Difference between revisions of "Python for Data Science"
Adelo Vieira (talk | contribs) |
Adelo Vieira (talk | contribs) |
||
| Line 1: | Line 1: | ||
| − | https://www. | + | '''Sentiment Analysis Applications''' |
| + | * https://www.csc2.ncsu.edu/faculty/healey/tweet_viz/tweet_app/ | ||
| + | * https://vimeo.com/andreitr | ||
| + | * https://www.softwareadvice.com/resources/free-twitter-sentiment-analysis-tools/ | ||
| − | https:// | + | * https://blog.flexmr.net/making-sense-of-big-qual-7-of-the-best-text-and-sentiment-analysis-tools |
| − | |||
| − | https://www. | + | '''Mapas''' |
| + | * https://www.amcharts.com/demos/multi-series-map/ | ||
| − | |||
| − | https://www.udemy.com/course/ | + | '''Sentiment analysis with Python''' |
| + | * https://www.udemy.com/course/data-science-natural-language-processing-in-python/ | ||
| − | https://www.udemy.com/course/ | + | * https://www.udemy.com/course/sentiment-analysis-deep-learning-keras-python/ |
| − | https://www.udemy.com/course/ | + | * https://www.udemy.com/course/natural-language-processing-with-deep-learning-in-python/ |
| − | https:// | + | '''Back-end - Flask - DJango''' |
| + | * https://www.udemy.com/course/python-for-data-science-and-machine-learning-bootcamp/ | ||
| − | https:// | + | * https://www.udemy.com/course/python-rest-apis-with-flask-docker-mongodb-and-aws-devops/ |
| − | https:// | + | * https://www.udemy.com/course/rest-api-flask-and-python/ |
| − | https:// | + | * https://www.udemy.com/course/react-django-full-stack/ |
| − | https:// | + | * https://www.udemy.com/course/introduction-to-tweepy-python-twitter-library/ |
| − | https://www. | + | * https://www.udemy.com/course/introduction-to-tweepy-python-twitter-library-part-2/ |
| + | * https://www.udemy.com/course/python-bot-development/ | ||
| − | |||
| − | https:// | + | '''Predicting elections with sentiment analysis''' |
| + | * https://medium.com/@stefanobosisio1/sentiment-analysis-to-predict-political-elections-outcome-506284890132 | ||
| − | https:// | + | * https://ricochet.com/565273/archives/predicting-elections-using-a-i-and-machine-learning/ |
| + | |||
| + | * https://link.springer.com/article/10.1007/s40092-017-0238-2 | ||
| + | |||
| + | * https://pdfs.semanticscholar.org/fd8b/8e5d4ae127afc71437d39881d69d963ed80a.pdf | ||
| + | |||
| + | * https://medium.com/analytics-vidhya/twitter-sentiment-analysis-for-the-2019-election-8f7d52af1887 | ||
| + | |||
| + | * https://www.researchgate.net/publication/280623314_The_machine_learning_in_the_prediction_of_elections | ||
Revision as of 23:38, 5 October 2019
Sentiment Analysis Applications
Mapas
Sentiment analysis with Python
Back-end - Flask - DJango
Predicting elections with sentiment analysis
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)
