MLJAR's Blog

  • Validation - Learning, Not Memorizing

    October 17, 2018 by Paweł Grabiński Validation Overfit

    In business and science alike, while conducting some processes, it is always necessary to measure efficiency and quality. When it comes to the financial deals, the situation is simple. Income either in short or in long term is the way to go. But what about Machine Learning? To measure the quality of a developed model, we use the process of validation which ensures that we are moving forward in our search for the efficiency and the optimal capacity.

  • AutoML comparison

    December 07, 2017 by Piotr Płoński Compare

    Automated Machine Learning (autoML) is a process of building Machine Learning models by the algorithm with no human intervention. There are several autoML packages available for building predictive models:

  • Churn Prediction with AutoML

    September 27, 2017 by Dominik Krzemiński Automl

    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.

  • Are hyper-parameters really important in Machine Learning?

    August 22, 2017 by Dominik Krzemiński Hyperparameters

    Look at some titles of recent questions posted on Quora or Stack Overflow:

  • Employee Analytics

    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.

  • Machine Learning Wars

    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.

  • Predict stock market on AI tournament (numer.ai)

    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_COM is doing really well!