Topic: "mnist-classification-logistic"
harismuneer/Handwritten-Digits-Classification-Using-KNN-Multiclass_Perceptron-SVM
🏆 A Comparative Study on Handwritten Digits Recognition using Classifiers like K-Nearest Neighbours (K-NN), Multiclass Perceptron/Artificial Neural Network (ANN) and Support Vector Machine (SVM) discussing the pros and cons of each algorithm and providing the comparison results in terms of accuracy and efficiecy of each algorithm.
Language: Python - Size: 13 MB - Last synced at: about 2 months ago - Pushed at: 6 months ago - Stars: 62 - Forks: 18

ibodumas/logistic_regression
This project involves the implementation of efficient and effective Logistic Regression (FROM SCRATCH) classifiers on MNIST data set. The MNIST data comprises of digital images of several digits ranging from 0 to 9. Each image is 28 x 28 pixels. Thus, the data set has 10 levels of classes.
Language: Jupyter Notebook - Size: 10.5 MB - Last synced at: 17 days ago - Pushed at: over 7 years ago - Stars: 2 - Forks: 2

ArunSehrawat/Image_classification_with_CNN_and_QNN
Language: Jupyter Notebook - Size: 407 KB - Last synced at: about 2 years ago - Pushed at: about 2 years ago - Stars: 1 - Forks: 0
