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.

MNIST Softmax regression implemion using only pure Python

Sentiment analysis on tweets about covid19 vaccinations with different methods.

Multiclass classification by logistic regression and softmax regression

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

Classic methods on digit recognition. As part of the MITx course on machine learning with Python - from linear models to deep learning

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

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.

CS224n : Natural Language Processing with Deep Learning Assignments, Winter 2017, Stanford University.

Applied Machine Learning (COMP 551) Project

Tensorflow simple project using MNIST dataset and softmax-regression

Softmax Regression from scratch. MNIST dataset

Statistical Pattern Recognition (classic machine learning)

Handwritten digit classification systems