bergie

Some exercises from the Falsy Values workshops.

The good parts:

• HTTP server and client in same script
• Express cookies example
• Express routing example
• Express error handling
• Express middlewares example
• Simple HTTP proxy

CamDavidsonPilon

{
  "lines.linewidth": 2.0,
  "examples.download": true,
  "patch.linewidth": 0.5,
  "legend.fancybox": true,
  "axes.color_cycle": [
    "#30a2da",
    "#fc4f30",
    "#e5ae38",
    "#6d904f",

johnynek

/**
 * To get started:
 * git clone https://github.com/twitter/algebird
 * cd algebird
 * ./sbt algebird-core/console
 */

/**
 * Let's get some data. Here is Alice in Wonderland, line by line
 */

fchollet

'''This script goes along the blog post
"Building powerful image classification models using very little data"
from blog.keras.io.
It uses data that can be downloaded at:
https://www.kaggle.com/c/dogs-vs-cats/data
In our setup, we:
- created a data/ folder
- created train/ and validation/ subfolders inside data/
- created cats/ and dogs/ subfolders inside train/ and validation/
- put the cat pictures index 0-999 in data/train/cats

mcnees

%%-----------------------------------------------------------------------
%% Make your own quadrille, graph, hex, etc paper!
%% Uses the pgf/TikZ package for LaTeX, which should be part of
%% any modern TeX installation.
%% Email: [email protected] 
%% Twitter: @mcnees
%%-----------------------------------------------------------------------

\documentclass[11pt]{article}

danijar

"""Character based language modeling with multi-layer GRUs.

To train the model:

  python3 tf_char_rnn.py --mode training \
      --logdir path/to/logdir --corpus path/to/corpus.txt

To generate text from seed words:

  python3 tf_char_rnn.py --mode sampling \

chriseidhof

//
//  ContentView.swift
//  TestingMoreSwiftUI
//
//  Created by Chris Eidhof on 04.06.19.
//  Copyright © 2019 Chris Eidhof. All rights reserved.
//

import SwiftUI
import Combine

scastiel

all: pdf epub kindle html examples

BOOK_TITLE = A\ React\ Developer’s\ Guide\ to\ Hooks\ -\ Sebastien\ Castiel

dist:
	@mkdir -p dist

pdf: dist/${BOOK_TITLE}.pdf
	@echo '✅  PDF'

mattjj

import torch
import torch.utils.dlpack
import jax
import jax.dlpack

# A generic mechanism for turning a JAX function into a PyTorch function.

def j2t(x_jax):
  x_torch = torch.utils.dlpack.from_dlpack(jax.dlpack.to_dlpack(x_jax))
  return x_torch

karpathy

"""
stable diffusion dreaming
creates hypnotic moving videos by smoothly walking randomly through the sample space

example way to run this script:

$ python stablediffusionwalk.py --prompt "blueberry spaghetti" --name blueberry

to stitch together the images, e.g.:
$ ffmpeg -r 10 -f image2 -s 512x512 -i blueberry/frame%06d.jpg -vcodec libx264 -crf 10 -pix_fmt yuv420p blueberry.mp4