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I'm interested in various machine learning methods and wonder how can I aim for a career in the field. What are most basic skills to have?

I mean the matters strictly connected to the machine learning - not programming or libraries.

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    $\begingroup$ I'm sorry I need to vote it close as opinion-based :( Can you edit it and be a bit more specific? $\endgroup$
    – Dawny33
    Jan 7, 2016 at 12:14
  • $\begingroup$ @Dawny33 I mean the matters strictly connected to the machine learning - not programming or libraries. I just don't know how to put it into words. :( $\endgroup$
    – Luke
    Jan 7, 2016 at 12:17
  • $\begingroup$ @Luke The problem is that the question "what are the most basic skills" are based on personal opinion. People might disagree on the answer; there is not a single right answer. This kind of question is probably more suitable on reddit.com $\endgroup$ Jan 7, 2016 at 13:26
  • $\begingroup$ @moose I wanted to ask for the essential knowledge. Feel free to edit my question. $\endgroup$
    – Luke
    Jan 7, 2016 at 13:31
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    $\begingroup$ @Luke I understand what you asked and I've answered to that question. If you think I understood it wrong, you have to clarify. If I got it right, then this is opinion based. (I'm not saying this is a bad question; I only say that it is not suitable for the StackExchange format). $\endgroup$ Jan 7, 2016 at 13:36

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Machine Learning is a really big field. Depending on what exactly you want to do, there might be huge differences.

Having said that, the following skills are helpful:

  • Programming, especially Python / C++
  • Frameworks like TensorFlow, sklearn, Torch, ...
  • Algorithms like neural networks (especially gradient descent), SVM, decision trees, clustering algorithms, Q-Learning, ...
  • Mathematics (e.g. probability theory / statistics, linear algebra, analysis for calculating gradients

Knowing how to program the GPU directly (CUDA) is probably not always necessary, but certainly a big bonus.

In case you're interested what you learn at KIT (Karlsruhe, Germany) in an introductory machine learning course, see my blog post for exam preparation (I'm sorry, it is mostly in German).

Online Courses

There are lots of online material for machine learning. For example an Coursera ML course

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I have already answered similar questions here and here

So, that would help you get an idea of how you need to design your own learning path.

The reason why I said that this question is opinion-based is:

Data Science is a huge domain in itself, and attaining complete knowledge of everything in it, is close to impossible.

So, if I am interested in pursuing the concept of Neural Networks alone, and subsequently Deep Learning; then my learning path would be completely different to someone who wants to learn a different concept like time series.

And so does that of someone who wants to learn some other concept. The concepts might be intertwined, but something which I absolutely require in my learning path might not be necessary to someone else's.

So, those above resources are a rough guide to get started.

In addition to that, here is a list of conferences and podcasts of Data Science, which help you with your learning.

And also keep an eye on the tag here.

Additional reading:

Applying machine learning in a real world example A really good neural networks and deep learning book

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