Artem Golubin rushter

Achieving warp speed with Rust

FWIW: I (@rondy) am not the creator of the content shared here, which is an excerpt from Edmond Lau's book. I simply copied and pasted it from another location and saved it as a personal note, before it gained popularity on news.ycombinator.com. Unfortunately, I cannot recall the exact origin of the original source, nor was I able to find the author's name, so I am can't provide the appropriate credits.

Effective Engineer - Notes

By Edmond Lau
Highly Recommended 👍
http://www.theeffectiveengineer.com/

What's an Effective Engineer?

A Few Useful Things to Know about Machine Learning

The paper presents some key lessons and "folk wisdom" that machine learning researchers and practitioners have learnt from experience and which are hard to find in textbooks.

1. Learning = Representation + Evaluation + Optimization

All machine learning algorithms have three components:

Representation for a learner is the set if classifiers/functions that can be possibly learnt. This set is called hypothesis space. If a function is not in hypothesis space, it can not be learnt.
Evaluation function tells how good the machine learning model is.
Optimisation is the method to search for the most optimal learning model.

Update HISTORY.rst
Commit the changes:

git add HISTORY.rst
git commit -m "Changelog for upcoming release 0.1.1."

Update version number (can also be patch or major)

bumpversion minor

	from itertools import chain, repeat
	import sys
	import types

	# byte offsets for structures
	if hasattr(sys, 'gettotalrefcount'):
	# under PyDEBUG builds
	_f_localsplus_offset = 392
	_ob_item_offset = 40
	else:

	"""
	bitmap utils and much of the ctc code modified
	From Shawn Tan, Rakesh and Mohammad Pezeshki
	"""
	# Author: Kyle Kastner
	# License: BSD 3-clause
	from theano import tensor
	from scipy import linalg
	import theano
	import numpy as np

	Write a program that does what it’s supposed to do
	Write idiomatic code
	Debug a program that you wrote
	Debug a program someone else wrote
	Debug the interaction between a system you wrote and one you didn’t
	File a good bug report
	Modify a program you didn’t write
	Test a program you wrote
	Test a program you didn’t write
	Learn a new programming language

	"""
	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)

	# Byte-compiled / optimized / DLL files
	__pycache__/
	*.py[cod]

	# C extensions
	*.so

	# Distribution / packaging
	.Python
	env/

	# use ImageMagick convert
	# the order is important. the density argument applies to input.pdf and resize and rotate to output.pdf
	convert -density 90 input.pdf -rotate 0.5 -attenuate 0.2 +noise Multiplicative -colorspace Gray output.pdf