Home 2017-09-13T02:40:09+00:00
2903, 2018

Building a Content-Based Search Engine III: Feature Signatures

March 29th, 2018|Categories: Data Mining, Machine Learning|

This is part 3 in a series of tutorials in which we learn how to build a content-based search engine that retrieves multimedia objects based on their content rather than based on keywords, title or meta description. Part I: Quantifying [...]

803, 2018

Building a Content-Based Search Engine II: Extracting Feature Vectors

March 8th, 2018|Categories: Data Mining, Machine Learning|

This is part 2 in a series of tutorials in which we learn how to build a content-based search engine that retrieves multimedia objects based on their content rather than based on keywords, title or meta description. Part I: Quantifying [...]

2402, 2018

Building a Content-Based Search Engine I: Quantifying Similarity

February 24th, 2018|Categories: Data Mining, Machine Learning|

This is part 1 in a series of tutorials in which we learn how to build a content-based search engine that retrieves multimedia objects based on their content rather than based on keywords, title or meta description. Part I: Quantifying [...]

911, 2017

Deep Learning From Scratch VI: TensorFlow

November 9th, 2017|Categories: Artificial Intelligence, Deep Learning, Machine Learning, Python, TensorFlow|

This is part 6 of a series of tutorials, in which we develop the mathematical and algorithmic underpinnings of deep neural networks from scratch and implement our own neural network library in Python, mimicing the TensorFlow API. Start with the first [...]

2410, 2017

Connectionist Models of Cognition

October 24th, 2017|Categories: Artificial Intelligence, Cognitive Science, Computational Cognitive Modeling, Deep Learning, Machine Learning|

In this video, I give an introduction to the field of computational cognitive modeling (i.e. modeling minds through algorithms) in general, and connectionist modeling (i.e. using artificial neural networks for the modeling) in particular. We deal with the following topics:The purpose [...]

410, 2017

Robot Localization IV: The Particle Filter

October 4th, 2017|Categories: Artificial Intelligence, Machine Learning, Robotics, Self-Driving Cars|

This is part 4 in a series of articles explaining methods for robot localization, i.e. determining and tracking a robot's location via noisy sensor measurements. You should start with the first part: Robot Localization I: Recursive Bayesian Estimation The last [...]

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