This is inspired by A half-hour to learn Rust and Zig in 30 minutes.
Your first Go program as a classical "Hello World" is pretty simple:
First we create a workspace for our project:
This is inspired by A half-hour to learn Rust and Zig in 30 minutes.
Your first Go program as a classical "Hello World" is pretty simple:
First we create a workspace for our project:
### JHW 2018 | |
import numpy as np | |
import umap | |
# This code from the excellent module at: | |
# https://stackoverflow.com/questions/4643647/fast-prime-factorization-module | |
import random |
WAYLAND_PROTOCOLS=/usr/share/wayland-protocols | |
# wayland-scanner is a tool which generates C headers and rigging for Wayland | |
# protocols, which are specified in XML. wlroots requires you to rig these up | |
# to your build system yourself and provide them in the include path. | |
xdg-shell-protocol.h: | |
wayland-scanner server-header \ | |
$(WAYLAND_PROTOCOLS)/stable/xdg-shell/xdg-shell.xml $@ | |
xdg-shell-protocol.c: xdg-shell-protocol.h |
--- | |
Description: AWS AppSync Notes API | |
Parameters: | |
APIName: | |
Type: String | |
Description: Name of the API - used to generate unique names for resources | |
MinLength: 3 | |
MaxLength: 20 | |
AllowedPattern: '^[a-zA-Z][a-zA-Z0-9_]*$' |
""" | |
A bare bones examples of optimizing a black-box function (f) using | |
Natural Evolution Strategies (NES), where the parameter distribution is a | |
gaussian of fixed standard deviation. | |
""" | |
import numpy as np | |
np.random.seed(0) | |
# the function we want to optimize |
""" 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 |
{0: 'tench, Tinca tinca', | |
1: 'goldfish, Carassius auratus', | |
2: 'great white shark, white shark, man-eater, man-eating shark, Carcharodon carcharias', | |
3: 'tiger shark, Galeocerdo cuvieri', | |
4: 'hammerhead, hammerhead shark', | |
5: 'electric ray, crampfish, numbfish, torpedo', | |
6: 'stingray', | |
7: 'cock', | |
8: 'hen', | |
9: 'ostrich, Struthio camelus', |
#!/usr/bin/env bash | |
# | |
# gh-dl-release! It works! | |
# | |
# This script downloads an asset from latest or specific Github release of a | |
# private repo. Feel free to extract more of the variables into command line | |
# parameters. | |
# | |
# PREREQUISITES | |
# |