Mohcine Madkour mohcinemadkour

Deep Learning Hands-On Series with Eric Schles

05/22 - Deep Learning Hands-On Series - Data Exploration and API First Design 🎥

05/29 - Deep Learning Hands-On Series - Model Tuning 🎥

06/05 - Deep Learning Hands-On Series - Monitoring [cancelled]

Resources

Notebooks

Installing Traccar via Docker

... without installing Maven on your computer. This process will use the Docker container maven:3.5-jdk-8-alpine instead of a local Maven installation.

I used Ubuntu 16.04 server with the NGINX webserver.

📢 Deprecation notice 2019-06-29 📢

Traccar can now be run in Docker without building it yourself, just get the container from Docker Hub: https://hub.docker.com/r/traccar/traccar/

FWIW: I (@rondy) am not the creator of the content shared here, which is an excerpt from Edmond Lau's book. I simply copied and pasted it from another location and saved it as a personal note, before it gained popularity on news.ycombinator.com. Unfortunately, I cannot recall the exact origin of the original source, nor was I able to find the author's name, so I am can't provide the appropriate credits.

Effective Engineer - Notes

By Edmond Lau
Highly Recommended 👍
http://www.theeffectiveengineer.com/

What's an Effective Engineer?

How To Serve Flask Applications with uWSGI and Nginx on Ubuntu 14.04

@credit Yan Zhu (https://github.com/nina-zhu)

Introduction

Flask is a microframework for Python based on Werkzeug, Jinja 2 and good intentions, it can help you get your Python application or website off the ground. Flask includes a simplified development server for testing your code locally, but for anything even slightly production related, a more secure and powerful web server is required.

In this guide, we will demonstrate how to install and configure some components on Ubuntu 14.04 to support and serve Flask applications. We will configure the uWSGI application container server to interface with our applications. We will then set up Nginx to reverse proxy to uWSGI, giving us access to its security and performance features to serve our apps.

Prerequisites and Goals

A Typical directory structure for running tests using `unittest`

Ref : stackoverflow

The best solution in my opinion is to use the unittest [command line interface][1] which will add the directory to the sys.path so you don't have to (done in the TestLoader class).

For example for a directory structure like this:

new_project

├── antigravity.py

tmux cheatsheet

As configured in my dotfiles.

start new:

tmux

start new with session name:

Sublime Text 2 - Useful Shortcuts

Tested in Mac OS X: super == command

Open/Goto

super+t: go to file
super+ctrl+p: go to project
super+r: go to methods

	heat_plot <- function(player, d, HR=FALSE){
	# inputs
	# player - name of player
	# d - pitchRX data frame with variables Batter, Event, and X, Z (location of pitch)
	# will output a ggplot2 object
	# need to use print function to display the pot
	require(dplyr)
	require(ggplot2)
	require(mgcv)
	# define the strike zone