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Data Processing

SPSS Statistics

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Xiao

@chengxiao

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Biostatistician | Data Analyst | Python & R | Spss

$30 USD / Hour

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China (7:37 AM)

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Joined on June 5, 2012

$30 USD / Hour

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I provide professional data analysis and statistical support for academic and research‑related projects. Proficient in Python, R, SPSS for data cleaning, exploratory analysis, statistical modelling, visualization and result interpretation. Experienced in biostatistics, questionnaire data processing, clinical research data analysis, machine‑learning model implementation. I deliver reproducible scripts, well‑organized output tables and clear documentation for your research.

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Portfolio

Portfolio

Professional data analysis integrating machine learning, deep learning, mathematical statistics and bioinformatics analysis.
Supports survival analysis, time‑series forecast & decomposition, PCA‑Kmeans clustering, regression, binary classification and data visualization.

Build and optimize Random Forest, XGBoost, SVM, MLP, LSTM and CNNdeep‑learning models. Generate publication‑ready figures: Kaplan‑Meier, ROC, calibration curve, DCA, residual plots, boxplots.
Evaluate models with AUC, R², RMSE metrics. Deliver reproducible code, high‑resolution figures & research‑oriented interpretation.

Machine‑Learning & Bioinformatics

Professional data analysis integrating machine learning, deep learning, mathematical statistics and bioinformatics analysis.
Supports survival analysis, time‑series forecast & decomposition, PCA‑Kmeans clustering, regression, binary classification and data visualization.

Build and optimize Random Forest, XGBoost, SVM, MLP, LSTM and CNNdeep‑learning models. Generate publication‑ready figures: Kaplan‑Meier, ROC, calibration curve, DCA, residual plots, boxplots.
Evaluate models with AUC, R², RMSE metrics. Deliver reproducible code, high‑resolution figures & research‑oriented interpretation.

Machine‑Learning & Bioinformatics

Professional data analysis integrating machine learning, deep learning, mathematical statistics and bioinformatics analysis.
Supports survival analysis, time‑series forecast & decomposition, PCA‑Kmeans clustering, regression, binary classification and data visualization.

Build and optimize Random Forest, XGBoost, SVM, MLP, LSTM and CNNdeep‑learning models. Generate publication‑ready figures: Kaplan‑Meier, ROC, calibration curve, DCA, residual plots, boxplots.
Evaluate models with AUC, R², RMSE metrics. Deliver reproducible code, high‑resolution figures & research‑oriented interpretation.

Machine‑Learning & Bioinformatics

Professional data analysis integrating machine learning, deep learning, mathematical statistics and bioinformatics analysis.
Supports survival analysis, time‑series forecast & decomposition, PCA‑Kmeans clustering, regression, binary classification and data visualization.

Build and optimize Random Forest, XGBoost, SVM, MLP, LSTM and CNNdeep‑learning models. Generate publication‑ready figures: Kaplan‑Meier, ROC, calibration curve, DCA, residual plots, boxplots.
Evaluate models with AUC, R², RMSE metrics. Deliver reproducible code, high‑resolution figures & research‑oriented interpretation.

Machine‑Learning & Bioinformatics

Professional data analysis integrating machine learning, deep learning, mathematical statistics and bioinformatics analysis.
Supports survival analysis, time‑series forecast & decomposition, PCA‑Kmeans clustering, regression, binary classification and data visualization.

Build and optimize Random Forest, XGBoost, SVM, MLP, LSTM and CNNdeep‑learning models. Generate publication‑ready figures: Kaplan‑Meier, ROC, calibration curve, DCA, residual plots, boxplots.
Evaluate models with AUC, R², RMSE metrics. Deliver reproducible code, high‑resolution figures & research‑oriented interpretation.

Machine‑Learning & Bioinformatics

Professional data analysis integrating machine learning, deep learning, mathematical statistics and bioinformatics analysis.
Supports survival analysis, time‑series forecast & decomposition, PCA‑Kmeans clustering, regression, binary classification and data visualization.

Build and optimize Random Forest, XGBoost, SVM, MLP, LSTM and CNNdeep‑learning models. Generate publication‑ready figures: Kaplan‑Meier, ROC, calibration curve, DCA, residual plots, boxplots.
Evaluate models with AUC, R², RMSE metrics. Deliver reproducible code, high‑resolution figures & research‑oriented interpretation.

Machine‑Learning & Bioinformatics

Professional data analysis integrating machine learning, deep learning, mathematical statistics and bioinformatics analysis.
Supports survival analysis, time‑series forecast & decomposition, PCA‑Kmeans clustering, regression, binary classification and data visualization.

Build and optimize Random Forest, XGBoost, SVM, MLP, LSTM and CNNdeep‑learning models. Generate publication‑ready figures: Kaplan‑Meier, ROC, calibration curve, DCA, residual plots, boxplots.
Evaluate models with AUC, R², RMSE metrics. Deliver reproducible code, high‑resolution figures & research‑oriented interpretation.

Machine‑Learning & Bioinformatics

Professional data analysis integrating machine learning, deep learning, mathematical statistics and bioinformatics analysis.
Supports survival analysis, time‑series forecast & decomposition, PCA‑Kmeans clustering, regression, binary classification and data visualization.

Build and optimize Random Forest, XGBoost, SVM, MLP, LSTM and CNNdeep‑learning models. Generate publication‑ready figures: Kaplan‑Meier, ROC, calibration curve, DCA, residual plots, boxplots.
Evaluate models with AUC, R², RMSE metrics. Deliver reproducible code, high‑resolution figures & research‑oriented interpretation.

Machine‑Learning & Bioinformatics

Professional data analysis integrating machine learning, deep learning, mathematical statistics and bioinformatics analysis.
Supports survival analysis, time‑series forecast & decomposition, PCA‑Kmeans clustering, regression, binary classification and data visualization.

Build and optimize Random Forest, XGBoost, SVM, MLP, LSTM and CNNdeep‑learning models. Generate publication‑ready figures: Kaplan‑Meier, ROC, calibration curve, DCA, residual plots, boxplots.
Evaluate models with AUC, R², RMSE metrics. Deliver reproducible code, high‑resolution figures & research‑oriented interpretation.

Machine‑Learning & Bioinformatics

Professional data analysis integrating machine learning, deep learning, mathematical statistics and bioinformatics analysis.
Supports survival analysis, time‑series forecast & decomposition, PCA‑Kmeans clustering, regression, binary classification and data visualization.

Build and optimize Random Forest, XGBoost, SVM, MLP, LSTM and CNNdeep‑learning models. Generate publication‑ready figures: Kaplan‑Meier, ROC, calibration curve, DCA, residual plots, boxplots.
Evaluate models with AUC, R², RMSE metrics. Deliver reproducible code, high‑resolution figures & research‑oriented interpretation.

Machine‑Learning & Bioinformatics

Professional data analysis integrating machine learning, deep learning, mathematical statistics and bioinformatics analysis.
Supports survival analysis, time‑series forecast & decomposition, PCA‑Kmeans clustering, regression, binary classification and data visualization.

Build and optimize Random Forest, XGBoost, SVM, MLP, LSTM and CNNdeep‑learning models. Generate publication‑ready figures: Kaplan‑Meier, ROC, calibration curve, DCA, residual plots, boxplots.
Evaluate models with AUC, R², RMSE metrics. Deliver reproducible code, high‑resolution figures & research‑oriented interpretation.

Machine‑Learning & Bioinformatics

Professional data analysis integrating machine learning, deep learning, mathematical statistics and bioinformatics analysis.
Supports survival analysis, time‑series forecast & decomposition, PCA‑Kmeans clustering, regression, binary classification and data visualization.

Build and optimize Random Forest, XGBoost, SVM, MLP, LSTM and CNNdeep‑learning models. Generate publication‑ready figures: Kaplan‑Meier, ROC, calibration curve, DCA, residual plots, boxplots.
Evaluate models with AUC, R², RMSE metrics. Deliver reproducible code, high‑resolution figures & research‑oriented interpretation.

Machine‑Learning & Bioinformatics

Professional data analysis integrating machine learning, deep learning, mathematical statistics and bioinformatics analysis.
Supports survival analysis, time‑series forecast & decomposition, PCA‑Kmeans clustering, regression, binary classification and data visualization.

Build and optimize Random Forest, XGBoost, SVM, MLP, LSTM and CNNdeep‑learning models. Generate publication‑ready figures: Kaplan‑Meier, ROC, calibration curve, DCA, residual plots, boxplots.
Evaluate models with AUC, R², RMSE metrics. Deliver reproducible code, high‑resolution figures & research‑oriented interpretation.

Machine‑Learning & Bioinformatics

Professional data analysis integrating machine learning, deep learning, mathematical statistics and bioinformatics analysis.
Supports survival analysis, time‑series forecast & decomposition, PCA‑Kmeans clustering, regression, binary classification and data visualization.

Build and optimize Random Forest, XGBoost, SVM, MLP, LSTM and CNNdeep‑learning models. Generate publication‑ready figures: Kaplan‑Meier, ROC, calibration curve, DCA, residual plots, boxplots.
Evaluate models with AUC, R², RMSE metrics. Deliver reproducible code, high‑resolution figures & research‑oriented interpretation.

Machine‑Learning & Bioinformatics

Professional data analysis integrating machine learning, deep learning, mathematical statistics and bioinformatics analysis.
Supports survival analysis, time‑series forecast & decomposition, PCA‑Kmeans clustering, regression, binary classification and data visualization.

Build and optimize Random Forest, XGBoost, SVM, MLP, LSTM and CNNdeep‑learning models. Generate publication‑ready figures: Kaplan‑Meier, ROC, calibration curve, DCA, residual plots, boxplots.
Evaluate models with AUC, R², RMSE metrics. Deliver reproducible code, high‑resolution figures & research‑oriented interpretation.

Machine‑Learning & Bioinformatics

Professional data analysis integrating machine learning, deep learning, mathematical statistics and bioinformatics analysis.
Supports survival analysis, time‑series forecast & decomposition, PCA‑Kmeans clustering, regression, binary classification and data visualization.

Build and optimize Random Forest, XGBoost, SVM, MLP, LSTM and CNNdeep‑learning models. Generate publication‑ready figures: Kaplan‑Meier, ROC, calibration curve, DCA, residual plots, boxplots.
Evaluate models with AUC, R², RMSE metrics. Deliver reproducible code, high‑resolution figures & research‑oriented interpretation.

Machine‑Learning & Bioinformatics

Professional data analysis integrating machine learning, deep learning, mathematical statistics and bioinformatics analysis.
Supports survival analysis, time‑series forecast & decomposition, PCA‑Kmeans clustering, regression, binary classification and data visualization.

Build and optimize Random Forest, XGBoost, SVM, MLP, LSTM and CNNdeep‑learning models. Generate publication‑ready figures: Kaplan‑Meier, ROC, calibration curve, DCA, residual plots, boxplots.
Evaluate models with AUC, R², RMSE metrics. Deliver reproducible code, high‑resolution figures & research‑oriented interpretation.

Machine‑Learning & Bioinformatics

Professional data analysis integrating machine learning, deep learning, mathematical statistics and bioinformatics analysis.
Supports survival analysis, time‑series forecast & decomposition, PCA‑Kmeans clustering, regression, binary classification and data visualization.

Build and optimize Random Forest, XGBoost, SVM, MLP, LSTM and CNNdeep‑learning models. Generate publication‑ready figures: Kaplan‑Meier, ROC, calibration curve, DCA, residual plots, boxplots.
Evaluate models with AUC, R², RMSE metrics. Deliver reproducible code, high‑resolution figures & research‑oriented interpretation.

Machine‑Learning & Bioinformatics

Professional data analysis integrating machine learning, deep learning, mathematical statistics and bioinformatics analysis.
Supports survival analysis, time‑series forecast & decomposition, PCA‑Kmeans clustering, regression, binary classification and data visualization.

Build and optimize Random Forest, XGBoost, SVM, MLP, LSTM and CNNdeep‑learning models. Generate publication‑ready figures: Kaplan‑Meier, ROC, calibration curve, DCA, residual plots, boxplots.
Evaluate models with AUC, R², RMSE metrics. Deliver reproducible code, high‑resolution figures & research‑oriented interpretation.

Machine‑Learning & Bioinformatics

Professional data analysis integrating machine learning, deep learning, mathematical statistics and bioinformatics analysis.
Supports survival analysis, time‑series forecast & decomposition, PCA‑Kmeans clustering, regression, binary classification and data visualization.

Build and optimize Random Forest, XGBoost, SVM, MLP, LSTM and CNNdeep‑learning models. Generate publication‑ready figures: Kaplan‑Meier, ROC, calibration curve, DCA, residual plots, boxplots.
Evaluate models with AUC, R², RMSE metrics. Deliver reproducible code, high‑resolution figures & research‑oriented interpretation.

Machine‑Learning & Bioinformatics

Professional data analysis integrating machine learning, deep learning, mathematical statistics and bioinformatics analysis.
Supports survival analysis, time‑series forecast & decomposition, PCA‑Kmeans clustering, regression, binary classification and data visualization.

Build and optimize Random Forest, XGBoost, SVM, MLP, LSTM and CNNdeep‑learning models. Generate publication‑ready figures: Kaplan‑Meier, ROC, calibration curve, DCA, residual plots, boxplots.
Evaluate models with AUC, R², RMSE metrics. Deliver reproducible code, high‑resolution figures & research‑oriented interpretation.

Machine‑Learning & Bioinformatics

Professional data analysis integrating machine learning, deep learning, mathematical statistics and bioinformatics analysis.
Supports survival analysis, time‑series forecast & decomposition, PCA‑Kmeans clustering, regression, binary classification and data visualization.

Build and optimize Random Forest, XGBoost, SVM, MLP, LSTM and CNNdeep‑learning models. Generate publication‑ready figures: Kaplan‑Meier, ROC, calibration curve, DCA, residual plots, boxplots.
Evaluate models with AUC, R², RMSE metrics. Deliver reproducible code, high‑resolution figures & research‑oriented interpretation.

Machine‑Learning & Bioinformatics

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Tianjin University

2008 - 2011

•

3 years

master

China

2008 - 2011

•

3 years