TwitterSentimentAndCryptocurrencies | Twitter Sentiment to discover correlations | Predictive Analytics library
kandi X-RAY | TwitterSentimentAndCryptocurrencies Summary
kandi X-RAY | TwitterSentimentAndCryptocurrencies Summary
This project is part of the Web Mining course at the HEIG-VD for the MSE HES-SO. The students realizing the project are Antoine Drabble & Sébastien Richoz. A cryptocurrency is a controversial digital asset designed to work as a medium of exchange that uses strong cryptography to secure financial transactions, control the creation of additional units, and verify the transfer of assets. Cryptocurrencies are extremely volatile. Four years of volatility in the stock market can be covered in a month of pricing movements in the cryptocurrency markets. Twitter is an online news and social networking service on which users post and interact with messages known as "tweets". It is also the primary channel of communication for cryptocurrencies. Many important news are relayed (retweeted) by thousands of user and can reach a very large audience. For example, John McAfee, who has 828'338 followers at the moment, is a famous cryptocurrency user. His tweets can affect the course of a cryptocurrency up to more than 100% due to his huge audience. There are many other influential Twitter users. The goal of this project is to propose a tool to visualize the correlation between cryptocurrencies' price in USD and a score based on the sentiment analysis of tweets, the number of followers of the user, the number of retweets and the number of likes. In the first part we will make an historical analysis of the correlation. In the second part we will propose a tool for the realtime visualisation of the evolution of tweets scores with cryptocurrency's price in USD.
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Trending Discussions on Predictive Analytics
QUESTION
GPU is good for parallel computing but the problem is some machine learning libraries don't utilize the GPU, unless that machine learning based on image processing or some sort of graphics processing, what if I am using machine learning for predictive Analytics? do libraries like TensorFlow utilize the GPU? or they use only CPU? or can I choose which processing unit to use? whats the deal here?
note: predictive Analysis requires no graphics processing.
...ANSWER
Answered 2020-Nov-21 at 21:35The computation that happens in the GPU in any of the machine learning frameworks that support GPUs is not limited to graphical processing. For instance, if your model is a simple logistic regression, a framework such as TensorFlow will run it on the GPU if properly configured.
The advantage of GPUs for machine learning is that training big neural networks benefits greatly from the high level of parallelism that the GPUs offer.
If you want to know more about this, I'd recommend you start here or here.
some things to consider:- how much a model will benefit from running in the GPU will depend on how much it will benefit from parallel computation in general.
- Deep Learning models can be applied to predictive analytics, as well as more classical machine learning models. Bear in mind that neural nets are possibly the category of models that will benefit inherently from the GPU (see links above).
- Even though running models using GPUs (or even more specialised hardware) can bring benefits, I would suggest that you don't choose a framework and, especially, don't choose an algorithm based solely on the fact that it will benefit from parallelism, but rather look at how appropriate a given algorithm is for the data you have.
QUESTION
I have a pandas dataframe which is a large number of answers given by users in response to a survey and I need to re-structure it. There are up to 105 questions asked each year, but I only need maybe 20 of them.
The current structure is as below.
What I want to do is re-structure it so that the row values become column names and the answer given by the user is then the value in that column. In a picture (from Excel), what I want is the below (I know I'll need to re-name my columns, but that's fine once I can create the structure in the first place):
Is it possible to re-structure my dataframe this way? The outcome of this is to use some predictive analytics to predict a target variable, so I need to re-strcture before I can use Random Forest, kNN, and so on.
...ANSWER
Answered 2020-Nov-01 at 19:39You might want try pivoting your table:
QUESTION
I have js files Dashboard and Adverts. I managed to get Dashboard to list the information in one json file (advertisers), but when clicking on an advertiser I want it to navigate to a separate page that will display some data (Say title and text) from the second json file (productadverts). I can't get it to work. Below is the code for the Dashboard and next for Adverts. Then the json files
...ANSWER
Answered 2020-May-17 at 23:55The new object to get params in React Navigation 5 is:
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Install TwitterSentimentAndCryptocurrencies
To execute the js script: please rename streamer/.env-sample into streamer/.env and edit the file with your plotly configuration. Install npm with nodejs (https://www.npmjs.com/get-npm) then $ cd streamer/ then run this command $ npm install && node stream_crypto.js. You need to be in the streamer folder to execute the command or it may not work.
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