Hình đại diện của pbcquoc
Cờ của Vietnam Hồ Chí Minh, Vietnam
Làm thành viên từ Ngày 26 tháng 08 năm 2016
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Trực tuyến Ngoại tuyến
I have 2 years working experience with deep learning, machine learning. Working at FPT Telecom My expertise in build and train novel/cutting-edge deep learning models (Attention, Seq2Seq, GAN, CycleGAN, Memory Network, LSTM, GRU) and many kinds of traditional machine learning models to solve real task. I work cross domain from natural language processing, audio to image. I have built many CNN model to solve classification, detection, image caption task. I also work with LSTM model to make sentence generator, sentiment analysis, predict next word of sentence, and various artificial intelligence task such as title product quality, build Chat Bot. I have participated in Kaggle, Codalab to solve problems with competitive model and almost i can top in 10% leaderboard. I have knowledge about various fields: regression task, classification task, time series analysis, build deep learning model to adapt to special task such as model can run on small memory device.
$5 USD/hr
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Trải nghiệm

Recommender System Platform

Sep 2016

My company business grow, we need a system that must to be scalable, flexible, easy to integrate new model, support AB testing which is an well-known business metrics, and lastly, realtime adapt to user when they watch new movies or musics. I proposal an architecture which combine Spofity’s recommender system and Netflix’s recommender system, and lead 4 teammates to build the system.

Music recommender system

Sep 2016

I proposal and build a music recommender system using Generative Adversarial Networks which is a novel deep learning model. The input to system is rely on only raw audio so songs can be suggested without any meta-data. The input is converted to MFCC features and pass to my model to learn representation, then i use cosine similarity for ranking songs. My system result is impressive than other based on meta-data

Lead Recommender System

Sep 2016

I build a movie recommender system to serve 600k users using PredictioIO, MLLib Spark, Scala. In detail, I implement Alternative Least Square for Collaborative Filtering approach and Single Value Decomposition for Content-Base approach, after that i combine these models using a linear model. My system improves performance to 500% rps and Click-Through-Rate increase 40%

Side Projects

Jan 2016

- Research and build chat bot using seq2seq which is LSTM encoder that encode sequence to fixed vector and try to decode into answer. I crawl tweet and comments as question and answer to train my model. - Design architecture and build deep learning model ( for localization, detection, classification) that can run on small cheap device that have less than 512MByte memory and slow processor.

Giáo dục


2012 - 2016 (4 years)

Bằng Cấp

The Best Thesis (2016)

Ho Chi Minh City University of Science

We implement a novel model to generate image description. Our approach is association of two most successful deep learning models in Computer Vision and Natural Language Modeling that known as Convolution Network and Long Short-Term Memory. Our result can help blind man to see the world

Message Prediction Competition (2017)


8th/220, Predict a message given the first letters of each word

CIKM AnalytiCup 2017: Lazada Product Title Quality Challenge (2017)


20th/450, build a product title quality model that can automatically grade the clarity and the conciseness of a product title.

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