INM431-Machine Learning

a particular suggestion for NB: initially a hyperparameter optimizer can be used to indicate the best distribution parameters. Following this a number of models can be built by modifying the following parameters: distribution types, smoothing type for the kernel density estimate, smoothing width for the kernel density estimate, priors use for the PDF estimates;
a particular suggestion for LR: exploring Ridge and Lasso regularisation methods, comparing fitting and not fitting an intercept, or bias; optionally, could also vary the learning rate

INM427-Neural Computing

Compared image classification performance between Support Vector Machine (SVM) and Multi Layer Perceptron (MLP) along with a brief comparison with Convolutional Neural Network (CNN)

Name		Name	Last commit message	Last commit date
Latest commit History 43 Commits
Final Project		Final Project
01-Neural Networks in One Dimension.ipynb		01-Neural Networks in One Dimension.ipynb
01-activation-functions.ipynb		01-activation-functions.ipynb
01-perceptron-in-numpy.ipynb		01-perceptron-in-numpy.ipynb
02-single-layer-neural-network-for-binary-classification.ipynb		02-single-layer-neural-network-for-binary-classification.ipynb
03-KMeans-Example-with-Scikit-Learn.ipynb		03-KMeans-Example-with-Scikit-Learn.ipynb
03-MNIST-Example-with-TensorFlow.ipynb		03-MNIST-Example-with-TensorFlow.ipynb
03-PCA-Example-with-Scikit-Learn.ipynb		03-PCA-Example-with-Scikit-Learn.ipynb
Ch1 Expectations and covariances.ipynb		Ch1 Expectations and covariances.ipynb
Ch1 Probability Theory.ipynb		Ch1 Probability Theory.ipynb
Pre Maths session part2.JPG		Pre Maths session part2.JPG
README.md		README.md
Tutorial1_Some tips for task 1.png		Tutorial1_Some tips for task 1.png
W2_Curve Fitting.ipynb		W2_Curve Fitting.ipynb
W2_Tutorial2.m		W2_Tutorial2.m
W3_Bayesian Inference.ipynb		W3_Bayesian Inference.ipynb
W3_Loss Functons.ipynb		W3_Loss Functons.ipynb
W3_LossfunctionEx.m		W3_LossfunctionEx.m
W3_Objective Function.ipynb		W3_Objective Function.ipynb
W3_Tutorial3study.ipynb		W3_Tutorial3study.ipynb
W3_bayescodestudyEx.m		W3_bayescodestudyEx.m
W4_Tutorial4.m		W4_Tutorial4.m