simecek

tjukanovt

import requests
import csv
import datetime
import calendar
import time
            
i=0
# Change the range depending on how long you like to record the data
for i in range (0,50):
    

bnutz

Just documenting my own experiences in restoring my Nexus 5X back from bootlooping state.

Hopefully this can be helpful to some, but "common sense" caveats apply:

• Follow at your own risk
• I'm not responsible for any loss of data, loss of hair, bricked devices, exploding(!) devices, mental / physical injuries, etc. etc. etc.

Remember:

• This is only an account of what I did to get my 5X working operational again.
• YMMV if you decide to try the steps below on your bootlooping device.

nygeog

import pandas as pd
from geopandas import GeoDataFrame
from shapely.geometry import Point
import fiona

df = pd.read_csv('data.csv')

geometry = [Point(xy) for xy in zip(df.x, df.y)]
crs = {'init': 'epsg:2263'} #http://www.spatialreference.org/ref/epsg/2263/
geo_df = GeoDataFrame(df, crs=crs, geometry=geometry)

davidvasandani

Learning How To Learn

Module 1 - What is Learning

Focused/Diffuse Modes Thinking
	- Obviously ‘focused’ is when you’re concentrating. Direct approach to solving familiar problems.
	- Focused: thoughts move through nicely-paved road of familiar notions (neural pattern looks very tight and directed).
		- encompasses rational, sequential, analytical approaches to thinking
	- Diffuse: More of a search function neural pattern. Thoughts move widely. More of a broad/big-picture perspective trying to connect ideas from different places.
	- We’re always either in focused or diffuse mode of thinking.

mrocklin

fchollet

'''This script goes along the blog post
"Building powerful image classification models using very little data"
from blog.keras.io.
It uses data that can be downloaded at:
https://www.kaggle.com/c/dogs-vs-cats/data
In our setup, we:
- created a data/ folder
- created train/ and validation/ subfolders inside data/
- created cats/ and dogs/ subfolders inside train/ and validation/
- put the cat pictures index 0-999 in data/train/cats

fchollet

'''This script goes along the blog post
"Building powerful image classification models using very little data"
from blog.keras.io.
It uses data that can be downloaded at:
https://www.kaggle.com/c/dogs-vs-cats/data
In our setup, we:
- created a data/ folder
- created train/ and validation/ subfolders inside data/
- created cats/ and dogs/ subfolders inside train/ and validation/
- put the cat pictures index 0-999 in data/train/cats

karpathy

""" Trains an agent with (stochastic) Policy Gradients on Pong. Uses OpenAI Gym. """
import numpy as np
import cPickle as pickle
import gym

# hyperparameters
H = 200 # number of hidden layer neurons
batch_size = 10 # every how many episodes to do a param update?
learning_rate = 1e-4
gamma = 0.99 # discount factor for reward

EderSantana

Code for Keras plays catch blog post

Train

python qlearn.py

Test

1. Generate figures