Machine Learning for your flat hunt. Part 1
9 min
Have you ever looked for a flat? Would you like to add some machine learning and make a process more interesting?
Contextual Emotion Detection in Textual Conversations Using Neural Networks
10 min
Nowadays, talking to conversational agents is becoming a daily routine, and it is crucial for dialogue systems to generate responses as human-like as possible. As one of the main aspects, primary attention should be given to providing emotionally aware responses to users. In this article, we are going to describe the recurrent neural network architecture for emotion detection in textual conversations, that participated in SemEval-2019 Task 3 “EmoContext”, that is, an annual workshop on semantic evaluation. The task objective is to classify emotion (i.e. happy, sad, angry, and others) in a 3-turn conversational data set.
How do you choose products in stores?
4 min
Translation
The most important single ingredient in the formula of success is knowing how to get along with people. Theodore Roosevelt
In the previous article I tried to cover the basics of pricing analytics. Now I'd like to talk about something more interesting.
Have you ever thought about why you choose certain products in stores, why you prefer them to other similar ones? Many shopping trips are spontaneous, so it's probably impossible to give a clear answer for all the times you go shopping. But the general idea is obvious: you go shopping for a specific reason (to get food, a gadget, for entertainment, to play blackjack). In this article I'm going to use available data from grocery retailers to talk about how a set of basic logical assumptions and community analysis can help us determine the way customers choose products.
A selection of Datasets for Machine learning
5 min
Hi guys,
Before you is an article guide to open data sets for machine learning. In it, I, for a start, will collect a selection of interesting and fresh (relatively) datasets. And as a bonus, at the end of the article, I will attach useful links on independent search of datasets.
Less words, more data.
Before you is an article guide to open data sets for machine learning. In it, I, for a start, will collect a selection of interesting and fresh (relatively) datasets. And as a bonus, at the end of the article, I will attach useful links on independent search of datasets.
Less words, more data.
A selection of datasets for machine learning:
- Data deaths and battles from the game of thrones — This data set combines three data sources, each based on information from a series of books.
- Global Terrorism Database — Over 180,000 terrorist attacks worldwide, 1970-2017.
- Bitcoin, historical data — Bitcoin data with an interval of 1 minute from selected exchanges, January 2012 — March 2019