khoparzi

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mschnetzer

library(tidyverse)
library(survey)
library(msthemes)
library(gganimate)

# Load HFCS and Non-core data
load("hfcs2014AT.rda")
load("Noncore AT/non-core-at.rda")

# Calculate estimated decile with mean from multiple imputation data

threepointone

https://twitter.com/snookca/status/1073299331262889984?s=21

‪“‬In what way is JS any more maintainable than CSS? How does writing CSS in JS make it any more maintainable?”

‪Happy to chat about this. There’s an obvious disclaimer that there’s a cost to css-in-js solutions, but that cost is paid specifically for the benefits it brings; as such it’s useful for some usecases, and not meant as a replacement for all workflows. ‬

‪(These conversations always get heated on twitter, so please believe that I’m here to converse, not to convince. In return, I promise to listen to you too and change my opinions; I’ve had mad respect for you for years and would consider your feedback a gift. Also, some of the stuff I’m writing might seem obvious to you; I’m not trying to tell you if all people of some of the details, but it might be useful to someone else who bumps into this who doesn’t have context)‬

So the big deal about css-in-js (cij) is selectors.

dominictarr

Hey everyone - this is not just a one off thing, there are likely to be many other modules in your dependency trees that are now a burden to their authors. I didn't create this code for altruistic motivations, I created it for fun. I was learning, and learning is fun. I gave it away because it was easy to do so, and because sharing helps learning too. I think most of the small modules on npm were created for reasons like this. However, that was a long time ago. I've since moved on from this module and moved on from that thing too and in the process of moving on from that as well. I've written way better modules than this, the internet just hasn't fully caught up.

@broros

otherwise why would he hand over a popular package to a stranger?

If it's not fun anymore, you get literally nothing from maintaining a popular package.

One time, I was working as a dishwasher in a restu

YBogomolov

import { HKT, Type, URIS } from 'fp-ts/lib/HKT';
import { identity, Identity, URI } from 'fp-ts/lib/Identity';
import { Monad, Monad1 } from 'fp-ts/lib/Monad';

// Task: get all users named 'John' and make them admins

interface User {
  id: number;
  name: string;
  age: number;

tcvieira

Setup Fastai v1 on Paperspace

Machine

• Create a Fast.ai machine from public templates w/ P4000 and public IP

Connect to the machine

• $ source deactivate fastai
• $ pip install virtualenv

rxwei

See the official Differentiable Programming Manifesto instead.

cvburgess

const { InMemoryLRUCache } = require("apollo-server-caching");

class SQLCache {
  constructor(cache = new InMemoryLRUCache()) {
    this.cache = cache;
  }

  async knexPlugin(knexThen, ctx, args) {
    const isSelectStatement = ctx._method === "select";

cvburgess

const { InMemoryLRUCache } = require("apollo-server-caching");
const DataLoader = require("dataloader");

class SQLCache {
  constructor(cache = new InMemoryLRUCache(), knex) {
    this.cache = cache;
    this.loader = new DataLoader(queries =>
      Promise.all(queries.map(query => knexInstance.raw(query)))
    );
  }

endolith

"""
Train a neural network to implement the discrete Fourier transform
"""
import matplotlib.pyplot as plt
import numpy as np
from tensorflow.keras.layers import Dense
from tensorflow.keras.models import Sequential

N = 32
batch = 10000