Deep Similarity Learning & Siamese Networks

In this project, I explored deep similarity learning algorithms and their behaviour with different type of data (sequential data, spatial data, multimodal data). For each of these different modalities, I wrote 2 Medium articles detailing the retained method and providing my implementation.

Time Series Land Cover Challenge: a Deep Learning Perspective

In this project, I explored a Time Series of satellite images dataset by building different deep learning classifiers, finding inspiration in paper research in the field of Time Series classification.

Segmentation Models on artificial moon imagery

In this project, I trained 4 DL segmentation models on an artificial Lunar Dataset to see how they will perform on real moon images from Nasa.

Improving Deep Neural Networks

This course taught me the ‘magic’ of getting deep learning to work well. Rather than consider the DL process as being a black box, I learnt what drives performanceeee

Machine Learning

During this course, I studied Machine Learning starting with both supervised (Regression, Classification) and unsupervised learning (Dimension reduction..)