bhavikngala

This gist contains a list of points I found very useful while watching the fast.ai "Practical deep learning for coders" and "Cutting edge deep learning for coders" MOOC by Jeremy Howard and team. This list may not be complete as I watched the video at 1.5x speed on marathon but I did write down as many things I found to be very useful to get a model working. A fair warning the points are in no particular order, you may find the topics are all jumbled up.

Before beginning, I want to thank Jeremy Howard, Rachel Thomas, and the entire fast.ai team in making this awesome practically oriented MOOC.

1. Progressive image resolution training: Train the network on lower res first and then increase the resolution to get better performance. This can be thought of as transfer learning from the same dataset but at a different resolution. There is one paper by NVIDIA as well that used such an approach to train GANs.

2. Cyclical learning rates: Gradually increasing the learning rate initially helps to avoid getting stuc

480

MacOS X + oh my zsh + powerline fonts + visual studio code (vscode) terminal settings

Thank you everybody, Your comments makes it better

Install oh my zsh

http://ohmyz.sh/

sh -c "$(curl -fsSL https://raw.github.com/ohmyzsh/ohmyzsh/master/tools/install.sh)"

inoperable

#!/usr/bin/env zsh

function exportDefaults {
    local outdir="$HOME/defaults"
    local outdirApple="$outdir/apple"
    local outdirUser="$outdir/user"
    local outdirGlobal="$outdir/global"
    local filesdone=0
    local filecount=0
    local filestotal=0

jjnilton

Disclaimer: I'm not the original author of this sheet, but can't recall where I found it. If you know the author, please let me know so I give the attribution.

The original author seems to be Charles Edge, here's the original content, as pointed out by @percisely.

Note: Since this seems to be helpful to some people, I formatted it to improve readability of the original. Also, note that this is from 2016, many things may have changed, and I don't use macOS anymore, so I probably can't help in case of questions, but maybe someone else can.

Mac Network Commands Cheat Sheet

After writing up the presentation for MacSysAdmin in Sweden, I decided to go ahead and throw these into a quick cheat sheet for anyone who’d like to have them all in one place. Good luck out there, and s

staltz

The introduction to Reactive Programming you've been missing

(by @andrestaltz)

---

This tutorial as a series of videos

If you prefer to watch video tutorials with live-coding, then check out this series I recorded with the same contents as in this article: Egghead.io - Introduction to Reactive Programming.

---

sundeepblue

int find_min_diff(vector<int>& A, vector<int>& B) {
	if(A.empty() || B.empty()) return -1;
	int m = A.size(), n = B.size();
	int i = 0, j = 0;
	int min_diff = INT_MAX;
	
	while(i < m && j < n) {
	    int diff = abs(A[i] - B[j]);
	    min_diff = min(min_diff, diff);
	    if(min_diff == 0) return 0;

sundeepblue

2^10=1024 ~10^3
2^64=(2^10)^6 * 2^4
=> (10^3)^6*16
=> 10^18*16
=> 1.6 * 10 ^ 19

= 16,000,000,000,000,000,000
Calculator says: 18,446,744,073,709,551,616

irazasyed

Homebrew Permissions Denied Issues Solution

sudo chown -R $(whoami) $(brew --prefix)/*

willwade

## The following is from TonyT
## http://hints.macworld.com/article.php?story=2008051406323031

import sys
import time
from Quartz.CoreGraphics import *    # imports all of the top-level symbols in the module

class AppleMouseEvents():
    """
     with thanks to:

adamnengland

redis = require "redis"

randomString = (length) ->
  chars = '0123456789abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ'
  result = ""
  i = length

  while i > 0
    result += chars[Math.round(Math.random() * (chars.length - 1))]
    --i