Hands-on Tutorials

A tutorial on how to tackle downstream ML tasks on data represented in a Knowledge Graph.

Table of contents

Representing Data With Knowledge Graphs

A write-up of the fourth place solution to the Kaggle OpenVaccine competition

A write-up on how we almost won the “University of Liverpool — Ion Switching” Kaggle competition

Mining discriminative walks with MINDWALC

1. A richer data representation with (Knowledge) Graphs

How we obtained ranking 16/204 in Belgium and 531/10724 globally

Google Hash Code

Scanning books in multiple libraries

How a neat simple trick can boost both predictive performance and interpretability.

Timeseries classification

Detecting the surface where a robot (Sony AIBO) is walking on using the X-axis of the accelerometer data. Image taken from http://www.timeseriesclassification.com/description.php?Dataset=SonyAIBORobotSurface1


A write-up on how we obtained a silver medal in the “Santa’s Workshop Tour 2019” competition organized by Kaggle

Problem definition

Elaborating upon the most important aspects encountered during the development of a platform for an AI competition.

How a simple heuristic based on path-finding found a path towards the top-tier on the leaderboard.

A more advanced implementation of the game Tron, called Armagetron

On bit operations, alpha-beta pruning and hard-coding initial game states to create a very strong AI agent for connect four.

def generate_move(board, player, saved_state):
"""Contains all code required to generate a move,
given a current game state (board & player)
Args: board (2D np.array): game board (element is 0, 1 or 2)
player (int): your plabyer number (float)
saved_state (object): returned value from previous call

Gilles Vandewiele

Data Scientist || Kaggle Master

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