jeremy woo appcoreopc

## index.html
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## gist:1809690078102648e8c7d1b76de450e5

      
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                appcoreopc
                / gist:1809690078102648e8c7d1b76de450e5
            
            
              Created
              October 24, 2018 16:11
                — forked from debasishg/gist:8172796
            
              
                A collection of links for streaming algorithms and data structures
              
          
General Background and Overview


Probabilistic Data Structures for Web Analytics and Data Mining : A great overview of the space of probabilistic data structures and how they are used in approximation algorithm implementation.
Models and Issues in Data Stream Systems
Philippe Flajolet’s contribution to streaming algorithms : A presentation by Jérémie Lumbroso that visits some of the hostorical perspectives and how it all began with Flajolet
Approximate Frequency Counts over Data Streams by Gurmeet Singh Manku & Rajeev Motwani : One of the early papers on the subject.
[Methods for Finding Frequent Items in Data Streams](http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.187.9800&amp;rep


## protractorAPICheatsheet.md

      
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                appcoreopc
                / protractorAPICheatsheet.md
            
            
              Created
              August 1, 2018 19:23
                — forked from javierarques/protractorAPICheatsheet.md
            
              
                Protractor API Cheatsheet
              
          
    Protractor API

http://angular.github.io/protractor/#/api
Note: Most commands return promises, so you only resolve their values through using jasmine expect API or using .then(function()) structure
Based on this post: https://spagettikoodi.wordpress.com/2015/01/14/angular-testing-cheat-sheet/ by @crystoll
Control browser

browser.get('yoururl'); // Load address, can also use '#yourpage'

  
## ngrxintro.md

      
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                appcoreopc
                / ngrxintro.md
            
            
              Created
              December 7, 2017 20:01
                — forked from btroncone/ngrxintro.md
            
              
                A Comprehensive Introduction to @ngrx/store - Companion to Egghead.io Series
              
          
    Comprehensive Introduction to @ngrx/store

By: @BTroncone
Also check out my lesson @ngrx/store in 10 minutes on egghead.io!
Update: Non-middleware examples have been updated to ngrx/store v2. More coming soon!
Table of Contents


## gist:175bdaefdb5bc7b312a7d5ca581aa79e

      
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                appcoreopc
                / gist:175bdaefdb5bc7b312a7d5ca581aa79e
            
            
              Created
              February 22, 2017 08:08
                — forked from entaroadun/gist:1653794
            
              
                Recommendation and Ratings Public Data Sets For Machine Learning 
              
          
    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
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