Welcome to my Data Science portfolio! This repository showcases a variety of projects I have worked on, covering areas like Machine Learning, Data Analysis, Large Language Models (LLMs), Reinforcement Learning, and Computer Vision. Each project reflects my hands-on experience and the application of advanced techniques to solve real-world problems.
I’m a Computer Science graduate with a 3.53 GPA from Brawijaya University. I’ve sharpened my data science skills through the Bangkit Academy’s Machine Learning bootcamp, where I dived deep into advanced machine learning techniques. During my internship, I put this knowledge into action by implementing OpenAI’s language models to create a chatbot. Moreover, I can perform oral and written language capability both in Indonesian and English.
- Introduction
- Machine Learning
- Data Analysis
- LLM (Large Language Model)
- Reinforcement Learning
- Computer Vision
- Micro Projects
- Closing Statement
Welcome to my Data Science portfolio! This repository showcases a variety of projects I have worked on, covering areas like Machine Learning, Data Analysis, Large Language Models (LLMs), Reinforcement Learning, and Computer Vision. Each project reflects my hands-on experience and the application of advanced techniques to solve real-world problems.
I’m a Computer Science graduate with a 3.53 GPA from Brawijaya University. I’ve sharpened my data science skills through the Bangkit Academy’s Machine Learning bootcamp, where I dived deep into advanced machine learning techniques. During my internship, I put this knowledge into action by implementing OpenAI’s language models to create a chatbot. Moreover, I can perform oral and written language capability both in Indonesian and English.
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Customer's Purchase Probability Based On E-Commerce Clickstream Data
After an exploration, I've decided to predict the probability of a customer making a purchase using clickstream data from an e-commerce platform using Deep Learning methods. There's 2 notebooks for this project, the Feature Engineering notebook and Prediction notebook. -
Fraud Detection on Crypto Coin (Ethereum)
Using an open database about Ethereum (ETH) transaction information, my goal is to build a model to detect fraudulent activities in Ethereum transactions, enhancing the security of crypto assets. You can see the presentation Here. -
Customer Segmentation Based On E-Commerce Database
Utilizing clustering techniques to segment customers by buying patterns and also spending profiles, enabling targeted marketing/sales strategies in e-commerce, especially to retain a specific segment of customers. You can see the presentation Here. -
Rain Prediction for Farmer's Decision Making
Developing a model to predict rainfall, helping farmers make informed decisions about crop management. You can see the presentation Here and the notebook Here. -
Plant Disease and Soil Detection (Terrafarms's Bangkit Academy Project)
Providing farmers with the tools and technologies they need to achieve higher yields, improve efficiency, and promote sustainability. This plant and soil detection was a small part of my big project Terrafarms. You can see the specific machine learning implementation Here. -
K-Nearest Neighbor in Kinematic Robot
Applying the K-Nearest Neighbor algorithm to improve the accuracy of robot kinematics in a controlled environment. You can see the repository Here.
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Terrorism & Poverty Relation Analysis
Exploring the relationship between terrorism and poverty through a comprehensive data analysis approach using R. Providing an "aha moment" from two databases that correlate with each other. You can see the R notebook Here. -
E-Commerce Clickstream Data Analysis
Analyzing e-commerce clickstream data to uncover user behavior patterns to achieve insight for further analysis. The main idea of this was to explore the data. You can see the notebook Here.
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Database/Tabular Data Analysis Using LIDA
Leveraging Large Language Models to perform in-depth analysis of database and tabular data, automating complex queries, giving goals possibilities, also providing small visualizations. You can see the notebook Here. -
Micro Chatbot Using OpenAI API
Creating a simple chatbot utilizing OpenAI's API, capable of handling basic customer inquiries and interactions. You can see it Here.
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DQN Implementation with Space Invaders Game
Implementing Deep Q-Networks (DQN) to train an agent for playing the Space Invaders game, focusing on reinforcement learning techniques. The project is available to play in my Hugging Face repo. -
DQN Implementation with Super Mario Game
Using DQN to create an AI that plays the Super Mario game, showcasing advanced reinforcement learning capabilities. You can see the project Here.
- Plate Detection
Developing a computer vision model to accurately detect and recognize license plates in images or video streams. You can see the project Here.
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PCA Implementation
Implementing Principal Component Analysis (PCA) to reduce the dimensionality of cancer datasets while preserving variance. Code. -
Churn Prediction
Building a model to predict customer churn, helping businesses retain valuable customers through targeted interventions. Code. -
Sales Forecasting
Using time series analysis to forecast sales, aiding in inventory management and business planning. Code. -
Sentiment Analysis
Analyzing text data to determine the sentiment, providing insights into customer opinions and market trends. Code. -
Toxic Classification
Developing a model to classify toxic comments in online discussions, improving content moderation. Code.
"Data science is the art of turning data into actions. It's not just about numbers; it's about making a meaningful impact in the world. Keep learning, keep exploring, and let your curiosity guide you through the vast oceans of data."
Thank you for exploring my portfolio. Feel free to reach out to me on LinkedIn or check out more of my work on GitHub.