Ishan Khatri ishankhatri90

## youtube-dl-download-audio-only-on-best-quality.md

      
              1 file
            
          
              0 forks
            
          
              0 comments
            
          
              0 stars
            
          
                ishankhatri90
                / youtube-dl-download-audio-only-on-best-quality.md
            
            
              Created
              May 14, 2020 21:24
                — forked from umidjons/youtube-dl-download-audio-only-on-best-quality.md
            
              
                Download Audio from YouTube with youtube-dl
              
          
    Download Audio from YouTube

-i - ignore errors
-c - continue
-t - use video title as file name
--extract-audio - extract audio track

  
## Sorta.scala
package org.logician.sorta

import scala.util.Random
import scala.math
import scala.collection.mutable
import scala.collection.mutable.ArrayBuffer

/**
 * Created with IntelliJ IDEA.
 * User: Austin

## config.txt
# From https://www.raspberrypi.org/forums/viewtopic.php?f=29&t=24679&start=50

hdmi_ignore_cec_init=1
hdmi_drive=2
disable_overscan=1

hdmi_ignore_edid=0xa5000080
hdmi_group=2
hdmi_mode=87
hdmi_timings=2560 1 64 64 96 1080 1 3 10 31 0 0 1 60 0 185580000 8

## groupyby_parallel.py
# coding=utf-8

import pandas as pd
import itertools
import time
import multiprocessing
from typing import Callable, Tuple, Union

def groupby_parallel(groupby_df: pd.core.groupby.DataFrameGroupBy,
                     func: Callable[[Tuple[str, pd.DataFrame]], Union[pd.DataFrame, pd.Series]],

## useful_pandas_snippets.py
# List unique values in a DataFrame column
pd.unique(df.column_name.ravel())

# Convert Series datatype to numeric, getting rid of any non-numeric values
df['col'] = df['col'].astype(str).convert_objects(convert_numeric=True)

# Grab DataFrame rows where column has certain values
valuelist = ['value1', 'value2', 'value3']
df = df[df.column.isin(valuelist)]

## kalman_example.py

import numpy as np
import matplotlib.pyplot as plt

plt.rcParams['figure.figsize'] = (10, 8)

# intial parameters
n_iter = 50
sz = (n_iter,) # size of array
x = -0.37727 # truth value (typo in example at top of p. 13 calls this z)

## install.sh
#!/bin/sh

# installation of Oracle Java JDK.
sudo apt-get -y update
sudo apt-get -y install python-software-properties
sudo add-apt-repository -y ppa:webupd8team/java
sudo apt-get -y update
sudo apt-get -y install oracle-java7-installer

# Installation of commonly used python scipy tools

## sentiment.py
import os
import time
import string
import pickle

from operator import itemgetter

from nltk.corpus import stopwords as sw
from nltk.corpus import wordnet as wn
from nltk import wordpunct_tokenize

## tf_idf_final.py
#-*- coding: utf-8 -*-

import re
import nltk
from nltk.tokenize import RegexpTokenizer
from nltk import bigrams, trigrams
import math


stopwords = nltk.corpus.stopwords.words('portuguese')

## NTU - Machine Learning
Codes for Machine Learning Foundations(NTU)
台湾国立大学《机器学习基石》（Coursera版）相关的代码、编程作业等。

课程地址：https://class.coursera.org/ntumlone-001/
	package org.logician.sorta

	import scala.util.Random
	import scala.math
	import scala.collection.mutable
	import scala.collection.mutable.ArrayBuffer

	/**
	* Created with IntelliJ IDEA.
	* User: Austin
	# From https://www.raspberrypi.org/forums/viewtopic.php?f=29&t=24679&start=50

	hdmi_ignore_cec_init=1
	hdmi_drive=2
	disable_overscan=1

	hdmi_ignore_edid=0xa5000080
	hdmi_group=2
	hdmi_mode=87
	hdmi_timings=2560 1 64 64 96 1080 1 3 10 31 0 0 1 60 0 185580000 8
	# coding=utf-8

	import pandas as pd
	import itertools
	import time
	import multiprocessing
	from typing import Callable, Tuple, Union

	def groupby_parallel(groupby_df: pd.core.groupby.DataFrameGroupBy,
	func: Callable[[Tuple[str, pd.DataFrame]], Union[pd.DataFrame, pd.Series]],
	# List unique values in a DataFrame column
	pd.unique(df.column_name.ravel())

	# Convert Series datatype to numeric, getting rid of any non-numeric values
	df['col'] = df['col'].astype(str).convert_objects(convert_numeric=True)

	# Grab DataFrame rows where column has certain values
	valuelist = ['value1', 'value2', 'value3']
	df = df[df.column.isin(valuelist)]

	import numpy as np
	import matplotlib.pyplot as plt

	plt.rcParams['figure.figsize'] = (10, 8)

	# intial parameters
	n_iter = 50
	sz = (n_iter,) # size of array
	x = -0.37727 # truth value (typo in example at top of p. 13 calls this z)
	#!/bin/sh

	# installation of Oracle Java JDK.
	sudo apt-get -y update
	sudo apt-get -y install python-software-properties
	sudo add-apt-repository -y ppa:webupd8team/java
	sudo apt-get -y update
	sudo apt-get -y install oracle-java7-installer

	# Installation of commonly used python scipy tools
	import os
	import time
	import string
	import pickle

	from operator import itemgetter

	from nltk.corpus import stopwords as sw
	from nltk.corpus import wordnet as wn
	from nltk import wordpunct_tokenize
	#-- coding: utf-8 --

	import re
	import nltk
	from nltk.tokenize import RegexpTokenizer
	from nltk import bigrams, trigrams
	import math


	stopwords = nltk.corpus.stopwords.words('portuguese')
	Codes for Machine Learning Foundations(NTU)
	台湾国立大学《机器学习基石》（Coursera版）相关的代码、编程作业等。

	课程地址：https://class.coursera.org/ntumlone-001/