BU_CS542_Machine_Learning

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BU_CS542_Machine_Learning

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## BU CS542 Machine Learning

Instructor: Kate Saenko, Brian Kulis

### Introduction

This course is an introduction to modern machine learning concepts, techniques, and algorithms. Topics include regression, classification, unsupervised and supervised learning, kernels, support vector machines, feature selection, clustering, sequence models, and Bayesian methods. Weekly labs and projects emphasize taking theory into practice, through applications on real-world problems and data sets.

### Solutions

ps0:[Basic Mathematical Skills](https://github.com/guozhonghao1994/BU_CS542_Machine_Learning/blob/master/ps0/ps0_soln.pdf)

ps1:[Linear Regression](https://github.com/guozhonghao1994/BU_CS542_Machine_Learning/blob/master/ps1/pset1_ml2018_solution.pdf)

ps2:[Classification](https://github.com/guozhonghao1994/BU_CS542_Machine_Learning/blob/master/ps2/pset2_ml2018_solution.pdf)

ps3:[Cluster,PCA](https://github.com/guozhonghao1994/BU_CS542_Machine_Learning/tree/master/ps3/solution)

ps4:[Neural Networks](https://github.com/guozhonghao1994/BU_CS542_Machine_Learning/tree/master/ps4/solution)

ps5:[LDA,CNN](https://github.com/guozhonghao1994/BU_CS542_Machine_Learning/blob/master/ps5/pset5_lda.ipynb)

ps6:[SVM](https://github.com/guozhonghao1994/BU_CS542_Machine_Learning/blob/master/ps6/pset6-solution.ipynb)

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