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Achievement: Pull Shark

Achievements

Achievement: Pull Shark

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devapratama/README.md

Hi there, I'm Deva👋

About Me

I am a recent graduate with a passion for Data Analysis, Data Science, and Machine Learning. I am certified as a TensorFlow Developer. I am eager to apply my academic knowledge and practical skills to real-world problems, aiming to make a meaningful impact through innovative solutions. I'm looking for my first job in the field of Data Analysis and Data Science, or Machine Learning.

Education

  • Bachelor of Informatics Engineering
    Dian Nuswantoro University, 2024. Graduated with a GPA of 3.82, completing the program in 3.5 years.

Thesis

  • Title: Emotion Recognition From E-Commerce Customer Reviews Using Transformer-Based Deep Learning
  • Description: This research explores the application of a Transformer-based deep learning architecture to identify emotions from customer reviews in Indonesian-language e-commerce. Using a dataset of 5,400 customer reviews, the model is designed to classify five categories of emotions: Happy, Sadness, Anger, Love, and Fear.
  • Technologies Used: Python, Pandas, Numpy, TensorFlow, Keras, Google Colaboratory, Streamlit.
  • Link to Project & Thesis: https://github.com/devapratama/text-emotion-recognition

Projects

Here are a few highlights of the projects I have worked on:

1. Travel Customer Prediction

  • Description: This is the final project from the Kampus Merdeka independent study program at Rakamin Academy's Data Science Bootcamp 2023. I led a team of 7 members to successfully complete this project. The focus of this project was on analyzing customer data to provide actionable recommendations for policy makers and marketing teams. Additionally, we developed a predictive model to identify potential customers likely to purchase a newly introduced vacation package.
  • Technologies Used: Python, Pandas, Matplotlib, Scikit-learn, Google Colaboratory, Streamlit.
  • GitHub Repository: https://github.com/devapratama/travel-purchase-predictor

2. Skin Disease Classification

  • Description: This project focuses on Skin Disease Image Classification using transfer learning with DenseNet121. As part of the "SkinSight" team for the Bangkit 2023 Capstone Project, I contributed to the development of the machine learning model. Our goal was to accurately classify various skin diseases, leveraging advanced deep learning techniques to aid in early detection and diagnosis.
  • Technologies Used: Python, TensorFlow, Keras, Google Colaboratory, Flask.
  • GitHub Repository: https://github.com/devapratama/Skin-Disease-Classification

Skills

  • Programming Languages: Python, SQL
  • Machine Learning: Scikit-Learn, TensorFlow, Keras
  • Data Analysis & Visualization: Pandas, NumPy, Matplotlib, Seaborn, Tableau
  • Databases: MySQL, PostgreSQL
  • Tools & Platforms: Jupyter, Git, GitHub, Streamlit

Let's Connect

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  1. Skin-Disease-Classification Skin-Disease-Classification Public

    Skin Disease Classification with DenseNet121. This is a project team for Bangkit Capstone Project named "SkinSight", and I'm part of creating the machine learning model. My Team: https://github.com…

    Jupyter Notebook 1

  2. text-emotion-recognition text-emotion-recognition Public

    This project explores the application of Transformer-based deep learning architecture to identify emotions from customer reviews in Indonesian-language e-commerce.

    Jupyter Notebook

  3. travel-purchase-predictor travel-purchase-predictor Public

    Travel-Customer-Prediction project aims to predict which customers are likely to purchase a new "Wellness Tourism Package" using machine learning. By analyzing customer data from a Kaggle dataset, …

    Jupyter Notebook

  4. spam-sms-classifier spam-sms-classifier Public

    This project develops a machine learning model to classify SMS messages as spam or legitimate, using NLP techniques to enhance user experience by filtering out unwanted messages.

    Jupyter Notebook

  5. home-credit-scorecard-model home-credit-scorecard-model Public

    This project improves the credit scoring model for PT Home Credit Indonesia, using machine learning to accurately approve loans for creditworthy customers, thereby increasing financial inclusion an…

    Jupyter Notebook

  6. Telco-Customer-Churn-Prediction Telco-Customer-Churn-Prediction Public

    This is my personal project to make Telco Customer Churn Prediction with supervised learning (classification).

    Jupyter Notebook