Hi, my name is Patrik. I stumbled upon this community from following Andrew Ng’s course on Machine Learning Specialization on Coursera. Currently, I’m on the Advanced Learning Algorithms course and it’s been really interesting so far.
Just wondering what should my next steps be after following the Coursera courses, should I undertake more content or shift more of my focus to developing machine learning projects? Which one would best help my ability to understand Machine Learning to the extent that it’s being used in the modern world?
P.S I am a computer science student but my university doesn’t offer advanced machine learning courses to the depth I would like to learn, they are more focused on data mining and selecting which models of machine learning to apply to data mining problems. What other resources would you recommend to deep dive into machine learning?
Many thanks, looking forward to being a part of the community
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Hi Patrik! It’s great to hear that you’re enjoying Andrew Ng’s course. You’re on the right track by thinking about what comes next.
You should focus on applying what you’ve learned by doing projects. For instance, after completing a concept like linear regression, take the time to create a project around it, such as predicting housing prices or stock market trends. This hands-on approach solidifies your understanding and helps build practical skills.
I also recommend continuing with the Deep Learning Specialization after completing the Machine Learning Specialization. It provides a strong foundation and is a crucial step toward understanding more advanced fields like NLP and CV.
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I see, I had initially thought that the project labs were enough to understand but I would definitely gain a deeper understanding by doing a small project for each model I learn. I will definitely be doing this next then.
Thanks so much for the input! I am also looking forward to the Deep Learning Specialisation course too.
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