Machine Learning

This repo contains my completed assignments in R and Python for Machine Learning courses.

Machine Learning Specialization (Coursera) by University of Washington

Predicting house prices by linear regression (https://github.com/androsova/machine_learning/blob/master/Predicting%20House%20Prices.ipynb)
Song recommender with popularity and personalized model (https://github.com/androsova/machine_learning/blob/master/Song%20Recommender.ipynb)
Document retrieval from Wikipedia by TF-IDF (term frequency–inverse document frequency) (https://github.com/androsova/machine_learning/blob/master/Document%20Retrieval.ipynb)

Practical Machine Learning (Coursera) by Johns Hopkins University

Human Activity Recognition (https://github.com/androsova/machine_learning/blob/master/practical_ml_assignment.Rmd)

Dataset description

The human activity recognition research has traditionally focused on discriminating between different activities, i.e. to predict "which" activity was performed at a specific point in time. With the Weight Lifting Exercises dataset, we can investigate "how (well)" an activity was performed by the wearer. The "how (well)" investigation has only received little attention so far, even though it potentially provides useful information for a large variety of applications,such as sports training.

Six young health participants were asked to perform one set of 10 repetitions of the Unilateral Dumbbell Biceps Curl in five different fashions: exactly according to the specification (Class A), throwing the elbows to the front (Class B), lifting the dumbbell only halfway (Class C), lowering the dumbbell only halfway (Class D) and throwing the hips to the front (Class E).

Class A corresponds to the specified execution of the exercise, while the other 4 classes correspond to common mistakes. Participants were supervised by an experienced weight lifter to make sure the execution complied to the manner they were supposed to simulate. The exercises were performed by six male participants aged between 20-28 years, with little weight lifting experience.

Source of information: http://groupware.les.inf.puc-rio.br/har#ixzz5PZerHbuq

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