SuDIS-ZJU/rookies
Rookie's guide
This guide helps aspiring machine learning and deep learning practitioners acquire foundational skills for academic research. It provides a structured curriculum, from mastering Git and Python to understanding core ML/DL concepts, and guides users through selecting, reading, and presenting research papers. The ideal user is a student or researcher new to the field, aiming to build a strong basis in AI for academic pursuits.
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Use this if you are a student or new researcher looking for a structured pathway to learn machine learning, deep learning, and how to effectively engage with academic research papers.
Not ideal if you are an experienced practitioner seeking advanced technical deep-dives into specific AI models or production-level deployment strategies.
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Aug 10, 2024
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