Our news and views relating to Data Analytics, Big Data, Machine Learning, and the world of Credit.
Shortly after the winners of the Oscars for Best Actor, Best Actress, Best Director and Best Picture were announced, John Robbie of Talk 702 spoke to Principa Data Scientist, Johan van Biljon, for a follow-up interview to find out how accurate Principa's predictions had been. Using data analytics, Principa correctly predicted Leo would win an Oscar for Best Actor, Brie Larson would win for Best Actress, and Iñárritu to win for Best Director.
John Robbie from Talk Radio 702 speaks to Principa Data Scientist, John Van Biljoen, about Principa's predictions for the Oscars this weekend. Principa's predictions are based on data analyticfrom over 80 years worth of Oscar winning movies.
We analysed 80 years of Oscars data to predict this year's Oscars winners. Along the way, we discovered some very interesting insights. Did you know 24% of Oscar winning films were based on a true story? Four of this year's Oscar nominees for Best Actor star in a film based on a true story. Is this a growing trend?
Spanish entertainment news website, Super Cartelera, picked up on the hype created by Principa around our predictions for this years Oscar nominees stating this might be the year Leo finally gets his Oscar. Apart from mentioning the other three nominees for Best Actress, Best Picture and Best Director, Super Cartelera found our infographic: "Oscars loves a True Story" particularly interesting highlighting that half of the movies nominated for an Oscar this year is based on a true story.
Data Scientist Tom Maydon speaks to CliffCentral host Gareth Cliff on how Principa used data analytics to predict the winners of the Oscars in the top four major categories.
Principa shares its predictions of who we think will win the 2016 Oscar Awards in the four major catergories with local technology news website ITweb. The data scientists at Principa have used data from hundreds of movies spanning back to 1935 to make these predictions.
Tech-savvy insight and analysis website Memeburn asks the question, can data analytics be used to predict who will win the Oscars and we believe we have the answer.
Times Live takes a look at who we predicted to win the Oscars this year based on Oscar data analysed from the past 80 years.
Read South African tech blog, HTXT.Africa, and their take on our Oscar predictions.
Following a highly successful initiative of using Machine Learning to predict last year’s Rugby World Cup results, we're trying our hand again at predicting the future and revealing some interesting insights along the way about another major event: The Academy Awards, or the Oscars.
Data has redefined how businesses understand their customer base and make decisions. For instance, it’s transformed marketing from a relatively intangible expense into a clear-cut investment with a measurable ROI and targetable initiatives. However, strategically applied data has more uses than strengthening your marketing efforts alone, especially when it comes to understanding your existing customers and better attending to their needs.
How does a credit card company differentiate itself in a market saturated with special offers, low interest rates, and convoluted rewards programs?
When you think of machine learning in action, it’s easy to imagine analytics-based marketing research or a matrix-style AI takeover. But there are actually far more grounded and practical applications that benefit hundreds of millions of people in their day-to-day leisure and business activities. Take the travel industry, for example. We’ve now reached a point in human history where over 100,000 flights are taking off every single day. With airports seeing more foot traffic than ever before – Dubai International alone saw over 78 million passengers in 2015 – they need to be run and managed like a carefully oiled machine. Alleviating bottlenecks is central to ensuring as smooth an operation as possible in the travelling experience.
In emerging or developing markets where formal credit history collection infrastructure or credit bureaus are lacking, the majority of people without reference data would struggle to achieve anything resembling an impressive credit score. As a large contingent of previously unbanked individuals join their respective middle classes in increasing numbers worldwide, lenders are finding creative ways of profiling and welcoming newcomers to the world of financial services.
The aim of a marketing director is simple: 1) to get your brand noticed by the right people and 2) to get the right people to choose it over your competitors’. As we all know, that task is becoming both more difficult and easier every day. With the rise of social media and mobile marketing it has become increasingly easy and cost-effective to reach a large audience. And the time required to do so has been cut dramatically. As a result, however, it has also become more difficult to compete for attention as the traditional barriers to building a brand, such as budget and geography, dissipate.