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Some directions to choose when you have covered basics of Machine Learning:
- deep learning (cs231n)
- theory of ML
- more practice, Kaggle
- first job in Data Science
- pet project
Some words on the fall 2018 session of

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  1. 1. Further steps when basic ML is covered
  2. 2. How it all started, spring 2017 520 started with A1 120 finished A10
  3. 3. Fall 2018 2200 started with A1 ~400 finished A10
  4. 4. What next? 1. New session - Feb 2019 More competitions! 2. #class_cs231n – from 24.12.18, Slack «Convolutional Neural Networks for Visual Recognition» Andrej Karpathy Fei-Fei Li Stanford
  5. 5. 3. Dive into theory of ML -> #edu_books -> #article_essence 4. More practice -> #kaggle_crackers -> #mlcourse_ai «Pattern Recognition & Machine Learning» (C. Bishop) «Deep Learning» (I. Goodfellow 5. First job in DS –> #career What next?
  6. 6. What next? 6. Pet project
  7. 7. What next? 7. Support (monthly) (one-time) Tell your story and spread a word! Kaggle Forum
  8. 8. See you in #class_cs231n! Thanks to team!