My workshop on machine learning using python language to implement different algorithms

PyTorch implementation of 'CLIP' (Radford et al., 2021) from scratch and training it on Flickr8k + Flickr30k

Official implementation of Highly Scalable and Provably Accurate Classification in Poincaré Balls (ICDM regular paper 2021)

A software package for large-scale linear multilabel classification.

This repository contains a PyTorch implementation for classifying the Oxford IIIT Pet Dataset using KNN and ResNet. The goal is to differentiate the results obtained using these two approaches.

Implementation of the perceptron algorithm on MATLAB for classification

Text classification with Machine Learning and Mealpy

Linear classification problem with tensorflow (Using LNNClassifier and DNNClassifier)

Implementation of various Machine Learning Algorithms and Machine Learning Concepts in Python

Con clasificación lineal podemos categorizar datos a partir de observaciones previas. Sus implementaciones va desde la detección de fraudes a segmentizar clientes. Acá te explico desde un punto matemático y teórico como se aplica. Además, hacemos una pequeña implementación.

Implementation of a Simple Perceptron (Simplest Neural network by Frank Rosenblatt) in C based on the example given example in the Veritasium video.

Machine Learning Algortihms from scratch.

A Chinese guide book for learning Tensorflow from a starter.

data science endeavour

Lung Cancer Detection Using Machine Learning Methods

This project detects digits using CNNs and OpenCV. It includes image preprocessing, model training on MNIST, real-time detection, and evaluation with accuracy metrics. Built with Python, TensorFlow/Keras, and Flask for deployment. Clone, install dependencies, and start detecting digits! 🚀

machine learning using python language to implement different algorithms

Nicole Cruz Portfolio

Scalable sparse linear models in Python

Bengaluru House Price Prediction using Python (Scikit-Learn, Pandas, NumPy, Matplotlib, Seaborn). Machine learning predicts prices based on features like location, size, and bathrooms. Data preprocessing, Ridge Regression model, and evaluation metrics ensure accurate predictions. Clone, install, and run the script for precise Bengaluru house prices