A technology enthusiast with a background in Computer Science at Bina Nusantara University specializing in DevOps and artificial intelligence. I have experience in creating personal projects with Linux shell scripting, containers, CI/CD, service mesh, asynchronous communication, microservices architecture, as well as creating models and applications based on machine learning and deep learning. I am a person who loves to learn, adapt easily, and can work together in a team.

• Artificial Intelligence in Entrepreneurial Mindfulness using CRISP-DM Method (https://ieeexplore.ieee.org/document/9971384/)
• UX Analysis on Entrepreneurial Mindfulness Application (Presented at a conference, but hasn't been published yet)
• Recommendation System Based Collaborative Filtering for Deciding Travelling Place (https://ieeexplore.ieee.org/abstract/document/10284657/)

• Computer Vision

  Building various computer vision models for 2D image classification, 3D image classification, video classification, point cloud classification, neural style transfer, google deep dream, image segmentation, image similarity, image captioning, and image reconstruction with various computer vision datasets such as ImageNet, Pix3D, MNIST, Flickr30K, and HMDB51.

• Natural Language Processing

  Building various natural language processing models for spam detection, sentiment analysis, article spinner, poem generator, topic modelling, keyword extraction, and text summarization with various NLP datasets such as BBC News, web scrapped texts, Edgar Allan and Robert Frost’s poem, and emails. In addition, I also have a travelling place news web scrapper project using Programmable Search Engine (Google Cloud) and Beautiful Soup library.

• Recommendation System

  Building various recommendation system models for recommending animes and tourist places. Naïve Bayes, scalable deep learning, efficient deep learning, SVD++, and hybrid algorithm (ContentKNN and RBM) were used for building recommendation system models.

• Time Series Forecasting
  Building various time series forecasting models for forecasting number of tourists in Indonesia and residential power usage. Deep learning and ARIMA were used for building time series forecasting models.

• DevOps
  • CI/CD pipeline
  • Application deployment with kubernetes
  • Asynchronous communication and service mesh
• Frontend Development (Flutter, HTML, CSS/ SASS, and JavaScript)
• Android Development (Java, Kotlin)
• Backend Development (Flask, Django, and Laravel)

• 3D modelling and animation projects (https://github.com/anthonycreates2000/3D-projects)
• Game Development