classification

Projet personnel de classification des maladies des feuilles d'arbre. Article technique disponible sur mon blog : https://boulayc.gitlab.io/blog/

Egg classification using PyTorch using ResNet50 and AlexNet

Library and tools for similarity measurement, classification and clustering of digital content and segmentation images from digitized document

A landcover classification tool based for humans. Classifier does "traditional" supervised and unsupervised learning. Image segmentation and soon also object detection

Compute phylogenetic trees from distance matrix using BioNJ algorithm. It will produce Newick file and Weighted newick if needed. There is also a render using Equal-angle algorithm and SVG output for testing. It's preferred to use a JS render like 'phylotree.js' (demo of phylotree.js here http://phylotree.hyphy.org/).

Repository to store train coffee diseases classification code

Using Natural Language Processing (NLP) on job ads for applications in Econometrics.

This project explores the application of Support Vector Machines (SVM) in classifying human cell records to predict the malignancy of breast cancer samples. By training an SVM model on a dataset of breast cancer features, the goal is to accurately differentiate between benign and malignant cases. This research aims to contribute to the development of early detection and diagnosis methods for breast cancer.

A Live Evaluation of Computational Methods for Metagenome Investigation

An example of tabular data regression (parameter estimates) using TabNet

Evaluación de distintos modelos para clasificar aguas entre potables y no potables

Generates a model predicting substrate class (rock, mixed, sand, or mud) using random forest and a stack of environmental predictors. Model is tested against withheld testing observations. Model can be run using a 1-step or 2-step approach. The 2-step approach generates a binary rock/not-rock layer and a mixed/sand/mud layer and the two are combined. This approach was created to reduce the prevalence of predicted rock in the output raster. Substrate index layers (densities per class) can also be produced.

My attempts to solve homework from the Moscow Institute of Physics and Technology course

Collection of completed data-mining (university course) on python

Propaganda Detection in Arabic Social Media Text

[mirror] Attributes about whether foods are vegan/vegetarian for the USDA FDC FoodData database | https://v3gtb.github.io/fooddata-vegattributes/