Compsci Study guides, Study notes & Summaries
Looking for the best study guides, study notes and summaries about Compsci? On this page you'll find 49 study documents about Compsci.
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Computer Science 144 A2 summaries
- Summary • 23 pages • 2022
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Excellently summarised notes for Computer Science 144 (Stellenbosch University) - all topics needed for the A2 are covered: 4.1, 4.2, 4.4, and 4.5 
4.1 Analysis of Algorithms 
4.2 Sorting and Searching 
4.4 Symbol Tables 
4.5 Case Study: Small-World Phenomenon 
 
The summaries are neatly digitally summarised, using a combination of the textbook, website-book and slides to help you ace the exam! 
 
Note: these summaries are for the Java language.
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Computer Science 144 A1 summaries
- Summary • 12 pages • 2022
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Summaries for Stellenbosch University Computer Science 144 - covering topics 3.1, 3.2, 3.3. and 3.4. 
 
3.1 Using Data Types 
describes how to use existing reference data types, for text processing image processing. 
3.2 Creating Data Types 
 describes how to create user-defined data types using Java's class mechanism. 
3.3 Designing Data Types 
considers important techniques for designing data types, emphasizing APIs, encapsulation, immutability, and design-by-contract. 
3.4 Case Study: 
N-B...
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Electronic HomeWork 8 University of California, Berkeley COMPSCI 188
- Exam (elaborations) • 14 pages • 2023
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Q1 HMMs, Part I 
20 Points 
Consider the HMM shown below. 
The prior probability , dynamics model , and sensor model 
are as follows: 
We perform a first dynamics update, and fill in the resulting belief distribution . 
We incorporate the evidence . We fill in the evidence-weighted distribution 
, and the (normalized) belief distribution . 
You get to perform the second dynamics update. Fill in the resulting belief distribution . 
.80 
.20 
P(X0 ) P(X ∣ t+1 Xt) P(E ∣ t Xt) 
B (X ) 
′ 
1 
E...
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CS 189 Introduction to Machine Learning HomeWork 3 University of California, Berkeley COMPSCI 189
- Exam (elaborations) • 18 pages • 2023
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CS 189 Introduction to Machine Learning 
Spring 2019 Jonathan Shewchuk HW3 
Due: Wednesday, February 27 at 11:59 pm 
Deliverables: 
1. Submit your predictions for the test sets to Kaggle as early as possible. Include your Kaggle 
scores in your write-up (see below). The Kaggle competition for this assignment can be 
found at: 
• 
• 
2. Submit a PDF of your homework, with an appendix listing all your code, to the Gradescope assignment entitled “HW3 Write-Up”. You may typeset your homework...
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CS 189/289A Introduction to Machine Learning HW2 Solutions University of California, Berkeley COMPSCI 189
- Exam (elaborations) • 19 pages • 2023
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CS 189/289A Introduction to Machine Learning 
Spring 2021 Jonathan Shewchuk HW2: I r Math 
Due Wednesday, February 10 at 11:59 pm 
• Homework 2 is an entirely written assignment; no coding involved. 
• We prefer that you typeset your answers using LATEX or other word processing software. If 
you haven’t yet learned LATEX, one of the crown jewels of computer science, now is a good 
time! Neatly handwritten and scanned solutions will also be accepted. 
• In all of the questions, show your ...
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CEPSCI BMPs PRACTICE EXAM QUESTION WITH COMPLETE SOLUTIONS
- Exam (elaborations) • 8 pages • 2023
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The amount of space on each side of a typical surface water that must serve as a buffer zone? correct answer: 30ft 
 
The amount of space on each side of a sensitive water body that must serve as a buffer zone? correct answer: 45ft 
 
Which option provides the entire buffer width? correct answer: Option A 
 
Which option provides a reduced buffer width? correct answer: Option B 
 
Which option provides no buffer zone? correct answer: Option C 
 
Which BMP cannot be used for velocity control...
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COMPSCI 61C Machine Structure - University of California - CS 189 Introduction to Machine Learning Spring 2021 Homework 6 Q&A
- Exam (elaborations) • 26 pages • 2023
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CS 189 Introduction to Machine Learning Spring 2021 HW6 Due: Wednesday, April 21 at 11:59 pm Deliverables: Neural network libraries such as Tensorflow and PyTorch have made training complicated ne ural network architectures very easy. However, we want to emphasize that neural networks begin with fundamentally simple models that are just a few steps removed from basic logistic regression. In this assignment, you will build two fundamental types of neural network models, all in plain numpy: a feed...
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COMPSCI 161 Computer Security project 1-writeup - University of California, Berkeley COMPSCI 161
- Exam (elaborations) • 9 pages • 2023
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Question 1 Behind the Scenes 
The vulnerability occurs in deja_vu function, where a malicious attacker can input more than 8 
characters, which will cause buffer overflow of buffer “door.” 
void deja_vu() 
{ 
 char door[8]; 
 gets(door); // where buffer overflow occurs 
} 
The info frame in the deja_vu function gives me this result: 
(gdb) i f 
Stack level 0, frame at 0xbffff800: 
 ... 
 Saved registers: 
 ebp at 0xbffff7f8, eip at 0xbffff7fc 
(gdb) p &door 
$1 = (char (*)[8]) 0xbffff7e8 
He...
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COMPSCI 3SD3 - COMP SCI 3SD3 Virtual Take Home Examination
- Exam (elaborations) • 5 pages • 2023
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COMP SCI 3SD3 Virtual Take Home Examination McMaster University Final Examination Total: 132 pts ● THIS EXAMINATION PAPER HAS 5 PAGES AND 9 QUESTIONS. ● The exam starts at 12:30 pm and ends at 3:30 pm, i.e. 180 (3hr) minutes (for students without extra time permissions). This includes the exam time (150 minutes) plus extra time for technology (30 minutes). ● Please submit the solutions via Avenue using the same procedure as for the assignments. ● Also, just in case, send the solutions vi...
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