Jaidev Deshpande jaidevd

Hypothesis:

For a given package ABC, if conda installs it without any additional arguments, pip install the same package without any additional arguments, they are not coming from the same source. They will have a slightly different version, patch or minor.

Procedure:

Suppose you have $n$ random variables, $\mathbf{x}_1, \mathbf{x}_2, x_3, \ldots x_n $.

Now, between any two random variables $x_i, x_j$ the covariance is defined as:

$$ \sigma_{\mathbf{x}_i, \mathbf{x}_j} = E[(\mathbf{x}i - \mu{\mathbf{x}_i})(\mathbf{x}j - \mu{\mathbf{x}_j})] $$

(where $\mu_{\mathbf{x}_i}$ is the mean of $\mathbf{x}_i$).

Generative vs discriminative classifiers

Discriminative classifiers:

Discriminative classifiers divide the feature space into regions that separate the data belonging to different classes such that every separate region contains samples belonging to a single class. The decision boundary is determined by constructing and solving equations of the form

$$ \mathbf{y} = \mathbf{w}^T\mathbf{\phi(X)}+b $$

	let g:python3_host_prog="~/conda/bin/python"
	let g:python2_host_prog="~/conda/bin/python"


	call plug#begin('~/.local/share/nvim/plugged')

	" Autocomplete stuff

	if has('nvim')
	Plug 'Shougo/deoplete.nvim', { 'do': ':UpdateRemotePlugins' }

	X <- numeric(length=1000)
	params.a <- sqrt(30) / 4
	params.c <- 0.811

	sqrt.fx <- function(x) {
	f <- (x ^ 4) - 2 * (x ^ 3) + (x ^ 2)
	return(sqrt(30 * f))
	}

	sample <- function() {

	from flask import request, Flask

	app = Flask(__name__)


	@app.route("/", methods=["POST"])
	def index():
	if request.content_type == 'application/pdf':
	with open('request.pdf', 'wb') as fout:
	fout.write(request.data)


	# coding: utf-8

	from keras import layers as L
	from keras import backend as K
	from keras.models import Model
	import tensorflow as tf
	import numpy as np

	_epsilon = tf.convert_to_tensor(K.epsilon(), np.float32)

	[
	{
	"text": "#BREAKINGNEWS MALAYSIA AIRLINES FLIGHT #MH17 CONFIRMED SHOT DOWN OVER #DONETSK OBLAST, SHORTLY BEFORE REACHING RUSSIAN AIR SPACE",
	"labels": [
	{
	"start": 14,
	"end": 31,
	"label": "ORG"
	},
	{