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Imbalanced Data Preprocessing in Big Data Approaches
⼤數據實作：資料不平衡前處理⽅法
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"Exact and Approximate SMOTE Algorithms for Handling Imbalanced Big Data in PySpark"
- Issues: SMOTE, an over-sampling technique, utilises the nearest neighbours algorithm to synthesise new data, while NN doesn’t inherently scale well to big datasets
- Aims: coming up with an efficient implementation of the SMOTE algorithm for big datasets in PySpark
- Developing 4 approaches to address this issue: a local solution, an approximate global solution, an exact global solution, and an exact solution for ENN, a down-sampling variant of SMOTE
- Introducing KDTree to look for the nearest neighbours in NN to reduce time complexity
- Generating a 3.7K words of paper report and a 12-minute presentation
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- Python (sklearn, PySpark, matplotlib)
- DataBricks: main platform to perform experiments in big datasets
- Microsoft PowerPoint: Presentation

⼤數據實作：資料不平衡前處理⽅法

MSc Data Science Graduated | Seeking Junior Data Engineer Jobs | Data-driven Decision-making | Problem-solving |

陳亭君

Time Series Analysis
時間序列分析
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1. Analysing the daily nitrous oxides level from Feb 2017 to Sep 2017
- Identifying stationary, trend and seasonality
- Fitting an ARIMA(1,0,0) x (0,1,1)_7 model to the data and checking the residuals
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2. Analysing the number of car registrations quarterly from 2001 to 2022
- Identifying stationary, trend and seasonality
- Fitting an ARIMA(0,1,1) x (0,1,1)_4 model to the data and checking the residuals
- Forecasting: predicting the car registration number for the next year
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- R (ts, arima, forecast, plot)
- Notion: project management and generating report

時間序列分析

Word Embedding in FinTech Literature
⾦融科技文獻⾃然語⾔處理
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This is a summer project for the MSc dissertation,
"Comparative Analysis of Word Embedding Methods for Citation Sentence Matching in FinTech Literature"

- Aim: finding the best text embedding method for fintech literature
- Data collection: collecting 3,500 fintech-related scientific articles
- Data structuring: converting PDFs to plain texts and matching citation sentences to the reference article
- Data preprocessing: handling special characters(ex: ligature), applying tokenisation, removing stop words and applying lemmatisation to construct our own fintech literature dataset
- 8 text embedding methods are introduced to evaluate the similarity between a citation sentence and its reference article as performances of embedding methods
- Including TF-IDF, LSA, word2vec, GloVe, FastText, ELMo, USE, and BERT
- generating a 10K words dissertation and a 15-minute presentation
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- Python (sklearn, NLTK, genism, matplotlib): main coding of PDF preprocessing, NLP modeling, data analysis
- Microsoft Excel: generating plots
- Microsoft PowerPoint: presentation
- draw.io: generating plots

⾦融科技文獻⾃然語⾔處理

Recurrence and Survival Prediction for Liver Cancer
肝癌復發及存活預測
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This project was hosted by National Yang Ming Chiao Tung University and Taipei Veterans General Hospital and supported by the Ministry of Science and Technology, Taiwan,
"Evolutionary Learning-Derived Clinical-Radiomic Models for Predicting Early Recurrence of Hepatocellular Carcinoma after Resection"

- Developing an evolutionary learning-derived method GARSL, genetic algorithm for predicting recurrence after surgery of liver cancer
- Converting medical images (CT) into radiomics features and combining them with clinical laboratory testing features
- Using evolutionary learning to optimise and predict 5-year recurrence for HCC patients who underwent partial resection operation and 3-year survival for HCC transarterial chemoembolisation(TACE) patients
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- Matlab: data structuring, converting RTSS (data structure for medical images) to jpg, tumour contouring, generating radiomics features, data cleaning
- Python (sklearn, numpy, matplotlib): ML modeling, data cleaning, generating plots
- Basic Linux command lines: evolutionary learning (modelling and optimisation)
- Microsoft Excel: data cleaning
- Microsoft PowerPoint: weekly and monthly meeting

肝癌復發及存活預測

Traffic Incidence Management System
資料庫實作：交通事故登錄系統 
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A web UI to interact with SQL database to register, edit and query for traffic incidence, create officer accounts and manage audit trails.
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- MySQL: construct and manage tables
- HTML: WebUI design
- PHP: enabling HTML to interact with MySQL and controlling login identification

資料庫實作：交通事故登錄系統 

Dedicated and friendly data analyst with a 1-year experience in AI, data mining and statistical analysis, currently graduating from the University of Nottingham. Keen to utilise my skills in modeling and visualisation to provide critical recommendations for decision-making with a heavy emphasis on great communication between stakeholders and technical team members.

University of Nottingham

National Yang Ming Chiao Tung University

陳亭君 敬業且熱情的資料工程師，在人工智慧、資料探勘和統計分析方面擁有 1 年經驗，目前畢業於諾丁漢大學及陽明交通大學。我擅長利用在模式識別和機器學習方面的技能，為公司開發可靠的數據模型及預測方法，發揮資料的最大利益。 Taipei City, Taiwan 教育程度 2023 英國諾丁漢大學...

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