fccforensics | Determine public opinion on net neutrality issue | Predictive Analytics library
kandi X-RAY | fccforensics Summary
kandi X-RAY | fccforensics Summary
Determine public opinion on net neutrality issue via sourcing and sentiment analysis of FCC comments.
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Top functions reviewed by kandi - BETA
- Tag positive terms
- Bulk update operation
- Bulk update a document
- Tag all documents matching a phrase
- Bulk index a given queue
- Determine ingestion method
- Check if a comment is complete
- Analyze a comment
- Runs the search
- Checks if a given email is reachable
- Tag submissions by email
- Return the source
- Run untagged query
- Tag a single document
- Generate index command
- Run bulk index
- Command line interface
- Runs attack
- Create a new index
- Query Elasticsearch by source
- Query by source
- Run a query to a function
- Command line parser
- Analyze comments
- Tags negative terms
- Run the bulk index
- Worker for tagging comments
fccforensics Key Features
fccforensics Examples and Code Snippets
Community Discussions
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:
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install fccforensics
go to http://localhost:5601
go to Management / Configure an index pattern Index name or pattern: fcc-comments [x] Index contains time-based events Time-field name: date_dissemenated Create
Set up cloud-hosted Elasticsearch:.
read-only user for queries
read-write user for ingest and analyze
get ES_URL like https://user:password@hostname:port
create index: fcc create --endpoint=$ES_URL
fetch comments from FCC and add to index: fcc index --endpoint=$ES_URL -g 2017-05-01 (restart as needed if/when API times out)
run static analyzers, 100k at a time: fcc analyze --endpoint=$ES_URL --limit 100000 (repeat until all docs have analyzed: curl '$ES_URL/_count?pretty' -H 'Content-Type: application/json' -d'{"query":{"bool":{"must_not":{"exists":{"field":"analysis"}}}}}')
TODO
cd server/fcc_analysis
zip -r ../lambda.zip . --exclude experiments/* --exclude *.csv --exclude *.txt
cd $VIRTUAL_ENV/lib/python3.6/site-packages
zip -r path/to/server/lambda.zip .
upload to AWS; set handler to lambda.query_by_source
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