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Kelvinson / robotics.md
Created May 1, 2019 14:10 — forked from UsmanMaqbool/robotics.md
Robotics Installation

Installation Guide

OPENCV

OpenCV 2.4.13

To install

cd ~
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Kelvinson / System Design.md
Created January 23, 2019 00:11 — forked from vasanthk/System Design.md
System Design Cheatsheet

System Design Cheatsheet

Picking the right architecture = Picking the right battles + Managing trade-offs

Basic Steps

  1. Clarify and agree on the scope of the system
  • User cases (description of sequences of events that, taken together, lead to a system doing something useful)
    • Who is going to use it?
    • How are they going to use it?
import argparse
import torch
import torch.nn as nn
from torch.autograd import Variable
from torch.utils.data import DataLoader
import torchvision
import torchvision.transforms as T
from torchvision.datasets import ImageFolder
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Kelvinson / tmux-cheatsheet.markdown
Created August 31, 2018 01:20 — forked from MohamedAlaa/tmux-cheatsheet.markdown
tmux shortcuts & cheatsheet

tmux shortcuts & cheatsheet

start new:

tmux

start new with session name:

tmux new -s myname
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Kelvinson / Install NVIDIA Driver and CUDA.md
Created April 17, 2018 22:25 — forked from wangruohui/Install NVIDIA Driver and CUDA.md
Install NVIDIA Driver and CUDA on Ubuntu / CentOS / Fedora Linux OS
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Kelvinson / min-char-rnn.py
Created March 17, 2018 22:07 — forked from karpathy/min-char-rnn.py
Minimal character-level language model with a Vanilla Recurrent Neural Network, in Python/numpy
"""
Minimal character-level Vanilla RNN model. Written by Andrej Karpathy (@karpathy)
BSD License
"""
import numpy as np
# data I/O
data = open('input.txt', 'r').read() # should be simple plain text file
chars = list(set(data))
data_size, vocab_size = len(data), len(chars)
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Kelvinson / graph_search.cpp
Created January 10, 2018 07:58 — forked from douglas-vaz/graph_search.cpp
Breadth First Search and Depth First Search in C++
#include <iostream>
#include <string>
#include <vector>
#include <queue>
#include <stack>
#include <algorithm>
using namespace std;
class Node{