YK yongkangc

Movies Recommendation:

MovieLens - Movie Recommendation Data Sets http://www.grouplens.org/node/73
Yahoo! - Movie, Music, and Images Ratings Data Sets http://webscope.sandbox.yahoo.com/catalog.php?datatype=r
Jester - Movie Ratings Data Sets (Collaborative Filtering Dataset) http://www.ieor.berkeley.edu/~goldberg/jester-data/
Cornell University - Movie-review data for use in sentiment-analysis experiments http://www.cs.cornell.edu/people/pabo/movie-review-data/

Music Recommendation:

Last.fm - Music Recommendation Data Sets http://www.dtic.upf.edu/~ocelma/MusicRecommendationDataset/index.html

Ideas

I have collected and moderated these ideas from various public sources and put into one place so that problem solvers and solution developers may find inspirations. Because I wish to update it regularly, I have setup as a single page wiki. You may try these ideas on hackathons/competitions/research; some are quite intense problems and some are not. Many of the problems were prepared keeping Dhaka/Bangladesh in mind, but of course can be applied to just about any underdeveloped/developing and sometimes developed countries.

Categories:

Eradicate Extreme Poverty and Hunger
Education
Healthcare
Governance

Semantic Commit Messages

See how a minor change to your commit message style can make you a better programmer.

Format: <type>(<scope>): <subject>

<scope> is optional

Example

Pipenv Cheat Sheet

Install pipenv

pip3 install pipenv

Activate

pipenv shell

Feel free to copy and paste this list into a README, issue or elsewhere in your project.

Audit prep checklist (reference)

Documentation (A plain english description of what you are building, and why you are building it. Should indicate the actions and states that should and should not be possible)
- For the overall system
- For each unique contract within the system
Clean code
- Run a linter (like EthLint)
Fix compiler warnings

	Latency Comparison Numbers (~2012)
	----------------------------------
	L1 cache reference 0.5 ns
	Branch mispredict 5 ns
	L2 cache reference 7 ns 14x L1 cache
	Mutex lock/unlock 25 ns
	Main memory reference 100 ns 20x L2 cache, 200x L1 cache
	Compress 1K bytes with Zippy 3,000 ns 3 us
	Send 1K bytes over 1 Gbps network 10,000 ns 10 us
	Read 4K randomly from SSD* 150,000 ns 150 us ~1GB/sec SSD

	def plot_learning_curves(estimator, X_train, y_train, X_val, y_val,
	suptitle='', title='', xlabel='', ylabel=''):
	"""
	Plots learning curves for a given estimator.

	Parameters
	----------

	estimator : sklearn estimator
	X_train : pd.DataFrame

	<?php
	/**
	* Gravity Forms Bootstrap Styles
	*
	* Applies bootstrap classes to various common field types.
	* Requires Bootstrap to be in use by the theme.
	*
	* Using this function allows use of Gravity Forms default CSS
	* in conjuction with Bootstrap (benefit for fields types such as Address).
	*

	#Resume Phrase Matcher code


	#importing all required libraries

	import PyPDF2
	import os
	from os import listdir
	from os.path import isfile, join
	from io import StringIO