A collection of my Data Science projects.
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In this project I’ll be creating a hybrid collaborative-filtering content-based recommendation system for Amazon Product using Tensorflow Keras API.
Tags: Deep Learning | Recommendation System | Tensorflow Keras | Word2Vec
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On my 5th semester in Binus University I took a Computer Vision course and for the final project me and my 2 teammates chose to build a super-resolution model (GAN) to enhance blurry unreadable linense plate into readable ones (License Plate Image Enhancer). Although this topic is quite advanced for the course at the time I found it interesting and so we decide to pursue it.
Tags: Computer Vision | Deep Learning | GAN | FastAI (PyTorch)
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On 25th April I took my Data Science Professional Certification from Data Camp, after going through several skill assessments in Python, Statistics, SQL, and Machine Learning along with a coding challenge in data management and exploratory analysis using python I was given this case study as my final project in which I have 24 hours to complete it and present my findings in a video format. I’ve made some improvements after submitting the project, particularly in the hyperparameter tuning section.
Tags: Classification | Machine Learning | Certification | DataCamp
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Recently, I started my deep learning journey on FastAI: Practical Deep Learning for Coders. I wanted to create this project to showcase what I’ve learned on image classification, and so I decided to create this dangerous plant classifier and deploy it in the form of a web app using render.
Tags: Computer Vision | Classification | Deep Learning | Model Deployment
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During the holiday I decided to make this regression project which try to estimate the prices of apartment rental in Jakarta. I know that there’s a lot of these type of property prediction project out there, especially on Kaggle. So I try to make it different by scraping my own data from the Travelio website. Overall, this is a fun experience for me I got to learn a lot of new things like linear regression assumption, web scraping with Selenium and Beautiful Soup, geocoding with google Map API, and trying out various ensemble learning methods.
Tags: Regression | Machine Learning | Geocoding | Web Scraping | Model Deployment