Alastair Paragas alastairparagas

Alastair's Personal Finance Resources

Let your money do some work: https://medium.com/fortune-for-future/let-your-money-do-some-work-17a72a12980f - assembling the groundwork for investments, retirements and tax-advantaged accounts [30 minute read]
Grownup Escapades - Handling Finances: https://aparagas.medium.com/grownup-escapades-handling-finances-d21ddeaa6c24 [20 minute read]

Bogleheads: https://www.bogleheads.org - full of adherents of John Bogle, founder of Vanguard (now one of the largest mutual fund companies in America, with $7.2 trillion assets under management).
- The main tenets of Bogleheads are:
Focus on costs (expense ratios) when investing on mutual funds. Index investing.

	import numpy as np
	import matplotlib.pyplot as plt
	np.seterr(all="ignore")
	import matplotlib.ticker as ticker
	import numpy_financial

	# Treasury, TIPS and I-bonds - these are all bonds, which allows you to lend
	# a $ amount (principal) to the US government. The US government promises to pay
	# you back in time (years).

	# Auto loan cost comparison
	# When debt can be obtained at low interest rates, using cheap debt
	# and investing the cash that would have been used otherwise) can be
	# more tactical, than just deploying cash where cheap debt can suffice.
	import math

	auto_rate_table = [
	0.0219, 0.0429, # Old vs New Rates, Credit Union 1
	0.0289, 0.0319, # Old vs New Rates, Credit Uni$on 2
	0.0449, 0.0524 # Old vs New Rates, National Bank

	Hey! I am using these online resources:

	https://textbooks.math.gatech.edu/ila/ (Lin Alg),
	https://github.com/cgcentral/awesome-linear-algebra (Lin Alg),
	https://www.math.brown.edu/streil/papers/LADW/LADW_2017-09-04.pdf (Lin Alg),

	https://ocw.mit.edu/courses/mathematics/18-02-multivariable-calculus-fall-2007/video-lectures/ (Multivariable Calc),
	https://tutorial.math.lamar.edu/classes/calciii/calciii.aspx (Multivariable Calc),
	https://www.amazon.com/Calculus-Intuitive-Physical-Approach-Mathematics/dp/0486404536?asin=0486404536&revisionId=&format=4&depth=1
	(latter parts of this book for Multivariable Calc)

	[ 4191.895970] Anomaly Detection (Kernel Hook) - Alastair Paragas
	[ 4191.904591] Syscall table address: 00000000c0647077
	[ 4191.904595] sizeof(unsigned long long *): 8
	[ 4191.904595] sizeof(sys_call_table) : 8
	[ 4203.278393] Execve: /usr/bin/sudo, ./target
	[ 4203.289339] Execve: ./target, rJgVdaRJqFc7fiCE7Q6M
	[ 4216.942554] Execve: /usr/bin/sudo, ./target
	[ 4216.952836] Execve: ./target, DR8wEkyRevYXlZMWvmvg
	[ 4225.844816] Execve: /usr/bin/sudo, ./target
	[ 4225.853263] Execve: ./target, ZeFeXLPHJNzfEwFBrhiW

	[ 3671.330080] Anomaly Detection (Kernel Hook) - Alastair Paragas
	[ 3671.334482] Syscall table address: 000000009c24251c
	[ 3671.334484] sizeof(unsigned long long *): 8
	[ 3671.334484] sizeof(sys_call_table) : 8
	[ 3681.637345] Execve: /usr/bin/sudo, ./target
	[ 3681.647421] Execve: ./target, rJgVdaRJqFc7fiCE7Q6M
	[ 3689.614274] Execve: /usr/bin/sudo, ./target
	[ 3689.624160] Execve: ./target, DR8wEkyRevYXlZMWvmvg
	[ 3697.999832] Execve: /usr/bin/sudo, ./target
	[ 3698.007720] Execve: ./target, ZeFeXLPHJNzfEwFBrhiW

	import numpy as np


	class DTLearner(object):

	leaf_size = None
	verbose = None
	tree = None

	def __init__(self, leaf_size=None, verbose=False):

	import numpy as np
	import base64
	from typing import List

	def encode(ord_key: List[int], some_str: str):
	s_len = len(some_str)
	ord_key_remapped = np.resize(ord_key, s_len)
	encoded_str = np.array(list(map(ord, some_str))) + ord_key_remapped % 256
	return base64.urlsafe_b64encode(encoded_str.tostring())