machine-learning-coding-homeworks's Introduction

Machine Learning and Deep Learning course coding Homeworks NYCU Taiwan

Image Recognition using Convolutional Neural Network
Dataset MNIST and CIFAR10
Showing correctly classified and miss classified Images
Displaying 9 feature maps per convolutional layer
Effect of L2 Regularization on overfittng and accuracy
Building a recurrent neural network for character-level language model
Recurrent neural network (RNN) for word generation using character-level language model
Long short term memory (LSTM) for word generation using charater-level language model
Shakespeare dataset
Regression using Neural Network with 2 Hidden Layers from scratch
Classification using Neural Network with one Hidden layer from scratch
Regularized linear regression (polynomial basis) using LSE and Newton's method and visualization
MNIST Digit classification using Naive Bayes that support discrete and continous feature of MNIST data
Online learning to learn the beta distribution of the parameter p (chance to see 1) of the coin tossing trails in batch
Random Data Generator
Sequential Estimator
Baysian Linear regression
Support Vector Machine to tackle classification of MNIST data using LIBSVM library
kernel functions used (linear, polynomial, and RBF kernels)
Find out support vectors using 2D Dataset
Implementation of k-means clustering, kernel k-means, spectral clustering, DBSCAN using Numpy from scratch
Dataset: 2 datasets with points on 2d space, circle.txt and moon.txt
Different ways to do dimension reduction on MNIST data using PCA, LDA, S-SNE and T-SNE
Use PCA to show the first 25 eigenfaces using att_faces dataset
Logistic Regression from scratch
Random data generator
EM Algorithm from scratch
Dataset: MNIST Data

Recommend Projects