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

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.

A software package for large-scale linear multilabel classification.

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.

A Chinese guide book for learning Tensorflow from a starter.

Machine Learning Algortihms from scratch.

Nicole Cruz Portfolio

Scalable sparse linear models in Python

Laboratory works on Methods of Artificial Intelligence course

This repository is my learning and practice of of essential concepts and framework-techniques for Data Science and Machine Learning.

This Repository Contains all the Information and the Projects that I did at SAIL during my Internship

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.