🍄 Chat bot for recognizing edible mushrooms.
A machine-learning project to determine if a certain mushroom is edible or poisonous.
I explain how to export weights from a Keras model and import those weights in Keras.js, a JavaScript framework for running pre-trained neural networks in the browser. I show you later how to include the final result into a Phonegap Cordova mobile application.
Learn to use Support Vector Machines in Python(sklearn) and R
Classifies mushrooms as poisonous or edible using machine learning algorithms
Machine Learning Model to classify whether a Mushroom is Edible or Poisonous by its features
As eating healthy is on the rise, how do we know if we can safely enjoy our fabulous fungi? This repository uses machine learning and visualizations to help classify which are the most dangerous and should be avoided.
Naive Bayes and Decision Tree Classifiers implemented with Scikit-Learn and Graphviz visualization (Datasets - News, Mushroom, Income)
CAN YOU EAT IT is a web application that allows users to identify fungi by location & season.
A simple binary classification project which detects whether a mushroom is edible or not
This project aims to accurately classify mushrooms as either poisonous or non-poisonous using supervised machine learning techniques.
🍄 Extract logical rules for mushroom edibility: Neural Networks; Genetic Algorithm + Decision Tree
An Android App for Image-Classification / Mushroom-Classification based on Pictures.
Mushroom foraging can be risky, as certain species are highly toxic. This project leverages machine learning to classify mushrooms as edible or poisonous based on their features. The goal is to build an accurate classification model using modern data science techniques.
This project aims at developing a web application that uses a machine-learning algorithm and predict if a certain mushroom is edible or poisonous by its specifications like cap shape, cap color, gill color, etc.
A comprehensive guide, created in September 2023, for collecting and analyzing weather data from stations across the Appennino in Reggio Emilia and Modena. It provides tools for data acquisition, storage, and visualization, with a particular focus on identifying optimal meteorological conditions for mushroom hunting.
This repository aims to implement a mushroom type classifier using PyTorch, utilizing various models to enhance performance. Additionally, the project includes an analysis of the model's performance using Gradient-Class Activation Map (Grad-CAM) visualization.
Playground with mushrooms for testing divide and conquer algorithm that learns decision trees.
Classification model that predicts the class of mushroom (poisonous or edible) and prominent features that indicate poisonous mushrooms.
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