UK elections: What May have said?

I am analysing the transcript of the UK prime minister speech which was delivered on 18th April 2017. She announced that there will be the general election on 8th June 2017. Here is the full transcript (Source: FT) “I have just chaired a meeting of Cabinet, where we agreed that the government should call a general election to be held on June 8. I want … Continue reading UK elections: What May have said?

Prime drivers of Aberdeen house price

1. Introduction Aberdeen is the third largest city in Scotland with a population of 230,000. Oil and gas are the prime driver of the Aberdeen economy, which has created more than 40,000 jobs. Economically, it has generated a revenue of £330 billion since 1970, in the form of direct taxes[1]. Since the economy of Aberdeen is driven by oil, the property market is one of … Continue reading Prime drivers of Aberdeen house price

Predicting satisfaction level of the region.

1. Introduction Office of National Statistics (ONS), and University of Manchester conducted an Opinions and Lifestyle Survey of 2048 people,  to understand their satisfaction level. The data set consist of following information Figure 1. Data index There are 12 different satisfaction indicators and 10 different demographic and personal information. 2. Aim and Objective The objective of the study is to identify whether machine learning can be used … Continue reading Predicting satisfaction level of the region.

Twitter data mining using Python and R

Introduction This post will introduce you to the data mining techniques in Python and R. This process consist of retrieving data (tweets) from the twitter website and analysing the tweets for a pattern. The whole process broadly follows two steps: Retrieving data from twitter Analysing the data for pattern and sentiment Retrieving data from twitter Twitter has developed an API which helps programming language like R … Continue reading Twitter data mining using Python and R

K-Means clustering (Scikit learn, Python and IPython notebook

Introduction Machine learning can be broadly divided into two categories based on the utility of the algorithm, these are: (a) Supervised and (b) Unsupervised. In supervised learning, the user tells the algorithm what to do. For example: What is the probability it will rain tomorrow given that it is the third week of June. Whereas, in the case of unsupervised learning, the machine calculates the best possible solution for a given … Continue reading K-Means clustering (Scikit learn, Python and IPython notebook