New Keyword Extraction: smarter and more flexible

We are excited to announce that we have made several improvements to our Keyword Extraction. You can try it for free here, you just need a MonkeyLearn account.

This module extracts keywords from text in English. Keywords can be compounded by one or more words and are defined as the important topics in your content and can be used to index […]

By |May 20th, 2015|News|0 Comments

Hacker News categorizer with MonkeyLearn

We are big fans of Hacker News here at MonkeyLearn. We read HN on a daily basis, but not all of us have the same interests; some are more interested news related to programming, and others are more interested in news related to startup and business.

So, what if we can read Hacker News but only see relevant news related […]

By |April 27th, 2015|How To|4 Comments

Analyzing news headlines across the globe with Kimono and MonkeyLearn

Contributed by Pratap Ranade, co-founder at Kimono Labs.

The news is probably one of the first things you check in the morning, but how much does what you know and understand about the world depend on your news source? Will you view the world differently if you head over to CNN instead of BBC? Tools like […]

By |April 17th, 2015|How To|6 Comments

New modules: Product Sentiment Analysis & Extractors

We are excited to announce some new cool public modules for MonkeyLearn: product sentiment analysis, keywords extraction and entity extraction. These modules are pre-trained by the MonkeyLearn team and ready to use modules by developers on their apps and platforms.

You can try these modules by login on your MonkeyLearn account and going to your dashboard.
Product […]

By |March 26th, 2015|News|0 Comments

MonkeyLearn at PyCon Startup Row’s event

On March 12 we had the amazing opportunity to pitch MonkeyLearn to a big crowd at PyCon Startup Row’s event. It was a very fun night held at Yelp’s office in Downtown SF and part of a SF Python Meetup.

We had 5 minutes to explain the product and give the pitch with more monkeys per Slide ratio known […]

By |March 19th, 2015|News|0 Comments

MonkeyLearn was featured in Twitter Dev Blog

Wondering how did we created this Twitter profiling demo?

Twitter did also. We were invited to write a Blog post on Twitter Developers Blog. The idea was to easily explain how to profile Twitter users using MonkeyLearn based on the bios of the people they follow and their related tweets. Using this profiling techniques Companies […]

By |March 6th, 2015|News|0 Comments

Kimono + MonkeyLearn: sentiment analysis with machine learning and web scraped data

Update May 2016: Kimono has been adquired by Palantir and its cloud service has been discontinued. We have made a new post covering how to create a hotel reviews sentiment analysis model with Scrapy and MonkeyLearn, check it out here. 

New tools have enabled businesses of all sizes to understand how their customers are reacting to them – […]

By |December 17th, 2014|How To|6 Comments

How to Create an Employment Analytics Visualization in Less Than 10 Minutes

Ever wondered which city has the most high tech jobs? Or recruitment openings? Will your career be better off in NYC or SF? Turns out you can answer these and many more questions by doing some simple data analysis. Using three awesome free tools (, MonkeyLearn and you can obtain, categorize and visualize […]

By |December 12th, 2014|How To|6 Comments

Black Friday at MonkeyLearn: 80% off in every new subscription plan

It’s Black Friday at MonkeyLearn!

We are joining our friends at who created an amazing data deal bundle. As part as this initiative, we are offering a huge Black Friday deal:

Discount: 80% off in every new subscription plan for the first 3 months.
We believe this could be great value for MonkeyLearn users! For example, if […]

By |November 28th, 2014|News|0 Comments

[GUEST POST] AngularJS provider for MonkeyLearn

Editor’s note: this is a guest blog post by Josué G. Gutiérrez, a full stack developer, an angularJS Lover and a NLP Enthusiastic. You can find him on Twitter @eusoj.

Startups, tech companies and academia are working really hard to solve problems related to the understanding of language (and the interaction between each of its […]

By |October 23rd, 2014|News|0 Comments