In this tutorial, I will elaborate how got I started on the Credit Card Fraud Detection competition on Kaggle. The goal of the task is to automatically identify fraudulent credit card transactions using Machine Learning. My Pythonic approach is explained step-by-step.
You want to build your own Tic-Tac-Toe opponent? Then you need to read further! In the Tic-Tac-AI series, I will present a couple of Artificial Intelligence algorithms implemented as Tic-Tac-Toe opponent. In this first article, I will introduce a method called Forward Sampling which is capable of not losing any game of Tic-Tac-Toe!
How can we use machine learning to predict stockprices? In this tutorial we will make Python scripts for doing sentiment analysis on Tweets and it is explained how to use it for making predictions.
As an example, suppose we had €1000,- at the first of January of 2014 and suppose we could use the algorithm which is described in this tutorial. Then it would generate €2901,- in total on the 22th of February, 2017! The total amount of money (cash + investments) is shown in the next figure:
Despite the patience you need to have, it will be worth the waiting time eventually. As mentioned in , moods in tweets are a good indication of the movement of closing prices on a stock market. In this article, we will only predict how positive or how negative a tweet is. But it turns out that this is giving predictive signals which is accurate enough for our purposes.
Disclaimer: this post is in Dutch. If you would like to obtain a translation of this article, feel free to ask me.
Het zijn gunstige tijden voor huizenkopers, de huizenprijzen zijn laag. Het grote probleem voor starters is dat banken niet veel risico durven te nemen en daardoor relatief lage hypotheken verstrekken. In dit artikel probeer ik het huidige hypotheeksysteem (augustus 2016) van de Rabobank te doorgronden. Is het systeem wel eerlijk? (more…)
There are lots of Python packages available on the internet. The aim of this post is to give you an overview of scientifically oriented Python packages, sorted per topic. The list will be updated regularly. If you have any recommendations, feel free to give your addition in the comments!
- NumPy – Powerful computational framework.
- pandas – Data structures and data analysis.
- matplotlib – Plotting and visualization tools.
- SymPy – For working with symbolic mathematics.
- Numba – High performance mathematical toolkit.
- emcee – Monte Chain Monte Carlo sampling.
- Scikit image – Image processing toolkit.
- IPython – An interactive shell.
- Anaconda – A bundle of the most used Python libraries.
- SciPy – A bundle of the most used scientific Python libraries.