Neuronal morphology preparation and classification using Machine Learning.
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Updated
Jul 5, 2024 - Python
Neuronal morphology preparation and classification using Machine Learning.
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A scikit-learn compatible hyperbox-based machine learning library in Python
In simpler words we tell whether a user on Social Networking site after clicking the ad’s displayed on the website,end’s up buying the product or not. This could be really helpful for the company selling the product. Lets say that its a car company which has paid the social networking site(For simplicity we’ll assume its Facebook from now on)to …
In this project we propose a solution for human gesture classification using Deep Learning models, meant to be useful for non-verbal comunication between humans and robots. We have created a human body gesture dataset using a MediaPipe pose tracking solution in order to train the main model of this work.
A tool to support using classification models in low-power and microcontroller-based embedded systems.
Alignment-free bacterial identification and classification in metagenomics sequencing data using machine learning
In this project, we embark on an exciting journey to explore and analyze customer churn within the Telecom network service using the CRISP-DM (Cross-Industry Standard Process for Data Mining) framework.
Exploring various machine models using sklearn
Paper examining the effectiveness of various classification models in matching rap song lyrics to corresponding artists
Whole-body magnetic resonance image classification using deep learning models in PyTorch
Quick image classification model designed to tell the difference between an airplane, boat, or a car that was trained on hundreds of images!
Machine learning example code in topics such classification, clustering and recommender systems in different techniques and approaches.
Implementação de um modelo de aprendizado de máquina para classificação de pokémons por tipo, utilizando Árvore de Decisão como algoritmo base.
COBRA for Classification tasks on Imbalanced Data
A graphical machine learning program written with tkinter and scikit-learn library.
Classifying images of fruits and vegetables. Final model has 96.11% accuracy.
A comprehensive set of programs demonstrating machine learning techniques have been made.
Repo to hold all the programs i write while learning machine learning skills
Easily generate synthetic data for classification tasks using LLMs
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