monkeylearn VS FastText

MonkeyLearn: A platform for text analysis and machine learning, allowing users to train custom models for tasks like sentiment analysis and topic classification. Source: 5 months ago

Monkeylearn.com — Text analysis with machine learning, free 300 queries/month. - Source: dev.to / over 1 year ago

MonkeyLearn supports 11 languages for data analysis (Spanish, Portuguese, German, Russian, Italian, French, Dutch, Chinese, Japanese, Korean and Arabic).  But for sentiment analysis, only Spanish seems to be available, I’m not sure about that. Source: over 1 year ago

R3: Used RedditExtractoR in R to download all-time top posts, and ran the resulting .csv through https://monkeylearn.com/. Downloaded the resulting table and deleted top result "OC" - then visualized it with ggplot to give a sense of absolute numbers. Total posts considered in this are 988, the word cloud only looks at the 98 most mentioned words/phrases. Let me know if you have got any questions/concerns! Source: almost 2 years ago

Go to monkeylearn.com and sign up for a free demo. Then cut and paste your blog text into the extractor/classifier. Source: almost 2 years ago

Here is one library that will be used for the training https://fasttext.cc/ this allows for the consensus across multiple languages so that we can define our mystery word correctly. Source: over 2 years ago

(response to edit) > The classification problem is interesting though. I ended up with a long list of hundreds of topics. Most articles fall in two or more. There's also a sub-problem of clustering news by subject. Yeah, certainly difficult. I'm doing it partially manually right now but also with fastText[1]. I'd like to switch completely to fastText soon though since more often than not the newsletters I add... - Source: Hacker News / almost 3 years ago

I'm planning to build a business on this, so probably won't open-source it--but I'm always looking for interesting things to write about! I write a weekly newsletter called Future of Discovery[1]; I might write up some more implementation details there in a week or two. In the mean time, most of the heavy lifting is done by the Surprise python lib[2]. It's pretty easy to play around with, just give it a csv of... - Source: Hacker News / almost 3 years ago

FastText is a Facebook tool that, among other things, is used to train text classification models. Unlike Tensorflow.js, it is more intended to work with text so we don't need to pass a tensor and we can use the text directly. Training a model with it is much faster and there are fewer hyperparameters. Besides, to use the model from the browser is possible through WebAssembly. So it's a good alternative to try.... - Source: dev.to / almost 3 years ago