The comprehensive exam looms! As a PhD student wading through the vast ocean of AI, the pressure is on. To ensure I’m shipshape for the June 2025 exam (tentatively),
I'm publicly documenting my daily learning journey.
My research focuses on the intersection of social computing and low-resource languages, but the comprehensive exam demands a broader understanding of AI fundamentals. I believe learning in public is the ultimate accountability partner! Plus, I'm excited to create a resource I can look back on to see how far I've come."
Today marks the start of a rigorous review of syllabus i would like to cover
1.Computational Mathematics for Data Science. (Linear Algebra, Optimization, Calculus, Probability and Statistics)
2.Machine Learning
3.Deep Learning
4.Text Mining and Analytics
My initial deep dive will be into Linear Algebra, specifically focusing on vectors, matrices, and their fundamental operations, which form the bedrock for so much of what we do in machine learning.
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