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  • #背景提升
  • #eecs

CS‌‌‍‍‌‍‍‌‍‍‌‍‌‍‍‍‍‌‌‌‍‌‍‍‌‌‍‌‌‌‍‌课程选择

whoisit
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楼主本科信息管理,学了点编程的皮毛和一些数学课比如,calculus,probability,linear algebra, intro to statistics,linear models目前本科最后一学期在学convex optimization, multiviate statistics然后master想读个深点的CS课程,准备未来从事Machine Learning方向,请教各路高手帮我看看一下课程哪些是对Machine Learning比较重要,或者就算是做码农也很重要的课,先谢谢大家先.

1.Microprocessors and Interfacing(ISA, interrupts and I/O interfacing, serial communication, timers etc)2.Digital Circuits and System3.Distributed Systems4.Computer Architecture(pipelined RISC machines,memory subsystem, I/O, and system level interconnect)5.Theory of Computation(Turing Machines, computability, Complexity: run time, space, too theoretical?)6.Design & Analysis of Algorithms7.Advanced and Parallel Algorithms (Spatial, semi-structured and multi-dimensional data storage and manipulation techniques, non Von-Neumann techniques, advanced and parallel algorithmic technique)8.Parameterized and Exact Computation( NP-hard problems, branching, colour coding, iterative compression, and kernelization)9.Artificial Intelligence (感觉这课太理论,没什么用?)10.Knowledge Representation and Reasoning(AI Logics, Probablilistic Reasoning, Constraints)

补充内容 (2016-5-30 22:30):

JAVA,Data Structure已经学过,是C++,然后binary tree, hash table什么的,因为比较基本就没列出来了.然后一些重要的数学课比如convex optimisation, multiviate statistics, stochastic process因为肯定要学也,没....
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