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Algorithm Efficiency. In this video, MIT professor of Computer Science and Engineering Charles Leiserson explains the importance of speed and space efficiency in programming. He guides students through different methods of computing the Fibonacci sequence and discusses the differences in efficiency of each version. Next, students are presented with several modern programming scenarios. Opportunities for pausing the video are provided so that students may independently consider and appreciate the different factors of efficiency in each example. (from ocw.mit.edu)

Algorithm Efficiency


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01. Algorithm Efficiency
02. An Ode to ODEs
03. Basic Programming Techniques
04. Buffers
05. Chirality
06. Conditional Probability
07. Conservation of Mass
08. Contaminant Fate Modeling
09. Diffusion and Fick's Law
10. Dimensional Analysis
11. Divergence
12. Electric Potential
13. Entropy
14. Enzyme Kinetics
15. Equilibrium vs. Steady State
16. Free Body Diagrams
17. Feedback Loops
18. Flux and Gauss' Law
19. Gear Trains
20. Genetics and Statistics
21. Gradient
22. Gravity
23. Kinetic Theory
24. Kinetics and Equilibrium
25. Latent Heat
26. Linear Approximations
27. Maxwell's Equations
28. Models of Light
29. Moments of Distributions
30. Motion
31. Newton's Laws
32. Polyelectrolyte Multilayers
33. Problem Solving Process
34. Radio Receivers
35. Rigid Body Kinematics
36. Rotating Frames of Reference
37. Stability Analysis
38. Strategic Communication
39. The Art of Approximation
40. The Scientific Process: An Example from Biology
41. Torque
42. Unit Analysis
43. Vector Fields
44. Vectors
45. VSEPR (Valence Shell Electron Pair Repulsion)
46. What is Temperature?