  With the availability of high precision digital sensors and cheap storage
medium, it is not uncommon to find large amounts of data collected on almost
all measurable attributes, both in nature and man-made habitats. Weather in
particular has been an area of keen interest for researchers to develop more
accurate and reliable prediction models. This paper presents a set of
experiments which involve the use of prevalent machine learning techniques to
build models to predict the day of the week given the weather data for that
particular day i.e. temperature, wind, rain etc., and test their reliability
across four cities in Australia {Brisbane, Adelaide, Perth, Hobart}. The
results provide a comparison of accuracy of these machine learning techniques
and their reliability to predict the day of the week by analysing the weather
data. We then apply the models to predict weather conditions based on the
available data.
