4 ms·

Ask HN: How to learn machine learning on my own?

• selmat 10y ago
  There were plenty of similar threads with very valuable resources. Let me mention some of them: > https://news.ycombinator.com/item?id=11663952 https://news.ycombinator.com/item?id=11663952 > https://news.ycombinator.com/item?id=11509921 https://news.ycombinator.com/item?id=11509921 > https://news.ycombinator.com/item?id=11887147 https://news.ycombinator.com/item?id=11887147 > https://news.ycombinator.com/item?id=198601 https://news.ycombinator.com/item?id=198601 > https://news.ycombinator.com/item?id=11883490 https://news.ycombinator.com/item?id=11883490 Best google phrase is: "machine learning site:news.ycombinator.com" I have list of resources I am going to read but day has only 24 hours.
  • tixocloud 10y ago
    Thanks! Appreciate your help.
• arcanus 10y ago
  The MOOC on coursera is an excellent place to pick up some basic terminology and simple algorithms. It is taught at an undergraduate level, so it is rather accessible.
  • saiko-chriskun 10y ago
    he's already taken coursera courses and looking for further resources.
• ddxv 10y ago
  My style is that I like constantly trying to put myself further into something I don't understand. If you read about something interesting in this forum, just go straight into trying it out. Install everything you can, test out the languages, packages and tools to the best of your ability. The more you don't understand, the better you're doing! Keep asking questions. Keep trying tutorials. Keep pushing into what you find confusing and difficult. I can't say for sure this is a great method of learning, but it's the style I enjoy most. Good luck, and thanks for opening this thread.
  • tixocloud 10y ago
    Thanks for your thoughts. I was thinking about picking a project to work on and using that as my motivation. I find myself sometimes just losing focus after watching the videos. Do you ever experience that?
    • arsenide 10y ago
      Not sure about OP, but I certainly feel this way. When I want to learn a new language/framework I work on a project using it; instead of watching videos I mostly use the docs and Google/SO when I get stuck or have a code design question, possibly watching/reading any seemingly interesting videos/articles I happen to come across along the way.
    • ddxv 10y ago
      Yes, I know that feeling too. =) I get bored too. As soon as I know enough to start my own small project I do it. Even if it's not something I could ever put on the Internet, it is enough that it makes me interested again in understanding what I am learning.
• sl8r 10y ago
  What are you looking for in particular? If you're looking to gain functional familiarity / put in practice reps with classical classification & regression algorithms, I think that running through the online tutorials for scikit-learn is the best bet. If you're looking for the theory behind the above, I think the book by Peter Flach is the best intro; "Elements of Statistical Learning" is the classic tome, but much more mathematically motivated. If you're looking for more specialized subjects, each has its own resources. Bayesian modeling? Gelman's BDA3 and Cam David Pilson's github book. Gaussian processes? Rasmussen. Etc., etc. for neural networks, reinforcement learning, etc. As a random recommendation: David Mumford's "Information theory" is eclectic and fun, but disconnected from the mainstream.
  • tixocloud 10y ago
    I'm looking to gain functional familiarity but also at the same time working on real world applications. Did you mean David Mumford's "Pattern Theory"? It was the only book I could find that's close to the topic. Unless I'm looking at the wrong David Mumford?
• gtani 10y ago
  this sub's wiki is pretty comprehensive: https://www.reddit.com/r/MachineLearning/wiki/index https://www.reddit.com/r/MachineLearning/wiki/index If you want to be taken seriously, you need to learn calculus, linear algebra, convex optimization, probability/statistics. So Khan academy, edX, coursera, etc MOOCs and open content books: https://www.reddit.com/r/MachineLearning/comments/1jeawf/machine_learning_books/ https://www.reddit.com/r/MachineLearning/comments/1jeawf/mac...
• DrNuke 10y ago
  The best way is to focus on one industry or application (e-commerce, natural language, image recognition and so on) you are really passionate about and start practicing theory and models from there. Machine learning is a bag of tools, the most important point is still the business model asking for it, why and how: target, metrics, execution, validation, deployment.
• justkd 10y ago
  Udacity also offers a free course on machine learning: https://www.udacity.com/course/intro-to-machine-learning--ud120 https://www.udacity.com/course/intro-to-machine-learning--ud... You will start with mini projects and will also work towards a final project: "searching for signs of corporate fraud in Enron data"
  • tixocloud 10y ago
    Thanks! That could actually be my next step.
• smcguirk 10y ago
  I just started the book "The Master Algorithm" by Pedro Domingos. The start seemed a bit to much of a sell, but the basic approaches to understanding the direction of this discipline seem sound.
• venkasub 10y ago
  Start attempting Data Science competitions; the learning rate just exponentially explodes. Also, look at the solutions from past exercises, it really helps in how different people solve the same problem with different approaches.