3D Medical image segmentation with transformers tutorial
Implement a UNETR to perform 3D medical image segmentation on the BRATS dataset
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Artificial Intelligence
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Best AI and Deep learning books to read in 2022
A list of the top books to learn deep learning divided into four distinct categories. Personal reviews are included for each one of them.
Neural Architecture Search (NAS): basic principles and different approaches
Explore what is neural architecture search, compare the most popular,SOTA methodologies and implement it with nni
Neural Architecture Search (NAS): basic principles and different approaches Read More »
Understanding Maximum Likelihood Estimation in Supervised Learning
This article demystifies the ML learning modeling process under the prism of statistics. We will understand how our assumptions on the data enable us to create meaningful optimization problems.
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Best Graph Neural Network architectures: GCN, GAT, MPNN and more
Explore the most popular gnn architectures such as gcn, gat, mpnn, graphsage and temporal graph networks
Best Graph Neural Network architectures: GCN, GAT, MPNN and more Read More »
Understanding SWAV: self-supervised learning with contrasting cluster assignments
A mathematical explanation of the Swapping Assignments Between Views (SWAV) paper.
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A complete Weights and Biases tutorial
Learn about the Weights and Biases library with a hands-on tutorial on the different features and visualizations.
Grokking self-supervised (representation) learning: how it works in computer vision and why
A general perspective on understanding self-supervised representation learning methods.
Speech Recognition: a review of the different deep learning approaches
Explore the most popular deep learning architecture to perform automatic speech recognition (ASR). From recurrent neural networks to convolutional and transformers.
Speech Recognition: a review of the different deep learning approaches Read More »
Deep learning on computational biology and bioinformatics tutorial: from DNA to protein folding and alphafold2
A self-complete guide for understanding biology concepts that are necessary for applying deep learning in biology and bioinformatics focused on protein folding and alphafold2 related stuff