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Based on our record, monkeylearn should be more popular than Gnome Pomodoro. It has been mentiond 11 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
Https://gnomepomodoro.org/ there's a menu for summarying all your time working. Source: about 1 year ago
Https://gnomepomodoro.org/ used this a couple of times, with time spent daily/weekly/montly, pretty simple I like it. Source: about 1 year ago
Not into Pomodoro myself, but have come across Gnome Pomodoro. Source: over 1 year ago
If you then go into the terminal, and run sudo dnf install gnome-pomodoro, you will install the actual GNOME Pomodoro. (By the way, as a sidenote, you must login, log back in, and enable the Extension if you want GNOME Pomodoro to work.). Source: over 2 years ago
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
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