Repository contains somethings about materials, code and papers for Traing Phase 1 DSLab, International Center BKAI.
Phase 1 training focuses on all the fundamentals of Machine Learning and Deep Learning, practice in domain NLP. You can practice right now with the Google Colab badge above.
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materials: All lectures of course Machine Learning IT3190E of HUST, taught by Assoc Prof Than Quang Khoat - Team Leader DSLab -
ss1: Season 1 focus Preprocessing text documents with TF-IDF and Ridge Regression -
ss2: Season 2 focus K-Means & SVM -
ss3: Season 3 focus ANN -
ss3: Season 4 focus time-series data, specifying RNNs
Each season we have:
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ss/data: Store data raw/processed for training -
ss/materials: Some papers for research -
ss/src: Source code
I was in training Phase 2 DSLab, about the Probabilistics Graph Model, which needed a large amount of mathematics, specifying Prob Stat. I will sometimes update the repo about it, but if you're interested, I recommend the course PGM CS228 of Stanford. I hope you love it!
And I know people who read this README.md want to join DSLab and I think you know me. Application forms will be opened in August each year on BKAI. You have 2 months to wait to check your pending CV, and people who passed will announce in last September if your CV is very good. You have your first interview at the beginning of October, and then you have 3 months to train in math by yourself on your way to interview 2. Total time needed to become a DSLab official member may be approximately 6 months.
Don't worry about it because I'm also not good at math and still passed it. Good luck for all, hope see you soon at DSLab ^^