ohanhi

Learning FP the hard way: Experiences on the Elm language

by Ossi Hanhinen, @ohanhi

with the support of Futurice 💚.

Licensed under CC BY 4.0.

Editorial note

alirobe

### 
###
### UPDATE: For Win 11, I recommend using this tool in place of this script: 
### https://christitus.com/windows-tool/
### https://github.com/ChrisTitusTech/winutil
### https://www.youtube.com/watch?v=6UQZ5oQg8XA
### iwr -useb https://christitus.com/win | iex
###
### OR take a look at 
### https://github.com/HotCakeX/Harden-Windows-Security

dannguyen

Using Python 3 + Google Cloud Vision API's OCR to extract text from photos and scanned documents

Just a quickie test in Python 3 (using Requests) to see if Google Cloud Vision can be used to effectively OCR a scanned data table and preserve its structure, in the way that products such as ABBYY FineReader can OCR an image and provide Excel-ready output.

The short answer: No. While Cloud Vision provides bounding polygon coordinates in its output, it doesn't provide it at the word or region level, which would be needed to then calculate the data delimiters.

On the other hand, the OCR quality is pretty good, if you just need to identify text anywhere in an image, without regards to its physical coordinates. I've included two examples:

####### 1. A low-resolution photo of road signs

jeroenvdgulik

The list is now hosted on a repository so you can PR -> https://github.com/jeroenvdgulik/awesome-talks/blob/master/README.md

The list

• Alberto Brandolini - Chasing Elephants https://youtu.be/klsksbDJOhI
• Erik Meijer - One Hacker Way https://youtu.be/FvMuPtuvP5w
• Erik Meijer - Category Theory, The essence of interface-based design https://youtu.be/JMP6gI5mLHc
• Gary Bernhardt - Wat https://www.destroyallsoftware.com/talks/wat
• Konstantin Kudryashov - Min-maxing Software Costs https://youtu.be/uQUxJObxTUs
• Marco Pivetta - Extremely Defensive PHP https://youtu.be/8d2AtAGJPno

jexp

export NEO4J_HOME=${NEO4J_HOME-~/Downloads/neo4j-community-3.0.1}

if [ ! -f data-csv.zip ]; then
  curl -OL https://cloudfront-files-1.publicintegrity.org/offshoreleaks/data-csv.zip
fi
	
export DATA=${PWD}/import

rm -rf $DATA

agileone

export NEO4J_HOME=${NEO4J_HOME-~/Downloads/neo4j-community-3.0.1}

if [ ! -f data-csv.zip ]; then
  curl -OL https://cloudfront-files-1.publicintegrity.org/offshoreleaks/data-csv.zip
fi
	
export DATA=${PWD}/import

unzip -o -j data-csv.zip -d $DATA

arun-gupta

# Docker Machine for Consul
docker-machine \
   create \
   -d virtualbox \
   consul-machine

# Start Consul
docker $(docker-machine config consul-machine) run -d --restart=always \
         -p "8500:8500" \
         -h "consul" \

gastaldi

#Install the required plugins
addon-install-from-git --url https://github.com/forge/wildfly-swarm-addon.git
addon-install-from-git --url https://github.com/forge/keycloak-addon.git

# Create the project and configure the WildFly Swarm maven plugin
project-new --named demo --stack JAVA_EE_7 --type wildfly-swarm

# Create the JPA entity
jpa-new-entity --named Customer

Digital-Daz

CREATE TABLE json_store (
	name varchar(255) not null,
	data text,
	name_uuid PRIMARY KEY default gen_random_uuid()
	);

ALTER TABLE json_store OWNER TO fusionpbx;

CREATE TABLE agents (
    name character varying(255),

bigsnarfdude

# if error writing `export LD_LIBRARY_PATH="$LD_LIBRARY_PATH:/usr/local/cuda/lib64:/usr/local/cuda/extras/CUPTI/lib64"`


import tensorflow as tf
from tensorflow.examples.tutorials.mnist import input_data

def init_weights(shape, name):
    return tf.Variable(tf.random_normal(shape, stddev=0.01), name=name)

# Step 1 - Add some items to graph section of Tensorboard