Where'd Tony's pre-Europe post go?
The line of thought "Sprinkles -> donut -> torus -> topology -> mathematics" sounds like what my head says to me whenever I walk into a bakery.. or well, whenever I see a donut, in general.
I've had my textbooks for a few weeks now. Here's the pre-reviews of the math books:
A Mathematical Introduction to Fluid Mechanics, Chorin (for Math 705 - grad-level fluids)
A very short, cool-looking book that's pretty easily readible. The only real drawback is that it's not the most current version (and with that comes the annoying older vector calc notation). The physics and derivations are somewhat sketchy in the little that I've read, but that seems to be normal for the intro fluid dynamics genre. I don't know how much I like the order in which the concepts are introduced. One reviewer on Amazon claims typos exist, but I haven't encountered anything glaring yet.
Elementary Fluid Dynamics, Acheson (also for Math 705)
This is my favorite textbook in my library. I've had this book since last school year; I've worked the first two chapters, and have skimmed a lot of the rest. The derivations are solid, there are a lot of references to experiments (don't be too surprised if you find me running little clay airfoil shapes through dyed water in the bathtub), the diagrams are clear, and the order is very good for understanding stuff. Definitely plays strongly on both my math and physics sides.
Molecular Modelling, Leach (Math 801 - grad-level math methods of computational biochem)
I haven't had much chance to hang out with this book yet, but anytime something puts equations and molecules together, I get all riled up. It looks like this book will help me to push my computational biochem knowledge outside of what I've learned from protein docking and folding literature.
Scientific Computing, Heath (also for Math 801)
I haven't had a good look through this either. On the first run through, it looked like a lot of standard applied numerical analysis, with some cooler advanced topics not covered by the more immature numerical analysis books I own.
Statistical Inference, Casella (Econ 709 - grad-level stats & econometrics, semester 1 of 2)
The first semester of this sequence may as well be called math, as it's just stats and probability. This book looks like it will be pretty useful; starts with probability theory (all covered in 431), and builds up the stats and inference concepts from there. Not even five good books will save me from certain doom, though; this class is going to kick my ass.
The trip to GenCon commences at 11:00a later today; I'll talk to you guys when I get back.
I've had my textbooks for a few weeks now. Here's the pre-reviews of the math books:
A Mathematical Introduction to Fluid Mechanics, Chorin (for Math 705 - grad-level fluids)
A very short, cool-looking book that's pretty easily readible. The only real drawback is that it's not the most current version (and with that comes the annoying older vector calc notation). The physics and derivations are somewhat sketchy in the little that I've read, but that seems to be normal for the intro fluid dynamics genre. I don't know how much I like the order in which the concepts are introduced. One reviewer on Amazon claims typos exist, but I haven't encountered anything glaring yet.
Elementary Fluid Dynamics, Acheson (also for Math 705)
This is my favorite textbook in my library. I've had this book since last school year; I've worked the first two chapters, and have skimmed a lot of the rest. The derivations are solid, there are a lot of references to experiments (don't be too surprised if you find me running little clay airfoil shapes through dyed water in the bathtub), the diagrams are clear, and the order is very good for understanding stuff. Definitely plays strongly on both my math and physics sides.
Molecular Modelling, Leach (Math 801 - grad-level math methods of computational biochem)
I haven't had much chance to hang out with this book yet, but anytime something puts equations and molecules together, I get all riled up. It looks like this book will help me to push my computational biochem knowledge outside of what I've learned from protein docking and folding literature.
Scientific Computing, Heath (also for Math 801)
I haven't had a good look through this either. On the first run through, it looked like a lot of standard applied numerical analysis, with some cooler advanced topics not covered by the more immature numerical analysis books I own.
Statistical Inference, Casella (Econ 709 - grad-level stats & econometrics, semester 1 of 2)
The first semester of this sequence may as well be called math, as it's just stats and probability. This book looks like it will be pretty useful; starts with probability theory (all covered in 431), and builds up the stats and inference concepts from there. Not even five good books will save me from certain doom, though; this class is going to kick my ass.
The trip to GenCon commences at 11:00a later today; I'll talk to you guys when I get back.
posted by erick at 10:48 PM
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