wordview VS obsei

Compare wordview vs obsei and see what are their differences.

Judoscale - Save 47% on cloud hosting with autoscaling that just works
Judoscale integrates with Django, FastAPI, Celery, and RQ to make autoscaling easy and reliable. Save big, and say goodbye to request timeouts and backed-up task queues.
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InfluxDB high-performance time series database
Collect, organize, and act on massive volumes of high-resolution data to power real-time intelligent systems.
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wordview obsei
1 9
11 1,260
- 0.4%
0.0 5.1
18 days ago 6 months ago
Python Python
MIT License Apache License 2.0
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

wordview

Posts with mentions or reviews of wordview. We have used some of these posts to build our list of alternatives and similar projects.

obsei

Posts with mentions or reviews of obsei. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-02-27.

What are some alternatives?

When comparing wordview and obsei you can also consider the following projects:

Unredactor - In this project we are tryinbg to create unredactor. Unredactor will take a redacted document and the redacted flag as input, inreturn it will give the most likely candidates to fill in redacted location. In this project we are only considered about unredacting names only. The data that we are considering is imdb data set with many review files. These files are used to buils corpora for finding tfidf score. Few files are used to train and in these files names are redacted and written into redacted folder. These redacted files are used for testing and different classification models are built to predict the probabilies of each class. Top 5 classes i.e names similar to the test features are written at the end of text in unreddacted foleder.

awesome-sentiment-analysis - Repository with all what is necessary for sentiment analysis and related areas

tf-idf - Term Frequency-Inverse Document Frequency from Scratch

budibase - Budibase is an open-source low code platform that helps you build internal tools in minutes 🚀

NLP-Model-for-Corpus-Similarity - A NLP algorithm I developed to determine the similarity or relation between two documents/Wikipedia articles. Inspired by the cosine similarity algorithm and built from WordNet.

R-text-data - List of textual data sources to be used for text mining in R

Judoscale - Save 47% on cloud hosting with autoscaling that just works
Judoscale integrates with Django, FastAPI, Celery, and RQ to make autoscaling easy and reliable. Save big, and say goodbye to request timeouts and backed-up task queues.
judoscale.com
featured
InfluxDB high-performance time series database
Collect, organize, and act on massive volumes of high-resolution data to power real-time intelligent systems.
influxdata.com
featured