Answers.Body: <p>I think it depends on what you want to do with your knowledge and what background you are coming from. Also are you having any specific problem in mind you want to solve? because that could give a direction.</p>
  <p>If you want to come up with new ways of using algorithms for problems, you will probably need to understand the math behind them. so it that is the case you will need to read the first kind of book you mentioned, I think.</p>
  <p>if you are just looking to use machine learning for problems that look like ones that have been solved before, you may get away with not knowing the exact math behind it all, as I have been so far (software engineering background).</p>
  <p>I started with a book called &quot;Introduction to machine learning with Python&quot; by Andreas C. Müller and Sarah Guido. It is a book that falls under the second category and gives nice implementation examples and tips &amp; tricks. It doesn't cover deep learning though, but is a great introduction.</p>
  
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Answers.CreationDate: 2023-03-25T11:44:57.143Z
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Body: <p>Thing is, I got a lot of resources to learn from and I have no idea which ones will be the most effective, and where to start. I've come across 2 kinds of books, the ones which talk about the mathematics behind ML and the others which show the technical side of it with the help of various toolkits. I don't know which to do before which, and I feel like I'm running in circles.</p>
  <p>Any suggestions on how I can make my progress effective? Any specific approach with which I need to learn?</p>
  <p>P.S. I tend to learn better from books and notes as compared to video lectures, so it would
  be really helpful if suggested solutions are along that line.</p>
  
Tags: <neural-networks><machine-learning><deep-learning><generative-adversarial-networks>
Title: I'd like some suggestions on how to effectively master machine learning. I'm new to this and I'm kinda lost
UserDisplayName: Meerkat
ThreadText: # I'd like some suggestions on how to effectively master machine learning. I'm new to this and I'm kinda lost
  
  (Asked by: username_0 on 2023-03-25)
  
  Thing is, I got a lot of resources to learn from and I have no idea which ones will be the most effective, and where to start. I've come across 2 kinds of books, the ones which talk about the mathematics behind ML and the others which show the technical side of it with the help of various toolkits. I don't know which to do before which, and I feel like I'm running in circles.
  
  Any suggestions on how I can make my progress effective? Any specific approach with which I need to learn?
  
  P.S. I tend to learn better from books and notes as compared to video lectures, so it would
  be really helpful if suggested solutions are along that line.
  
  **Tags:** neural-networks, machine-learning, deep-learning, generative-adversarial-networks
  
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  ## 1 answers
  
  ### Answer by username_1 on 2023-03-25. Score: 1
  
  I think it depends on what you want to do with your knowledge and what background you are coming from. Also are you having any specific problem in mind you want to solve? because that could give a direction.
  
  If you want to come up with new ways of using algorithms for problems, you will probably need to understand the math behind them. so it that is the case you will need to read the first kind of book you mentioned, I think.
  
  if you are just looking to use machine learning for problems that look like ones that have been solved before, you may get away with not knowing the exact math behind it all, as I have been so far (software engineering background).
  
  I started with a book called "Introduction to machine learning with Python" by Andreas C. Müller and Sarah Guido. It is a book that falls under the second category and gives nice implementation examples and tips & tricks. It doesn't cover deep learning though, but is a great introduction.
  
  
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