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Skills Summary

I love learning from first principles, writing efficient code, visualising large datasets, training machine learning and deep learning algorithms on large datasets, and exploring causal effects and science that connects the dots.

  • Fields of Interest: Data Science, Data Analytics, Causal Inference, Machine Learning, Software Development
  • Key Skills: Querying Databases, Creating Dashboards, Data Analysis and Storytelling, Developing Machine Learning and Deep Learning Models, Mathematical Modelling and Simulation
  • Machine Learning and Statistical Learning Methods: Linear Regression, Logistic Regression, k-NN, SVM, Naive Bayes, Decision Tree, Random Forest, XGBoost, LightGBM, k-means clustering, t-SNE, EM Algorithm, Hypothesis Testing
  • Deep Learning: MLP, CNN, RNN, LSTM, word2vec, seq2seq, Transformer, VAE, GAN
  • Basic Software Skills: RESTful APIs, Web Design with HTML and CSS, Web Scrapping, Continuous Integration and Build System
  • Right now, I'm deepening my knowledge of SQL & Databases, Data Visualisation, Data Cleaning and Pre-processing, Causal Inference, Machine Learning, and Software Development.