Sometimes we don’t even realize how common machine learning (ML) is in our daily lives. Various “intelligent” algorithms help us for instance with finding the most important facts (Google), they suggest what movie to watch (Netflix), or influence our shopping decisions (Amazon). The biggest international companies quickly recognized the potential of machine learning and transferred it to business solutions.
September 27, 2017 by Dominik Krzemiński Automl
August 22, 2017 by Dominik Krzemiński Hyperparameters
Look at some titles of recent questions posted on Quora or Stack Overflow:
May 19, 2017 by Piotr Płoński Employee analytics
The analytic methods can improve Human Resources (HR) management for companies with large number of employees. It is very easy to give example, how can companies benefit from machine learning methods applied to HR. Let’s assume that training of new employee costs 1000$ and if we can predict which employee is going to leave next month, and propose him/her a bonus program worth 500$ to keep him for next 6 months, we are 500$ on plus and keep experienced, well-trained employee under the hood, with higher morale.
December 12, 2016 by Piotr Płoński Compare
Herein the performance of MLJAR on Kaggle dataset from “Give me some credit” challenge is reported. The obtained results are compared with other predictive APIs from Amazon, Google, PredicSis and BigML. This post was inspired with Louis Dorard’s article.
September 28, 2016 by Piotr Płoński
The data and machine learning models used by hedge funds are secret. However, there is one hedge fund which makes its data public - Numer.ai. The dataset is encrypted and prediction of stock market is transformed into binary classification problem. Every 7 days (one round) a new dataset is released and anyone can download it, train model and upload predictions. At the end of the round, the best predictions are rewarded - there is no need to upload the model. As you can see from the leaderboard,
MLJAR_COMis doing really well!