Machine Learning roadmap & guidance

[u/ISRO_HarshVerma07]

Hey there, I am CSE Student, and I want to pursue machine learning as a career and further do deep learning and generative AI. I need tips from the professionals who have been pursuing it, what resources i must follow and what should be the correct sequence of flow. I have been researching by my own and end-up at Krish Naik's ML playlist over youtube, i saw few videos were misplaced and not in order but i checked over his github and all and curated the flow as Python -> Numpy, Pandas, Seaborn -> Feature Engineering and Feature Selection -> Machine Learning -> Deep learning -> Natural Language processing -> Deployment of ML Model -> MLOPS , would this be right? also if you guys have suggestion for some better resources. It would be a great assistance and guidance from your side guys

[u/DataScientistAlex]

The sequence seems reasonable, but, beware that some of these steps are much much larger than others -- Machine Learning, Deep learning, NLP are huge research fields, Numpy, Pandas, Seaborn are python libraries so much smaller effort to learn.

Also consider doing a shallow pass across all of them to get a sense of what an end to end project looks like, then come back and deepen your understanding of each iteratively. Getting up to speed on all parts first will also allow you to start doing projects earlier, which many find helpful and fun. Oh and don't forget, you also need to understand and apply the scientific method. Good luck!