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Stay
Calm
Keep
Current
&
Poll #1 How experienced are you
with Machine Learning?
Liad Magen
Tech & AI Lead
Software Developer
Computer Science
Biomedical Engineering
Blogs & Sites
● reddit.com/r/MachineLearning
● Distill.pub
● TowardsDataScience.com
● OpenDataScience.com
● DAIR: medium.com/dair-ai
● MIT - TechnologyReview.com
● Johns Hopkins Data Science Lab - jhudatascience.org
● ShortScience.org - Paper summary
● Sci-hub
Newsletters
● Data Machina - @ds_ldn
www.getrevue.co/profile/datamachina
● The Wild Week in AI - @dennybritz
www.getrevue.co/profile/wildml
● Import AI - @jackclarksf
jack-clark.net
● Data Science:
○ DataElixir.com - @lonriesberg
○ Johns Hopkins Data Science Lab
Community
● Twitter
○ Andrew Ng - @AndrewYNg
○ Yann LeCun - @ylecun
○ Andrej Karpathy - @karpathy
● Google Scholar
● NIPS - nips.cc
● ICML - icml.cc
● ACL (Computational Linguistics)
● Journal of Machine Learning Research - jmlr.org
● PLOS - Computational Biology
Publication Filtering Engines
● Arxiv Recent papers - arxiv.org/list/cs.LG/recent
● Scirate.com ( Statistics -> Machine Learning )
● Deeplearn.org
● CiteULike.org
● Mendeley.com
● Arxiv Sanity Preserver - www.arxiv-sanity.com
○ Slack-Bot: github.com/thundergolfer/arXie-Bot
● deepai.org/arxiv
● SemanticScholar.org (AllenAI)
GitHub.com/Keep-Current
Vladimir Vilchinsky
Tieto
Thomas Treml
daten sensorium
Keep-Current
GitHub.com/Keep-Current
● Locate
● Filter
● Summarize
● Adapt
DataBase Wrapper
Centrifuge - NLP Engine
Web Crawler + Content Scraper
Text Extractor
Readability PDF2Text
DocumentUser
Topic Modeling
Newsletter
Recommender System
Preprocessing
Summarization
Message
Broker
Web-App Facade
Relation
(GraphDB)
Centrifuge - Information Filtering Engine
github.com/Keep-Current/Engine
● Topic / Keywords Extraction
○ TF-IDF
○ TextRank / RAKE / TAKE Ensemble
Pay, Tayfun, and Stephen Lucci. "Automatic keyword extraction: An ensemble method." Big Data (Big Data), 2017 IEEE
International Conference on. IEEE, 2017.
● Probabilistic Topic Modeling
○ LDA
Blei, D. M., Ng, A. Y., & Jordan, M. I. (2003). Latent dirichlet allocation. Journal of machine Learning research, 3(Jan), 993-
1022.
Centrifuge - Information Filtering Engine
● Recommender System
○ Proximity Measurement
■ Word Embedding - Doc2Vec
○ Collaborative Filtering (CF)
C. Wang and D. Blei. Collaborative topic modeling for recommending scientific articles. In SIGKDD, pages
448–456. ACM, 2011.
○ Contextual Bandits
Li, L., Chu, W., Langford, J., Schapire, R.E.: A contextual-bandit approach to personalized news article
recommendation. In: Proceedings of the 19th international conference on World Wide Web, ACM (2010) 661–670
The results improve by your
feedback
Adaptation &
UI/UX
Roadmap :: Model Rationalization
● LIME
Ribeiro, Marco Tulio, Sameer Singh, and Carlos Guestrin. "Why should i trust you?: Explaining the predictions of any
classifier." Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. ACM,
2016.
● Reasoning
○ Lei, Tao, Regina Barzilay, and Tommi Jaakkola. "Rationalizing neural predictions." arXiv preprint arXiv:1606.04155
(2016).
○ Janner, Michael, Karthik Narasimhan, and Regina Barzilay. "Representation learning for grounded spatial
reasoning." arXiv preprint arXiv:1707.03938 (2017).
Join us @
GitHub.com /
Keep-Current
Work Shop
Meet-Up #1
Today
13:00
Room 2.31
Bring your laptop!
Thank You

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Stay Calm & Keep Current

  • 2. Poll #1 How experienced are you with Machine Learning?
  • 3. Liad Magen Tech & AI Lead Software Developer Computer Science Biomedical Engineering
  • 4.
  • 5. Blogs & Sites ● reddit.com/r/MachineLearning ● Distill.pub ● TowardsDataScience.com ● OpenDataScience.com ● DAIR: medium.com/dair-ai ● MIT - TechnologyReview.com ● Johns Hopkins Data Science Lab - jhudatascience.org ● ShortScience.org - Paper summary ● Sci-hub
  • 6. Newsletters ● Data Machina - @ds_ldn www.getrevue.co/profile/datamachina ● The Wild Week in AI - @dennybritz www.getrevue.co/profile/wildml ● Import AI - @jackclarksf jack-clark.net ● Data Science: ○ DataElixir.com - @lonriesberg ○ Johns Hopkins Data Science Lab
  • 7. Community ● Twitter ○ Andrew Ng - @AndrewYNg ○ Yann LeCun - @ylecun ○ Andrej Karpathy - @karpathy ● Google Scholar ● NIPS - nips.cc ● ICML - icml.cc ● ACL (Computational Linguistics) ● Journal of Machine Learning Research - jmlr.org ● PLOS - Computational Biology
  • 8. Publication Filtering Engines ● Arxiv Recent papers - arxiv.org/list/cs.LG/recent ● Scirate.com ( Statistics -> Machine Learning ) ● Deeplearn.org ● CiteULike.org ● Mendeley.com ● Arxiv Sanity Preserver - www.arxiv-sanity.com ○ Slack-Bot: github.com/thundergolfer/arXie-Bot ● deepai.org/arxiv ● SemanticScholar.org (AllenAI)
  • 9.
  • 13. DataBase Wrapper Centrifuge - NLP Engine Web Crawler + Content Scraper Text Extractor Readability PDF2Text DocumentUser Topic Modeling Newsletter Recommender System Preprocessing Summarization Message Broker Web-App Facade Relation (GraphDB)
  • 14. Centrifuge - Information Filtering Engine github.com/Keep-Current/Engine ● Topic / Keywords Extraction ○ TF-IDF ○ TextRank / RAKE / TAKE Ensemble Pay, Tayfun, and Stephen Lucci. "Automatic keyword extraction: An ensemble method." Big Data (Big Data), 2017 IEEE International Conference on. IEEE, 2017. ● Probabilistic Topic Modeling ○ LDA Blei, D. M., Ng, A. Y., & Jordan, M. I. (2003). Latent dirichlet allocation. Journal of machine Learning research, 3(Jan), 993- 1022.
  • 15. Centrifuge - Information Filtering Engine ● Recommender System ○ Proximity Measurement ■ Word Embedding - Doc2Vec ○ Collaborative Filtering (CF) C. Wang and D. Blei. Collaborative topic modeling for recommending scientific articles. In SIGKDD, pages 448–456. ACM, 2011. ○ Contextual Bandits Li, L., Chu, W., Langford, J., Schapire, R.E.: A contextual-bandit approach to personalized news article recommendation. In: Proceedings of the 19th international conference on World Wide Web, ACM (2010) 661–670
  • 16. The results improve by your feedback Adaptation & UI/UX
  • 17. Roadmap :: Model Rationalization ● LIME Ribeiro, Marco Tulio, Sameer Singh, and Carlos Guestrin. "Why should i trust you?: Explaining the predictions of any classifier." Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. ACM, 2016. ● Reasoning ○ Lei, Tao, Regina Barzilay, and Tommi Jaakkola. "Rationalizing neural predictions." arXiv preprint arXiv:1606.04155 (2016). ○ Janner, Michael, Karthik Narasimhan, and Regina Barzilay. "Representation learning for grounded spatial reasoning." arXiv preprint arXiv:1707.03938 (2017).
  • 18. Join us @ GitHub.com / Keep-Current
  • 19. Work Shop Meet-Up #1 Today 13:00 Room 2.31 Bring your laptop!