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aigaosheng/README.md

Who am I?

I'm currently a data scientist in an e-commerce company, working on interesting projects such as competitive intelligence, smart voucher, category prediction. I am interesting to develop efficient and robust productive systems. Before joining the current company, I'm leading a data science team (~5 members) in a media company, working on user profiling, news recommendation, news tag classification, media content view forcasting. Jumping into industry happened after 16-year researching & developing in a*star, Singapore as a research scientist. Just want to open eye on industry product development.

Some project stuffs

Competitive intelligence

  • Understaing assortment & price competitive of products in platform

Smart voucher

  • Personalized voucher recommendation

Digital optimizer

  • Building personized ads recommendation system to improve CTR in media domai

Media content view forcasting

  • Predicting how many users will view media (news, radio, video) contents when published

News tagging

  • Tagging news with IAB taxonomy (customized) for English, Chinese, Malay & Hindu

Speech recognition

  • Acoustic model, language model + search engine + real-time system optimization

Audio fingerprint

  • Support mobile phone based audio search (product system developed for a tech company among BAT)

Image tagging

  • Tagging image with semantic category

Sentiment classification

  • Classify social media content as positive, neutral, and negative

......

Popular repositories Loading

  1. dns_challenge_code dns_challenge_code Public

    Python 3 1

  2. speech_vc speech_vc Public

    this is to investigate voice conversion

    Python 2

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    buy/sell/hold signal prediction & price regression

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  4. backtrader_reload backtrader_reload Public

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  5. pyltp pyltp Public

    Forked from HIT-SCIR/pyltp

    pyltp: the python extension for LTP

    C++

  6. TextCleanser TextCleanser Public

    Forked from gouwsmeister/TextCleanser

    Normalizes lexically ill-formed text to its most likely clean text, e.g. "c u thr 2nite!" -> "see you there tonight!".

    Python