> what are the best resources for a CS student/decent programmer to get into the field of ML and DL on their own
It would be helpful to know more about your background and motivations.
Are you currently enroled in a Bachelor of Science (B.Sc.) full time stdy program at a university, and your goal is to be a research scientist (either staff scientist or professor or research fellow) in the area of machine learning?
If this is true, does your university offer a Master's program in Machine Learning, or are your grades such that you could apply for such a program elsewhere after completing your first degree? You could then enter a Ph.D.
programm in machine learning itself, or in computer science with an applied ML topic such as ML for NLP (Natural Language Processing) or ML for IR (Information Retrieval = search engines) or ML for robotics etc. The choice of doctoral advisor and Ph.D. topic will steer you towards a particular direction, in which you can then find employment to conduct research under the direction of others, and potentially, become a research group leader yourself after gaining the necessary experience.
Time: M.Sc.: 1-2 years; Ph.D.: 3-8 years; postdoctoral/pre-tenure time: e.g. 2-k years, depending on ability and luck/timing). It's a lot of fun to get paid for doing science, so I chose that path (but with multiple deviations due to startups and industry jobs along the way).
The more people know, the easier it is to recommend you useful materials.
It would be helpful to know more about your background and motivations.
Are you currently enroled in a Bachelor of Science (B.Sc.) full time stdy program at a university, and your goal is to be a research scientist (either staff scientist or professor or research fellow) in the area of machine learning?
If this is true, does your university offer a Master's program in Machine Learning, or are your grades such that you could apply for such a program elsewhere after completing your first degree? You could then enter a Ph.D. programm in machine learning itself, or in computer science with an applied ML topic such as ML for NLP (Natural Language Processing) or ML for IR (Information Retrieval = search engines) or ML for robotics etc. The choice of doctoral advisor and Ph.D. topic will steer you towards a particular direction, in which you can then find employment to conduct research under the direction of others, and potentially, become a research group leader yourself after gaining the necessary experience. Time: M.Sc.: 1-2 years; Ph.D.: 3-8 years; postdoctoral/pre-tenure time: e.g. 2-k years, depending on ability and luck/timing). It's a lot of fun to get paid for doing science, so I chose that path (but with multiple deviations due to startups and industry jobs along the way).
The more people know, the easier it is to recommend you useful materials.