Difference between revisions of "Data Science"

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(Social Media Sentiment Analysis)
(Methodology)
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* Secondly, we will need to store the data.
 
* Secondly, we will need to store the data.
 
* The third part of the project will be the analysis of the data. Here is where Machine learning will be implement.
 
* The third part of the project will be the analysis of the data. Here is where Machine learning will be implement.
** In this part we first need to decide what we want to analysis. There are many examples, here is a nice work I found: «This article describes the techniques that effectively analyzed Twitter Trend Topics to predict, as a sample test case, regional voting patterns in the 2014 Brazilian presidential election» : https://www.toptal.com/data-science/social-network-data-mining-for-predictive-analysis
+
** In this part we first need to decide what we want to analysis.
 +
*** There are many examples, here is a nice work I found: «This article describes the techniques that effectively analyzed Twitter Trend Topics to predict, as a sample test case, regional voting patterns in the 2014 Brazilian presidential election» : https://www.toptal.com/data-science/social-network-data-mining-for-predictive-analysis
 
:: In essence, this guy analyses Twitter data for the days prior to the election and got this mapa:
 
:: In essence, this guy analyses Twitter data for the days prior to the election and got this mapa:
  
 
[[File:Brazilian_elections_2014.png|950px|thumb|center|]]
 
[[File:Brazilian_elections_2014.png|950px|thumb|center|]]
  
 +
::* Another example will be:
 +
 +
::* <span style="background:#00FF00">But it will be up to us (as a team) to determine what we want to analyses.</span>
  
  

Revision as of 18:06, 2 October 2018

Social Media Sentiment Analysis

Motivation

Social media has almost become synonymous with «big data» due to the sheer amount of user-generated content.

Mining this rich data can prove unprecedented ways to keep a pulse on opinions, trends, and public sentiment. Facebook, Twitter, YouTube, WeChat... etc.

Social media data will become even more relevant for marketing, branding, and business as a whole.

As you see, this kind of analysis is a tool that will become more and more important in the coming years.

Methodology

  • The first part of the project will be: Mining Social Media data
  • Secondly, we will need to store the data.
  • The third part of the project will be the analysis of the data. Here is where Machine learning will be implement.
In essence, this guy analyses Twitter data for the days prior to the election and got this mapa:
Brazilian elections 2014.png
  • Another example will be:
  • But it will be up to us (as a team) to determine what we want to analyses.



https://www.dezyre.com/article/top-10-machine-learning-projects-for-beginners/397

https://elitedatascience.com/machine-learning-projects-for-beginners#social-media

https://en.wikipedia.org/wiki/Sentiment_analysis

https://en.wikipedia.org/wiki/Social_media_mining

Remote development

Eclipse - Connect to a remote file system

https://us.informatiweb.net/tutorials/it/6-web/148--eclipse-connect-to-a-remote-file-system.html

Mount a remote filesystem in your local machine

https://www.digitalocean.com/community/tutorials/how-to-use-sshfs-to-mount-remote-file-systems-over-ssh

https://stackoverflow.com/questions/32747819/remote-java-development-using-intellij-or-eclipse

https://serverfault.com/questions/306796/sshfs-problem-when-losing-connection

https://askubuntu.com/questions/358906/sshfs-messes-up-everything-if-i-lose-connection

https://askubuntu.com/questions/716612/sshfs-auto-reconnect

root@sinfronteras.ws: /home/adelo/1-system/3-cloud
sshfs -o reconnect,ServerAliveInterval=5,ServerAliveCountMax=3 root@sinfronteras.ws: /home/adelo/1-system/3-cloud
sshfs -o allow_other root@sinfronteras.ws: /home/adelo/1-system/3-cloud


faster way to mount a remote file system than sshfs: https://superuser.com/questions/344255/faster-way-to-mount-a-remote-file-system-than-sshfs

Anaconda

Anaconda is a free and open source distribution of the Python and R programming languages for data science and machine learning related applications (large-scale data processing, predictive analytics, scientific computing), that aims to simplify package management and deployment. Package versions are managed by the package management system conda. https://en.wikipedia.org/wiki/Anaconda_(Python_distribution)

Installation

https://www.anaconda.com/download/#linux

https://linuxize.com/post/how-to-install-anaconda-on-ubuntu-18-04/

https://www.digitalocean.com/community/tutorials/how-to-install-the-anaconda-python-distribution-on-ubuntu-18-04

Jupyter Notebook

https://www.datacamp.com/community/tutorials/tutorial-jupyter-notebook

Cursos

eu.udacity.com

https://classroom.udacity.com/courses/ud120

www.coursera.org

https://www.coursera.org/learn/machine-learning/home/welcome

Otros

https://www.udemy.com/machine-learning-course-with-python/

https://stackoverflow.com/questions/19181999/how-to-create-a-keyboard-shortcut-for-sublimerepl