Kaggle is an online community of data scientists and machine learners, owned by Google LLC. It offers an environment where users can find and publish datasets, explore and build models in a web-based data-science environment, work with other data scientists and machine learning engineers, and enter competitors to solve data science challenges.
The term Artificial Neural Networks (ANN) refers to a set of algorithms that try to mimic the brain. It is constructed of an input layer, the data you input, a number of hidden layers, which help to group unlabelled data according to similarities, and then the output layer which is the hypothesis. Neural networks can fall into a range of categories, this blog will focus on classification.
It's hard to go a day without hearing the word 'data'. We rely on data on a daily basis in all industries; media, education, technology, retail etc. We are all getting excited about the possibility of what data can do. We know the buzzwords; Analytics, Big Data, Data Visualisation and Data Science! But at the root of these buzzwords is the need for visible, authoritative, consistent data that we can rely on to gain insights to support missions and goals.
It's hard to miss the images of plastic waste in the media, with some of the statistics and pictures being both frightening and sickening. In 2015, the annual production of plastics increased to nearly 381 million tonnes, this is roughly equivalent to the mass of two-thirds of the world population. From a study conducted in 2010, it was estimated that 8 million tonnes of plastic entered the oceans with roughly 10,000 to 100,000s tonnes of plastic in surface waters (Our World in Data).
It was announced this week that the Gov.UK Verify had fallen short of its target of 25 million users by 2020, only securing 3.6 million so far. With a current spend of £154m on Verify, the government is due to stop funding it from April 2020, handing operations over to the private sector. So what is Verify and how did it fail?
There are few (if any) industries that can be transformed by artificial intelligence to the degree that healthcare can. As initiatives around the world seek to digitize healthcare data, there are huge opportunities for game-changing tools and platforms. However, with potentially a yottabyte (1024 gigabytes) of healthcare data in the United States alone, we are no closer to this utopian, data-driven world of healthcare. Data in existence is not standardized, highly fragmented and is stored in incompatible legacy platforms. The technology exists, so why is healthcare so far behind other sectors in utilizing existing technology and what needs to be done to catch up?
The fourth industrial revolution is about the acceleration of technology and digitisation. More and more companies are becoming equipped with the technology to make their job easier. Within the Government departments, the Met Police have introduced predictive policing and facial technology to tackle crime. HMRC have introduced a self-assessment platform for tax online, so instead of the long queues on the phone you can do it solo. The Department of Work and Pensions introduced an auto-enrolment scheme where citizens are automatically included unless they opt out. None of these above examples would've been possible without the innovation and technological advancement of the 21st century.
Any business/department can be defined by two things; strategy and processes. A strategy defines how an organisation succeeds, and processes are the operationalisation of that strategy; how a department buys, how it builds, how it sells. The trouble is, processes are complex, interdependent and often unpredictable – so even if a strategy is perfect, poorly executed processes will be your business’s downfall.
Big Data has many wonderful opportunities, some a little advanced for our current infrastructure but may become an everyday reality in a few years. Think of driverless cars or augmented and mixed reality, we are starting to embrace these new concepts but will be another 10 years before they really 'take over the world'. One opportunity that we see disseminating across the world is the use of data for 'Smart Cities'.