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@kevin-keraudren
kevin-keraudren / volume_rendering.py
Last active December 8, 2023 17:10
Volume rendering in Python using VTK-SimpleITK
#!/usr/bin/python
import SimpleITK as sitk
import vtk
import numpy as np
import sys
from vtk.util.vtkConstants import *
filename = sys.argv[1]
@tsiege
tsiege / The Technical Interview Cheat Sheet.md
Last active June 12, 2024 03:08
This is my technical interview cheat sheet. Feel free to fork it or do whatever you want with it. PLEASE let me know if there are any errors or if anything crucial is missing. I will add more links soon.

ANNOUNCEMENT

I have moved this over to the Tech Interview Cheat Sheet Repo and has been expanded and even has code challenges you can run and practice against!






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@KWMalik
KWMalik / interviewitems.MD
Created September 16, 2012 22:04 — forked from amaxwell01/interviewitems.MD
My answers to over 100 Google interview questions

##Google Interview Questions: Product Marketing Manager

  • Why do you want to join Google? -- Because I want to create tools for others to learn, for free. I didn't have a lot of money when growing up so I didn't get access to the same books, computers and resources that others had which caused money, I want to help ensure that others can learn on the same playing field regardless of their families wealth status or location.
  • What do you know about Google’s product and technology? -- A lot actually, I am a beta tester for numerous products, I use most of the Google tools such as: Search, Gmaill, Drive, Reader, Calendar, G+, YouTube, Web Master Tools, Keyword tools, Analytics etc.
  • If you are Product Manager for Google’s Adwords, how do you plan to market this?
  • What would you say during an AdWords or AdSense product seminar?
  • Who are Google’s competitors, and how does Google compete with them? -- Google competes on numerous fields: --- Search: Baidu, Bing, Duck Duck Go
@rreas
rreas / spkmeans.m
Created June 2, 2012 17:55
Spherical K-Means Clustering
function [U,V,idx] = spkmeans(X,k,tol,imax)
[d,n] = size(X);
U = zeros(d,k);
V = zeros(k,n);
% random clusters and normalize to unit sphere.
for j = 1:n
V(randi(k),j) = 1;