About Bruno Stecanella

Engineering student and primate enthusiast. I write code and blog about monkeys. Sometimes about other stuff, too.

Analyzing customer support interactions on Twitter with Machine Learning

We are seeing new trends in customer support. Some companies are starting to have a different social media appearance, trying to appear more hip and cool (probably actual words used by executives). Instead of making their social media managers behave in a professional servile-like fashion, these companies opt instead to communicate in a more […]

By |October 5th, 2017|Applications|0 Comments

Getting started with Python & Machine Learning

Machine learning is eating the world right now. Everyone and their mother are learning about machine learning models, classification, neural networks, and Andrew Ng. You’ve decided you want to be a part of it, but where to start?

In this article we’ll cover some important characteristics of Python and why it’s great for machine learning. […]

By |August 3rd, 2017|News|0 Comments

An introduction to Support Vector Machines (SVM)

So you’re working on a text classification problem. You’re refining your training set, and maybe you’ve even tried stuff out using Naive Bayes. But now you’re feeling confident in your dataset, and want to take it one step further. Enter Support Vector Machines (SVM): a fast and dependable classification algorithm that performs very well with a limited amount of data. […]

By |June 22nd, 2017|News|3 Comments

A practical explanation of a Naive Bayes classifier

The simplest solutions are usually the most powerful ones, and Naive Bayes is a good proof of that. In spite of the great advances of the Machine Learning in the last years, it has proven to not only be simple but also fast, accurate and reliable. It has been successfully used for many purposes, but it works particularly well with natural language processing (NLP) problems. […]

By |May 25th, 2017|News|20 Comments

Analyzing 10 years of startup news with Machine Learning

Analyzing startup news — part 3

This is the final part in a series where we use machine learning and natural language processing to analyze articles published in tech news sites in order to gain insights about the state of the startup industry. […]

By |May 11th, 2017|News|2 Comments

Creating machine learning models to analyze startup news

Analyzing startup news — part 2

This is the second part in a series where we analyze thousands of articles from tech news sites in order to get insights and trends about startups.

Last time around we scraped all the articles ever published in TechCrunch, VentureBeat and Recode using Scrapy. We then filtered out all the articles that weren’t about startups, […]

By |April 11th, 2017|How To|0 Comments

Filtering startup news with Machine Learning

Analyzing startup news — part 1

On this new post series, we will analyze hundreds of thousands of articles from TechCrunch, VentureBeat and Recode to discover cool trends and insights about startups.

What are the hottest industries for startups right now?
Do machine learning startups get more press than fintech startups?
What is the startup segment with most acquisitions?

These are the […]

By |March 13th, 2017|How To|0 Comments

Donald Trump vs Hillary Clinton: sentiment analysis on Twitter mentions

Election day looms closer and closer every week. US Politics are rapidly becoming the preferred conversation topic for millions of Americans and non-Americans worldwide. What are these people saying? What do they think? What are their opinions? How do they feel?

We are using machine learning to find out! For the past few months, we’ve […]

By |October 20th, 2016|Applications|13 Comments

Machine Learning over 1M hotel reviews finds interesting insights

Analyzing hotel reviews — Part 3

On a previous post we learned how to train a machine learning classifier that is able to detect the different aspects mentioned on hotel reviews. With this aspect classifier, we were able to automatically know if a particular review was talking about cleanliness, comfort & facilities, food, Internet, location, staff and […]

By |July 20th, 2016|How To|16 Comments

Aspect Analysis from reviews using Machine Learning

Analyzing hotel reviews — Part 2

Recently we walked you through on how to train a sentiment analysis classifier for hotel reviews using Scrapy and MonkeyLearn. This tutorial is a perfect example on how we can combine web scraped data and machine learning for discovering valuable insights about a particular industry.

With this model, we were able to analyze millions […]

By |May 19th, 2016|How To|0 Comments