Abhishek Anil Deshmukh Abhishek-Deshmukh

## tmux_local_install.sh
#!/bin/bash

TMUX_VERSION="2.1"
LIBEVENT_VERSION="2.0.20"
NCURSES_VERSION="6.0"

# Script for installing tmux on systems where you don't have root access.
# tmux will be installed in $HOME/local/bin.
# It's assumed that wget and a C/C++ compiler are installed.

## day_length.py
from sklearn.cluster import KMeans
from PIL import Image
import numpy as np
import matplotlib.pyplot as plt


time_diff_mins = 1
shape = [3468, 4624]
cutoff = 95
box = (0, shape[1]*0.1, shape[0]*0.5, shape[1]*0.4)

## clustering_submission.md

      
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                Abhishek-Deshmukh
                / clustering_submission.md
            
            
              Created
              September 3, 2021 08:11
            
              
                CS640 assignment (Clustering)
              
          
    If the data is less (less than like million points). Then just do a scatter plot and visually count the number of clusters. This is also a good place to decide wether to use KMeans or DBSCAN. If the data is in circle-ish clusters then k-means should work fine, it not DBSCAN would be better.
I am not sure what to do when data is very large. I guess something specific about where the data came from and what we need can be used.

  
## id_rsa.pub
ssh-rsa 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 mercury@diana
	#!/bin/bash

	TMUX_VERSION="2.1"
	LIBEVENT_VERSION="2.0.20"
	NCURSES_VERSION="6.0"

	# Script for installing tmux on systems where you don't have root access.
	# tmux will be installed in $HOME/local/bin.
	# It's assumed that wget and a C/C++ compiler are installed.
	from sklearn.cluster import KMeans
	from PIL import Image
	import numpy as np
	import matplotlib.pyplot as plt


	time_diff_mins = 1
	shape = [3468, 4624]
	cutoff = 95
	box = (0, shape[1]0.1, shape[0]0.5, shape[1]*0.4)