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An Analysis… | …of random things

8230;of random things. Predicting Yelp ratings using textual reviews. Internet is truly full of free and fascinating datasets! I found this Yelp Dataset Challenge the other day that includes, among others, over 1 million reviews (most of which are recent) along with their respective 5-star ratings – excellent text. December 30, 2014. Notes to machine learning. November 15, 2014. Quora challenge – answer classification. November 15, 2014. Building a book recommender. October 4, 2014. If you are not from C...

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An Analysis… | …of random things | runzemc.com Reviews

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8230;of random things. Predicting Yelp ratings using textual reviews. Internet is truly full of free and fascinating datasets! I found this Yelp Dataset Challenge the other day that includes, among others, over 1 million reviews (most of which are recent) along with their respective 5-star ratings – excellent text. December 30, 2014. Notes to machine learning. November 15, 2014. Quora challenge – answer classification. November 15, 2014. Building a book recommender. October 4, 2014. If you are not from C...

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An Analysis… | …of random things | runzemc.com Reviews

https://runzemc.com

8230;of random things. Predicting Yelp ratings using textual reviews. Internet is truly full of free and fascinating datasets! I found this Yelp Dataset Challenge the other day that includes, among others, over 1 million reviews (most of which are recent) along with their respective 5-star ratings – excellent text. December 30, 2014. Notes to machine learning. November 15, 2014. Quora challenge – answer classification. November 15, 2014. Building a book recommender. October 4, 2014. If you are not from C...

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Building a book recommender – An Analysis…

http://www.runzemc.com/2014/10/building-a-book-recommender.html

8230;of random things. Building a book recommender. For example, has a group of in-house music experts that make playlists all day and 8tracks. But it’s still a very interesting problem nevertheless! As my first attempt at building such a system, I made a simple book recommender that, based on LDA modeling results and cosine similarities, recommends books from New York Times. 8216; and NPR. For users. You can check out my app here. And my R code here. Scraping New York Times. For each book, the website u...

2

Predicting Yelp ratings using textual reviews – An Analysis…

http://www.runzemc.com/2014/12/predicting-yelp-ratings-using-textual-reviews.html

8230;of random things. Predicting Yelp ratings using textual reviews. Internet is truly full of free and fascinating datasets! I found this Yelp Dataset Challenge. The other day that includes, among others, over 1 million reviews (most of which are recent) along with their respective 5-star ratings – excellent text mining material! The IPython notebooks are rendered by nbviewer here. And the individual files can be accessed and viewed directly below:. Training models using the sentiment scores. Quora cha...

3

How Californians reacted to the Brazil vs. Germany game – An Analysis…

http://www.runzemc.com/2014/07/how-californians-reacted-to-the-brazil-vs-germany-game.html

8230;of random things. How Californians reacted to the Brazil vs. Germany game. Unless you’ve been living under a rock, there is no way you haven’t heard about the insert appropriate adjective game between Brazil and Germany yesterday (7/8/14), and chances are you have also seen this twitter heat map video. That went viral today. While watching it, I realized I have all the data to do such an analysis myself too (as I’ve been collecting tweets for another project). So I did. Since the majority of the twe...

4

Notes to machine learning – An Analysis…

http://www.runzemc.com/2014/11/notes-to-machine-learning.html

8230;of random things. Notes to machine learning. Below are my notes to machine learning when I was learning the subject myself (the two primary books I referenced are included in the notes below). As I’ve been reviewing the subject a lot these days, I decided to organize them and host them in a central place. They are still subject to revision as I learn more about it. Notes to machine learning. Tagged on: Machine learning. November 15, 2014. November 16, 2014. Leave a Reply Cancel reply.

5

Random acts of pizza – a Kaggle competition – An Analysis…

http://www.runzemc.com/2014/08/random-acts-of-pizza.html

8230;of random things. Random acts of pizza – a Kaggle competition. This weekend, I participated in a Kaggle not-for-prize competition that uses data obtained from Reddit’s Random Acts of Pizza forum. To analyze and predict the outcome of a request for pizza, and it was. Of fun (I always wanted to say that)! I have put all my code on github. Including the part related to topic modeling and data exploration) and here is a detailed explanation of what I did. Following the authors’ strategy, the first...

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An Analysis… | …of random things

8230;of random things. Predicting Yelp ratings using textual reviews. Internet is truly full of free and fascinating datasets! I found this Yelp Dataset Challenge the other day that includes, among others, over 1 million reviews (most of which are recent) along with their respective 5-star ratings – excellent text. December 30, 2014. Notes to machine learning. November 15, 2014. Quora challenge – answer classification. November 15, 2014. Building a book recommender. October 4, 2014. If you are not from C...

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