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

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

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

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)

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 various Machine Learning Algorithms and Machine Learning Concepts in Python

data science endeavour

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.

Nicole Cruz Portfolio

Scalable sparse linear models in Python

machine learning using python language to implement different algorithms

Different machine learning approaches on classifying customers who are most likely to purchase an offer. Made with Jupyter Notebook, scikit-learn, and other helpful python packages.

ML models built from scratch in Python 3.9.13

Laboratory works on Methods of Artificial Intelligence course