Paddle Serving: model-as-a-service! Triggered by a single command line, deployment finishes in 10 minutes

To bridge the gap between Paddle Serving and PaddlePaddle framework, we release the new service of PaddleServing: Model As A Service (MAAS) online in Github. With the help of the new service, when a PaddlePaddle model is trained, users now can obtain the corresponding inference model at the same time, making it possible to deploy the deep learning inference service online for any applications. PaddleServing has the following four key features:

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Slideshare (6): Cross-lingual Paper reading notes

During this summer, I did a project on cross-lingual NLP tasks. Recently I was working my notes and I organized them into a better format. I would like to share some of the notes with the readers who might be interested in this topic.


Papers covered:


Prepare for the Interviews!

For the past few years after my Master’s, I did many jobs, long term, short term, internship, or full-time. I also had too many interviews, some of them I failed. Together with my friends, we had collected many materials, including basic algorithms, popular questions, basic machine learning knowledge, and deep learning knowledge. Then I organized them as one huge PDF (150+ pages).

A very brief outline:

  • Sorting
  • Data structure + popular questions
  • Machine Learning 
  • SoftDev interview questions

The material covers some screenshots from other people’s lectures and books. [Some slide pages are not in English! I am too lazy to translate them..]

I went through this PDF each time before there is an interview, in the case to answer questions like “what is knn”.   I hope you may find the material useful.  Download link:


Recently, I am working on a new version by adding more deep learning basics.


New items need to be updated: Merge sort; Sorting code in Python; Boyer-Moore Vote Algorithm.