I am a Machine Learning Engineer who is enthusiastic in algorithms, and at the same time puts emphasis on practical integration of machine learning methodologies into systems / products.
At work, I always try to demonstrate my main philosophy: great and successful machine learning adoptions must embody data lifecycle as a whole, and not solely the algorithm. This includes question-initiated decisioning of how and what data is collected, to designing of the automated pipeline for data preprocessing, cleaning, and modeling.
Areas of interest:
- Automated data pipeline designs for ML-integrated solutions
- Machine learning algorithms, including SVM, Random Forest & Deep Learning
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