A generative network for animal vocalizations. For dimensionality reduction, sequencing, clustering, corpus-building, and generating novel 'stimulus spaces'. All with notebook examples using freely available datasets.
ipython notebooks for learning how to use SimpleITK
Analytics and ML notebooks
TensorFlow (Keras) implementation of MobileNetV3 and its segmentation head
Notebooks of pre trained models using the HAM10000 dataset
Processing code and exploratory notebooks for BeetlePalooza dataset (2018 NEON Ethanol-preserved Ground Beetles).
Deeplearning (pytorch, transformers, GANs, BERT, RNNs)
This is a repository of my Google Colab notebooks for various machine/deep learning problems.
Backup for kaggle.com notebooks
セマンティックセグメンテーションを実装するためのデモ
Computer Vision Paper Reviews with Key Summary of paper, End to End Code Practice and Jupyter Notebook converted papers
Collection of notebooks for image segmentation tasks.
Unets notebook developed while I was working in NUS for multiclass 3D segmentation
This repository contains IPython Notebooks for Computer Vision tasks using OpenMMLab - MMDetection, MMSegemntation etc.
In this project, I will analyze a dataset containing data on various customers' annual spending amounts (reported in monetary units) of diverse product categories for internal structure. One goal of this project is to best describe the variation in the different types of customers that a wholesale distributor interacts with. Doing so would equip…
Este repositorio presenta una implementación de segmentación de mamas utilizando YOLOv8. La segmentación de mamas es crucial en el diagnóstico de cáncer de mama. El proyecto incluye un notebook detallado y una demostración desplegada para probar el modelo en tiempo real.
Wound healing analysis and segment the wound area
Jupyter Notebooks e codigos para analise de bioimagens e dados biologicos utilizados no meu canal BioPrograma - https://www.youtube.com/channel/UCbJAU7N9FYvwkdgSwD_1S4Q
This notebook provides a comprehensive example of how to perform customer segmentation using K-Means clustering, including data preprocessing, visualization, standardization, one-hot encoding, model training, evaluation, and saving/loading the model.
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