Making notes from the course

I am currently learning Supervised Machine Learning: Regression and Classification by DeepLearning on Coursera. My aim is to be a pro in it. Should I maintain a separated notebook to note down technical terms and definitions along with algorithms being discussed? How did you all learn AI/ ML? Share your learning methods too.

With regards
Ak

I make my own notes from the lectures…

Hello @Ayushi_Kandpal ,

  • While learning, I take notes.
  • Revision
  • I used to have a glossary/dictionary of technical terms, my own written down.
  • After that , I explore and learn more about it- research more,
  • Then I go for application and implementation of my knowledge gained, to solve real world problems by building projects.
  • I do get stuck with errors as well, initially I used to sit for hours to days, to fix them myself - debugging.

Theory gives you the base and understanding. After that, I believe practical implementations are crucial to get a better grasp of AI/ML.
Mini projects are good to start with.

With reagards,
Nilosree Sengupta

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Totally agree with you on this .

Thanks @nilosreesengupta Can you list some mini projects I can work on ?

Hello @Ayushi_Kandpal ,

By mini, I mean relatively smaller, simpler code and begginer level.

examples:
For Regression : House/Car Price Estimation
For Classification : Iris Flower Species Classification

With reagards,
Nilosree Sengupta

I use a notes template called Cornell Notes. It really helps me in my daily learning

Yes it’s really efficient. I’ll do that too! Thanks for sharing

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You welcome, my friend.

Can anyone share his/her notes. Thank You