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Stars1
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LanguageJupyter Notebook
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Created over 3 years ago
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Data-Generation-with-Blender
Step-by-step tutorial on how to create data with Blender for an object detection application, with ressources included.Evaluating-w-Embeddings
In this paper we compare and evaluate two simple embedding models which can be constructed directly from a given co-occurrence matrix extracted from Twitter data; Positive Pointwise Mutual Information (PPMI), and Hellinger Principal Component Analysis (H-PCA). For each embedding model we consider three alternative metrics for word similarity: cosine, euclidean and manhattan distance.SVM-LR-on-Fashion-MNIST
This is a brief tutorial on using Logistic Regression and Support Vector Machines for classification on the Fashion MNIST dataset.PCA-on-Fashion-MNIST
This is a concise tutorial on applying PCA in the benchmark dataset Fashion MNIST. I analyse how the data compression process is done in visual information.Regularization-techniques-on-NNs
During this study we will explore the different regularisation methods that can be used to address the problem of overfitting in a given Neural Network architecture, using the balanced EMNIST dataset.BoVW-ResNet18-Robustness-Evaluation
The aim of this project is to explore the classification of images using a ResNet18 Convolutional Neural Network and a Bag of Visual Words (BoVW) method that uses Support Vector Machines (SVM) on a dataset that contains 1200 224 x 224 images of cats and dogs.Love Open Source and this site? Check out how you can help us
