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Does anyone know something similar but for data projects/science? Preferably something with practical data, not just the math.

• eshyong 8y ago
  I've heard good things about Andrew Ng's Coursera machine learning class, and it's free: https://www.coursera.org/learn/machine-learning https://www.coursera.org/learn/machine-learning There is a free intro to data science class on Udacity as well: https://www.udacity.com/course/intro-to-data-science--ud359 https://www.udacity.com/course/intro-to-data-science--ud359 Lastly, there's always Kaggle, which has plenty of resources to learn from, and competitions as well: https://www.kaggle.com/ https://www.kaggle.com/
  • gamedna 8y ago
    I can vouch for Andrew Ng's class. Its really top notch.
• maccard 8y ago
  I'm in the same boat, I've been toying with kaggle recently. They have some guided tutorials done via notebooks with some data that seems to be heading towards playing with the data myself. I recommend it as it's interesting, has me playing with data, and is consumable le, but I don't have enough experience to give an informed opinion on it.
• jointpdf 8y ago
  ISLR is a good one—it’s focused on practical theory, but there’s still some unavoidable math. Code exercises are simple (and ugly—stats professor code) but gives you the basics to build on. Book/code: http://www-bcf.usc.edu/~gareth/ISL/ http://www-bcf.usc.edu/~gareth/ISL/ Lectures: https://www.r-bloggers.com/in-depth-introduction-to-machine-learning-in-15-hours-of-expert-videos/amp/ https://www.r-bloggers.com/in-depth-introduction-to-machine-...
  • jointpdf 8y ago
    Also: this was recommended on HN recently and it’s the best intro to matrix algebra / basic math of ML that I’ve seen. Lots of very practical and relevant exercises that relate to real data science tasks like text and image analysis. Code examples are in Julia. http://vmls-book.stanford.edu/ http://vmls-book.stanford.edu/ And one more gold standard for more practical data science (with R) stuff. It introduces a more modern take on R (chaining functions together with the %>% pipe operator, which makes everything clean and terse). https://r4ds.had.co.nz/ https://r4ds.had.co.nz/
• skadamat 8y ago
  We're aiming to do this at Dataquest (where I work). Essentially create a complete learning path from 0 to job ready. Data Scientist path - https://www.dataquest.io/path/data-scientist https://www.dataquest.io/path/data-scientist Some of the projects peppered throughout the track: https://www.dataquest.io/projects https://www.dataquest.io/projects EDIT: Forgot to mention, almost every lesson uses a real dataset!