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I am a Data Scientist and a Le Wagon graduate, passionate about solving real-world problems with data. Through the intensive and practical bootcamp curriculum, I have gained hands-on experience in Python, data extraction, manipulation, and visualization, machine learning, deep learning, and ML engineering. I am proficient in using Scikit-Learn, TensorFlow, and GCP for building comprehensive workfl
I am a Data Scientist and a Le Wagon graduate, passionate about solving real-world problems with data. Through the intensive and practical bootcamp curriculum, I have gained hands-on experience in Python, data extraction, manipulation, and visualization, machine learning, deep learning, and ML engineering. I am proficient in using Scikit-
• Thorough study in Python for Data Science, with expertise in data extraction, manipulation, and visualization, backed by a strong foundation in statistics and linear algebra. • Delving into Machine Learning and Deep Learning, with practical application in building comp
• Generates completely new music by Recurrent Neural Network (RNN) that can be easily customizable by musical software • Architectures RNN model for learning musical patterns from large classical music datasets that are expressed in numerical format. • Deplyed the project into the Streamlit by utilizing FastAPI • Built the connection between generated music and musical software Abelton
• Performed high-precision calibration for the radio-frequency antenna for an advanced research instrument. • Established scientific Python & C++ hybrid package, inspired by C++-based code, that extracts physics results from raw data which has led to wildly use by intern
• Classified astronomical signal by statistical-oriented Principal Component Analysis (PCA), after obtaining features from 2 billion amounts (∼200 TB) of radio-frequency data measured below the South Pole. • Implemented automation solutions for utilizing large CPU & GPU clusters by building Python & C++ packages to streamline data analysis workflows and enhance productivity which has led to wildly use by international collaborators. • Implemented physics techniques, such as the Fast Fourier Transform (FFT), Interferometry, and the Matched Filter, into the package for feature extraction. • Optimized the PCA based on Frequentist Statistics and Pseudo Experiment. • Analyzed & quantified results by calculating statistical significance, including systematic uncertainty, and Monte Carlo simulation. • Performed high-precision calibration for the radio-frequency antenna for an advanced research instrument. • Learned large database management, including optimization of data sourcing and efficient connection to supercomputer by using solid analysis pipeline. • Practiced a thorough way to evaluate the project results by using statistical techniques and the back-of-the-envelope calculation.