Complete Data Science Training: Mathematics, Statistics, Python, Advanced Statistics in Python

Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation, testing, and how hyperparameters could improve performance. Perform linear and logistic regressions in Python.

Important Facts

• The Field of Data Science
• The Problem
• The Solution
• The Skills
• Statistics
• Mathematics

News organisations all over the world have in recent years increased their use of analytics – systematic analysis of quantitative data on various aspects of audience behaviour aimed at growing audiences, increasing engagement, and improving newsroom workflows. In this Reuters Institute Report, we review how a range of different newsrooms across Europe and North America use analytics. On the basis of more than 30 interviews, we find the following

Leading digital news organisations are developing distinct forms of editorial analytics tailored to help them pursue their particular goals. these forms of editorial analytics differ from more rudimentary and generic approaches (1) in being aligned with the editorial priorities and organisational imperatives (whether commercial, non-profit, or public service) of specific news organisations, (2) in informing both short-term day-to-day decisions and longer-term strategic development, and (3) in continually evolving to keep pace with a changing media environment.

globally oriented US- and UK-based news organisations remain ahead of most others in their development and use of analytics, but market leaders in most countries are developing editorial analytics suited to their specific priorities and situations. Market leaders across continental Europe frequently have more in common with leading US and UK organisations than with their domestic competitors. Many news organisations across all the countries covered here continue to lag behind best practice

Because best-practice editorial analytics are tailored to the priorities and goals of a given organisation as well as the context in which it competes, there is no one right way to do analytics or one set of tools that will give an organisation everything it needs. Instead, news organisations need to think about how they can develop their analytics capability by making sure they combine (1) the right set of tools, (2) an organisational structure that incorporates the expertise to use them, and (3) a newsroom culture that embraces data-informed decision-making. Falling short in any one of these areas undermines an organisation’s analytics capability

the most sophisticated audience teams are keenly aware that analytics are not perfect. the data never tell the full story, and quantitative analysis always has to be supplemented by editorial expertise and other forms of qualitative judgement. Even the best editorial analytics continue to be constrained by the difficulties involved in defining and measuring many of the things that news organisations aim to achieve and is beset by a whole range of data-quality and data-access issues, exacerbated by rapid changes in the media environment.

Results

Journalists today not only need analytics to navigate an ever-more competitive battle for attention. Many journalists also want analytics, as an earlier period of scepticism seems to have given way to interest in how data and metrics can help newsrooms reach their target audiences and do better journalism. that is encouraging, because analytics and data metrics will continue to evolve, and if journalists are not part of that process, the tools and techniques developed will continue to reflect and empower commercial and technological priorities more than editorial priorities.