MNIST Softmax regression implemion using only pure Python

Sentiment analysis on tweets about covid19 vaccinations with different methods.

Face detection and recognition into 6 classes of some famous personalities.

The softmax function  or normalized exponential function  is a generalization of the logistic function to multiple dimensions. In this example (X is weight, Y is height) where (0,0) is top left corner.

Implementation of classic machine learning concepts and algorithms from scratch and math behind their implementation.Written in Jupiter Notebook Python

Work on Bayesian growth mixture models including hidden Markov chains and softmax regressions for representing latent class memberships.

Using advanced deep learning techniques on the MNIST dataset. Over 98% validation set accuracy.

including Softmax Regression, Neural Network (regularized), KNN, LDA

Spring 2021 Machine Learning (CS 181) Homework 2

This repository is a compilation of machine learning algorithms implemented by me on differnet datasets and I'm currently working on it. The algorithms are categorized based on the types of data they are designed to handle and some of the codes are just a basic descriptions about the algorithms.

Deep Learning basics in Python using NumPy, PyTorch, and TensorFlow/Keras: linear regression, softmax regression, multilayer perceptron, etc.

Handwritten digit classification systems

A softmax regression model to classify images as neutral or smiling by different facial expressions.

Projects for Knowledge Engineering class (BIT北理工, NLP, 知识工程)

Implementation of multinomial logisitic regression, Weighted Logistic Regression, Bayesian Logistic Regression, Gaussian Generative Classification and Gaussian Naive Bayes Classification from scratch in MATLAB

Tensorflow simple project using MNIST dataset and softmax-regression

Softmax Regression from scratch. MNIST dataset

Statistical Pattern Recognition (classic machine learning)