I wanna be the guy

嗨,我是楊凱州,目前是個平凡的研究生,正在探索人工智慧與資料科學的藝術,期許自己有朝一日能成為 Kaggle 與 Gym 的大魔王。 我喜歡關注各式各樣的開源會議,熱衷於嘗試一些天馬行空的發想,藉由開發一些有趣的小專案自娛娛人,同時也提高自己的實務水平。

我也是雷德麥的藏書閣與 NCKUCSIE Notes 的作者, 閒暇之餘會寫些技術報告或學習心得。 我相信技術是為了生活而存在,而致力於用說故事的方式, 搭配上生活化例子擊破那些艱澀的理論。 若您在文章的實作上遭遇到了困難,還是發現內容存在有待加強的地方, 都歡迎藉由 G-mail 與我分享您的觀點,期待透過討論能讓彼此更加強大 ヾ(´︶`*)ノ

Education

國立成功大學

Department of Computer Science July 2013 - July 2017

伴我從新手村走到二轉之路的好夥伴。 一路上挑戰了形形色色的演算法與資料結構,從中認識了不少程式語言,建構出許許多多妙趣橫生的專案。 觀過網路架構的層巒疊嶂,體會過模糊理論的道不清說不明,玩轉過了一道又一道的密碼矩陣, 還有更多更多沒提到的精彩冒險,且讓我日後在藏書閣中娓娓道來吧。

  • 二年級上下學期書卷獎
  • 三年級上下學期書卷獎
  • Experiences

    CIKM AnalytiCup

    2nd place August 2018

    This competition is about short-text semantic similarity and cross-lingual knowledge transfer. I design three deep learning models based on different hypotheses and create the variety intra-model by mixing various views of input data.

    WSDM Cup

    3rd place February 2019

    This is a challenge for Chinese fake-news detection. I implemented various NLI networks and inject the world knowledge using BERT and proposed a rumor-aware model which is inspired by decomposable attention.

    Gendered Pronoun Resolution on Kaggle

    4th place April 2019

    Pronoun resolution is part of coreference resolution, the task of pairing an expression to its referring entity. In this task, I conducted extensive analysis among hidden layers of BERT and proposed a multi-head siamese scorer for answer selection.

    KDD Cup

    top 1% May 2018

    Aim at predicting concentration levels of PM2.5, PM 10 and O3 over the coming 48 hours for Beijing and London. I reach top 1% without any external data by an end to end sequence generative network that fuses the views from regional and sequential information efficiently.

    Toxic Comment Classification Challenge on Kaggle

    top 1% February 2018

    A challenge for multi-label sentence classification. To identify the toxic comments, I present two simple and easy-to-use architectures for generating reliable sentence embeddings and ensemble them with gradient boosting trees.

    WSDM - KKBox's Music Recommendation Challenge on Kaggle

    top 1% November 2017

    The goal is to predict the chances of a user listening to a song repetitively after the first observable listening event within a time window was triggered. I model the user and song pair by deep factorization machine and gradient boosting trees with effective feature engineering.

    Works

    創新系統軟體應用實驗室

    兼任助理 July 2015 - August 2015

    使用 Smarty 與 JQuery 維護成功大學醫學院 e 化學習系統,並針對現有的 Bug 進行除錯。 以及協助進行農業地理資訊統計,調用 GoogleMap API 進行地圖打點和編寫地址至經緯度的批量轉換器。

    網路探勘暨跨語知識系統實驗室

    研究員 July 2016 - February 2017

    執行科技部大專生研究計畫,實作具即時語音信息擷取功能之緊急任務救助服務匹配系統,採用自然語言處理技術,抽取短語中的潛在意圖,並透過定義缺漏特徵的個數,以構件多輪式的對話情境。

    胖地 Punplace

    資訊服務人員 March 2015 - July 2015

    以自身技術協助其他社會福利機構,如 Excel 的表單統計與函式除錯,個人在程式上的學習經驗分享等等。

    Skills

    • Python
    • C++
    • Java
    • C#
    • Scikit-Learn
    • PyTorch
    • Keras
    • TensorFlow

    Client Testimonials

    • Your time is limited, so don't waste it living someone else's life. Don't be trapped by dogma - which is living with the results of other people's thinking. Don't let the noise of others' opinions drown out your own inner voice. And most important, have the courage to follow your heart and intuition.

      Steve Jobs
    • If you don’t make mistakes, you’re not working on hard enough problems. And that’s a big mistake.

      Frank Wilczek
    • Start by doing what's necessary; then do what's possible; and suddenly you are doing the impossible.

      Francis of Assisi