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bet on myself & beat the odds
bet on myself & beat the odds
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Hi, this is quangtiencs’s log, a homepage of my engineering life. I am Tien Le-Quang (Lê Quang Tiến), a ˈdeɪtə dɪˈtektɪv (a.k.a data detective or data scientist).


Primary interests:

  • Real-world applications: Causal reasoning, Search system.
  • Machine learning methodologies: Bayesian Inference, Probabilistic Deep Learning, Probabilistic Graphical Models.
  • Algorithm for optimizations: Bandit Algorithms, Constraint Programming (CP-SAT problem).

Tech Stack:

  • Programming languages: Python, Julia, Javascript, C++17 (and a little bit of R, Scala)
  • Machine learning frameworks: Tensorflow (and Tensorflow Probability), Stan, LightGBM, Scikit-Learn.
  • Good at data visualizations. Visualization Libraries: d3js, bokeh, matplotlib.

Popular repositories

  1. bayesian-cognitive-modeling-with-turing.jl bayesian-cognitive-modeling-with-turing.jl Public

    Bayesian Cognitive Modeling with Turing.jl (Julia Programming Language)

    Jupyter Notebook 2

  2. Public

    HTML 1

  3. theta-notebook theta-notebook Public

    Jupyter Notebook 4

  4. kdd2021-tutorial kdd2021-tutorial Public

    Forked from causal-machine-learning/kdd2021-tutorial

    EconML/CausalML KDD 2021 Tutorial

    Jupyter Notebook

  5. Machine-Learning-for-Algorithmic-Trading-Second-Edition Machine-Learning-for-Algorithmic-Trading-Second-Edition Public

    Forked from PacktPublishing/Machine-Learning-for-Algorithmic-Trading-Second-Edition

    Code and resources for Machine Learning for Algorithmic Trading, 2nd edition.

    Jupyter Notebook

  6. wasm-crfsuite wasm-crfsuite Public