iNeuron.ai internship project: Mushroom Classification using Ensemble Machine Learning Models and Streamlit Deployment
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Updated
Jul 14, 2024 - Jupyter Notebook
iNeuron.ai internship project: Mushroom Classification using Ensemble Machine Learning Models and Streamlit Deployment
Proyecto de análisis y detección de hongos venenosos vs comestibles con ML.
This project aims to accurately classify mushrooms as either poisonous or non-poisonous using supervised machine learning techniques.
Apply machine-learning models on mushroom data to predict if a mushroom is edible or not
An Android App for Image-Classification / Mushroom-Classification based on Pictures.
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.
Flask & Keras project for forest mushrooms classification
Playground with mushrooms for testing divide and conquer algorithm that learns decision trees.
Mushroom Classification Analysis using Machine Learning
Implementation of a neural network for solving the problem of mushroom classification based on the TensorFlow library and the pre-trained efficientnet/b0 model.
Drying mushrooms is one of the most popular ways of mushroom preservation. Dried mushrooms can be stored for an extended period of time and used in a variety of recipes. Additionally, preserving mushrooms through freezing or canning can also be effective techniques for long-term storage.
Project for Intro to Data Mining course, where the goal is to classify a mushroom as poisonous or edible.
Capstone project for WGU's Computer Science program.
CAN YOU EAT IT is a web application that allows users to identify fungi by location & season.
Machine Learning assignments, Machine Learning (IE500618) course, fall 2022.
Detect the poisonous mushroom using its physical characteristics
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