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Code for Keras plays catch blog post

Train

python qlearn.py

Test

1. Generate figures

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OS X Screencast to animated GIF

This gist shows how to create a GIF screencast using only free OS X tools: QuickTime, ffmpeg, and gifsicle.

Instructions

To capture the video (filesize: 19MB), using the free "QuickTime Player" application:

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/* 
 * Set up your Git configuration 
 */

git config --global user.email "[email protected]"

git config --global user.name "Your Name"

git config --global core.editor "nano"

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# Install the PyDrive wrapper & import libraries.
!pip install -U -q PyDrive
from pydrive.auth import GoogleAuth
from pydrive.drive import GoogleDrive
from google.colab import auth
from oauth2client.client import GoogleCredentials

# Authenticate and create the PyDrive client.
auth.authenticate_user()
gauth = GoogleAuth()

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#!/usr/bin/env python

"""
How to use it:
1. Just `kill -2 PROCESS_ID` or `kill -15 PROCESS_ID`,
   The Tornado Web Server Will shutdown after process all the request.
2. When you run it behind Nginx, it can graceful reboot your production server.
"""

import time

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So you've cloned somebody's repo from github, but now you want to fork it and contribute back. Never fear!

Technically, when you fork "origin" should be your fork and "upstream" should be the project you forked; however, if you're willing to break this convention then it's easy.

* Off the top of my head *

1. Fork their repo on Github
2. In your local, add a new remote to your fork; then fetch it, and push your changes up to it

    git remote add my-fork [email protected]

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def press_statistic(y_true, y_pred, xs):
    """
    Calculation of the `Press Statistics <https://www.otexts.org/1580>`_
    """
    res = y_pred - y_true
    hat = xs.dot(np.linalg.pinv(xs))
    den = (1 - np.diagonal(hat))
    sqr = np.square(res/den)
    return sqr.sum()

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import matplotlib.pyplot as plt

def draw_neural_net(ax, left, right, bottom, top, layer_sizes):
    '''
    Draw a neural network cartoon using matplotilb.
    
    :usage:
        >>> fig = plt.figure(figsize=(12, 12))
        >>> draw_neural_net(fig.gca(), .1, .9, .1, .9, [4, 7, 2])
    

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#!/usr/bin/env bash

# Create isolated ROS Workspace
cd ~
mkdir ros_py35
cd ros_py35

# Unset sourced workspace
# Go to ~/.bashrc and comment out lines from previous installation of ROS (Lunar)

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ffmpeg

Converting Audio into Different Formats / Sample Rates

Minimal example: transcode from MP3 to WMA:
ffmpeg -i input.mp3 output.wma

You can get the list of supported formats with:
ffmpeg -formats

Convert WAV to MP3, mix down to mono (use 1 audio channel), set bit rate to 64 kbps and sample rate to 22050 Hz: