| """ 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 |
Typing vagrant from the command line will display a list of all available commands.
Be sure that you are in the same directory as the Vagrantfile when running these commands!
vagrant init-- Initialize Vagrant with a Vagrantfile and ./.vagrant directory, using no specified base image. Before you can do vagrant up, you'll need to specify a base image in the Vagrantfile.vagrant init <boxpath>-- Initialize Vagrant with a specific box. To find a box, go to the public Vagrant box catalog. When you find one you like, just replace it's name with boxpath. For example,vagrant init ubuntu/trusty64.
vagrant up-- starts vagrant environment (also provisions only on the FIRST vagrant up)
Picking the right architecture = Picking the right battles + Managing trade-offs
- Clarify and agree on the scope of the system
- User cases (description of sequences of events that, taken together, lead to a system doing something useful)
- Who is going to use it?
- How are they going to use it?
| # Role/Profession | |
| Frontend Developer | |
| # Project Description | |
| ## Project Brief | |
| We are building a japanese langauge learning web-app which serves the following purposes: | |
| - A portal to launch study activities |
I have moved this over to the Tech Interview Cheat Sheet Repo and has been expanded and even has code challenges you can run and practice against!
\
| # Use this script to test that your Telegram bot works. | |
| # | |
| # Install the dependency | |
| # | |
| # $ gem install telegram_bot | |
| # | |
| # Run the bot | |
| # | |
| # $ ruby bot.rb | |
| # |
A curated list of AWS resources to prepare for the AWS Certifications
A curated list of awesome AWS resources you need to prepare for the all 5 AWS Certifications. This gist will include: open source repos, blogs & blogposts, ebooks, PDF, whitepapers, video courses, free lecture, slides, sample test and many other resources.
| #!/usr/bin/env bash | |
| set -euo pipefail | |
| bold() { printf "\033[1m%s\033[0m\n" "$*"; } | |
| info() { printf "• %s\n" "$*"; } | |
| warn() { printf "\033[33m! %s\033[0m\n" "$*"; } | |
| err() { printf "\033[31m✗ %s\033[0m\n" "$*" >&2; } | |
| ok() { printf "\033[32m✓ %s\033[0m\n" "$*"; } | |
| require_macos() { |
L1 cache reference ......................... 0.5 ns
Branch mispredict ............................ 5 ns
L2 cache reference ........................... 7 ns
Mutex lock/unlock ........................... 25 ns
Main memory reference ...................... 100 ns
Compress 1K bytes with Zippy ............. 3,000 ns = 3 µs
Send 2K bytes over 1 Gbps network ....... 20,000 ns = 20 µs
SSD random read ........................ 150,000 ns = 150 µs
Read 1 MB sequentially from memory ..... 250,000 ns = 250 µs
