BrscnTnl

Beerwulf.Data.Assessment

DropBoxPP

asdaw

first_streamlit_app

MSc_1_ArtificialIntelligence_HW1_Search

Application of Search Algorithms on 8-Puzzle

MSc_1_ArtificialIntelligence_TermProject_SLP

Wine Quality Prediction with Single Layer Neural Network

MSc_3_MachineLearning_HW1_NaiveBayes

The aim of the dataset is to predict the age of abalone from physical measurements. Originally it is a regression problem in which the output is age in years. However, we will use it as a classification problem. The age value is discretized as young, middle-aged, and old. The dataset (input features and class labels of the samples) are provided as a seperate text file (abalone_dataset.txt).

MSc_3_MachineLearning_TermProject_KNN

Parkinson classification using K-NN from UPDRS

MSc_4_ArtificialNeuralNetworks_HW1_MLP

Train a multilayer perceptron (MLP) with 12 inputs, one output and H hidden units. Forest Fire Data

MSc_4_ArtificialNeuralNetworks_HW2_RBF

BrscnTnl/MSc_1_ArtificialIntelligence_TermProject_SLP

Wine Quality Prediction with Single Layer Neural Network

BrscnTnl/MSc_3_MachineLearning_TermProject_KNN

Parkinson classification using K-NN from UPDRS

BrscnTnl/Beerwulf.Data.Assessment

BrscnTnl/DropBoxPP

asdaw

BrscnTnl/first_streamlit_app

BrscnTnl/MSc_1_ArtificialIntelligence_HW1_Search

Application of Search Algorithms on 8-Puzzle

BrscnTnl/MSc_3_MachineLearning_HW1_NaiveBayes

The aim of the dataset is to predict the age of abalone from physical measurements. Originally it is a regression problem in which the output is age in years. However, we will use it as a classification problem. The age value is discretized as young, middle-aged, and old. The dataset (input features and class labels of the samples) are provided as a seperate text file (abalone_dataset.txt).

BrscnTnl/MSc_4_ArtificialNeuralNetworks_HW1_MLP

Train a multilayer perceptron (MLP) with 12 inputs, one output and H hidden units. Forest Fire Data

BrscnTnl/MSc_4_ArtificialNeuralNetworks_HW2_RBF