Alex Ilchenko ijkilchenko

## pg-pong.py
""" Trains an agent with (stochastic) Policy Gradients on Pong. Uses OpenAI Gym. """
import numpy as np
import cPickle as pickle
import gym

# hyperparameters
H = 200 # number of hidden layer neurons
batch_size = 10 # every how many episodes to do a param update?
learning_rate = 1e-4
gamma = 0.99 # discount factor for reward

## amznymous.md

      
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              April 23, 2024 11:14
            
              
                An Amazon Programmer's Perspective (http://pastebin.com/BjD84BQ3)
              
          
    Originally posted at http://pastebin.com/BjD84BQ3
Trigger warning: mention of suicidal ideation
tl;dr: I burned out as a developer at Amazon at the end of my second year. I’ve since found a healthy and sustainable work-life balance and enjoy work again. I write this to A) raise awareness, especially for new-hires and their families, and B) help give hope and advice to people going through the same at Amazon or other companies.
Hello, world

There’s been no shortage of anecdotes, opinions, and rebuttals regarding Amazon’s corporate culture as of late. I write this not to capitalize on the latest news-feed fad, but to share what I had already written and promptly deleted. I didn’t think anyone would want to hear my story, but it’s apparent people are going through a similar experience and don’t have a voice.
I’m a Software Development Engineer II at Amazon; SDE II basically means a software developer with at least 2–3 years of industry experience. I started at Amazon as an SDE I.

  
## min-char-rnn.py
"""
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)
	""" Trains an agent with (stochastic) Policy Gradients on Pong. Uses OpenAI Gym. """
	import numpy as np
	import cPickle as pickle
	import gym

	# hyperparameters
	H = 200 # number of hidden layer neurons
	batch_size = 10 # every how many episodes to do a param update?
	learning_rate = 1e-4
	gamma = 0.99 # discount factor for reward
	"""
	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)