Subhajit Mondal suvo-ee16s073

suvo-ee16s073 / plot_roc.py

Created July 28, 2020 14:04 — forked from code-of-kpp/plot_roc.py

Python pyplot receiver operating characteristic (ROC) curve with colorbar

	import numbers

	import six

	import numpy
	import matplotlib.collections
	from matplotlib import pyplot

	# using example from
	# http://nbviewer.ipython.org/github/dpsanders/matplotlib-examples/blob/master/colorline.ipynb

suvo-ee16s073 / exploratory_data_analysis.py

Created July 13, 2020 15:24 — forked from jiahao87/exploratory_data_analysis.py

	import pandas as pd
	import numpy as np
	import matplotlib
	import matplotlib.pyplot as plt
	import seaborn as sns
	import missingno
	import warnings
	warnings.filterwarnings("ignore")
	%matplotlib inline

suvo-ee16s073 / r_on_ubuntu.sh

Created October 21, 2017 08:49 — forked from pachadotdev/r_on_ubuntu_16_04.sh

Install R on Ubuntu 16.04

	# add CRAN to apt sources
	sudo apt-key adv --keyserver keyserver.ubuntu.com --recv-keys E084DAB9
	printf '\n#CRAN mirror\ndeb https://cran.dcc.uchile.cl/bin/linux/ubuntu xenial/\n' \| sudo tee -a /etc/apt/sources.list

	# install R
	sudo apt-get update
	sudo apt-get install libxml2-dev libssl-dev libcurl4-gnutls-dev gfortran
	sudo apt-get install r-base r-base-dev

	# install common packages

suvo-ee16s073 / nn.py

Created August 27, 2017 15:04 — forked from ottokart/nn.py

3-layer neural network example with dropout in 2nd layer

	# Tiny example of 3-layer nerual network with dropout in 2nd hidden layer
	# Output layer is linear with L2 cost (regression model)
	# Hidden layer activation is tanh

	import numpy as np

	n_epochs = 100
	n_samples = 100
	n_in = 10
	n_hidden = 5