyzing, building models, and also creating artificial intelligence. My background in software engineering provides a strong foundation in understanding data structures and algorithms, as well as an understanding of the necessary tools such as Python, R, SQL, and various supporting frameworks and libraries such as TensorFlow, Flask, Streamlit, PyTorch, and others. I am actively seeking opportunities to gain practical experience and contribute to teams working with data, especially machine learning, to further enhance my skills and expertise in this field.

Python Data Analysis Data Mining Machine Learning Artificial Intelligence Data Science

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User Name: raflidmr
Account Type: Personal Account
Date Registered: 11/05/2025 21:12:09 WIB
Last Seen: 23/05/2025 16:22:47 WIB
Provinsi: Jawa Barat
Kabupaten: Kota Bogor
Website: https://www.datascienceportfol.io/rfldmr
Online Hours: 1.92
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2025: WeaVis is an AI-based weather recognition information system designed to recognize weather uploaded or photographed by users, and then display information about the weather. Built on PyTorch, with CNN algorithm plus MobileNet v3 architecture, the weather predictions provided have very good accuracy values.

2025: SMARE AI is an AI-based automatic report generation system for water quality testing certification. Supported by the Gradient Booster algorithm, SMARE AI can predict water quality categories with test result data inputted by users and automatically generate test certificate reports in PDF format.

2025: VokaBot is a simple AI-based customer service chatbot designed to provide information and answer questions related to IPB Vocational School. Built using the TensorFlow framework and utilizing the NLTK library for natural language processing (NLP), VokaBot is able to understand and respond to questions by utilizing a trained deep learning model.

 

 

 

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