β‘ Fun fact: A human really love sea π Skateboarding πΉ Guitar πΈ and photography πΉ
As a Data Scientist πΎ
My skills: Programming & Tools: Python (Pandas, Sklearn, Matplotlib, Seaborn, NetworkX, Nature Language Toolkit),
SQL (Advanced), Tableau, PowerBI, R (RCT, DID, RDD, IV), PySpark, AWS, Google Analytics, MS Office
Specialization: supervised methods (decision tree, KNN, Ensemble methods, Naive Bayes and SVM)
and unsupervised methods (PCA, Clustering, Text Mining and Analysis and Association Analysis)
Deployed K-core decomposition to examine the community structure, applied NLP including Name Entity
Recognition, Sentimental Analysis and Topic Modelling on tweets to investigate the emotion cascade
Using PCA and UMAP to visualize the participantsβ stance on a 2-dimensional map, uses Kmeans to cluster and classify group A and B,
and uses centroid coords calculation to get the distance between two groups.
Built and trained Logistic Regression, DecisionTree, SVM, RandomForest, XGBoost and GBDT to identify 5
primary indicators and 35 secondary indicators
the key influential factor on the attitude of EU citizen towards UBI
Developed a multivariate model in STATA incorporating Difference-in-Difference and Propensity Score Matching
Estimated the indirect effects and direct impacts of remittances in the context of parental work-related migration on
the well-being and academic achievements of left-behind children.