An explanation of how classification developed as a learning machine, from LDA to the perceptron, on to logistic regression, and through to support vector machines.
The classic guide for entrepreneurs preparing a pitch is Sequoia’s Business Plan Template. This post aims to be a mere addendum to that in the age of machine learning.
The idea of citizen data scientists is being for more than a year, which suggests businesses to put the people from the business side in the work of exploring and analyzing data. Understand how you and your organisation can be benefitted by this.
Today is the 80th anniversary of the death of Karl Pearson, one of the founding father of statistics (correlation coefficient, principal components, the p-value, and much more). He was also deeply involved with eugenics, a jarring reminder that truth often comes bundled with a measure of darkness.
People have a tendency to blindly trust claims from any source that they deem credible, whether or not it conflicts with their own experiences or common sense. Basic stats - common sense = dangerous conclusions viewed as fact.
This post is an overview and discussion of Microsoft's increasing investment in, and approach to, artificial intelligence, and how their philosophy differs from their competitors.
Transforming your business with (big) data analytics and data-driven insights is not a one-time event, but a journey. Here are 6 steps to help enterprises become data-science driven business and enjoy benefits along the way.
As the rampant growth of data science continues across industries, the opportunities are plenty for both aspiring and expert data scientists. Here is an overview of data science industries, opportunities and work locations.
Gartner officially deemed 2016 the year of Modern BI and with this new era of BI changes are inevitable. Understand how the traditional BI is reshaping in this data century with Scrollytelling, citizen data scientist and new BI approaches.
Your company needs a data scientist... doesn't it? It very well may not, but you need to know either way. Read on to determine whether or not your company could benefit from the skills of an on-board data scientist.
Either you are a researcher, start-up or big organization who wants to use machine learning, you will need the right tools to make it happen. Here is a list of the most popular frameworks for machine learning.
"Connected" and "smart" are not synonyms, and bridging the gap takes a lot of upfront work; but with work invested in identifying, understanding and supporting the key decisions, the more productive the data science will be.
The idea of using artificial intelligence for the crime prevention has been around for more than a decade. In this post, we present four examples, including how using analytics, we can prevent a criminal from re-offending.
Self-service analytics is likely to spread in all the business layers, and with proper care to avoid certain risks, the culture of self-service analytics will help all organizations.
The IoT is one of a number of new sources, along with social media and wearable computing, which can be combined with data science, collectively as the Big Data Killer App for organizations.
Read about the presentation and overview of a new deep neural network architectural method, and the response to some strong reaction that it brought about.
Linkurious is a partner of the International Investigative Journalist Consortium (ICIJ) since the Swiss Leaks scandal. ICIJ network of 370 journalists is using Linkurious to investigate the Panama Papers. Learn the inside story of the biggest data leak investigation in history.
With the number of people claiming to be a data scientist growing, the “true” data scientists are becoming hard to find. Here your guide identify the clues to catch a bad data scientists.
With the rising wave of IoT devices, businesses everywhere are faced yet with another challenge: to ensure an adequate security level while also continuously integrating new technologies.
This article makes a case for the importance of innovating using open data, its also proves that adapting open data principles with visual design can enhance transparency, foster accountability, and aid citizen and voter education in elections.
Could Data Science in the insurance industry actually reduce the price of policies, as individual companies and people are no longer being judged against the average, and might be incentivised to change their lifestyle to improve their policy?
So your March Madness bracket is busted. Maybe that new algorithm can through the first round next year. It's never too early to start building your analytics Dream Team.
How Shutterstock created computer-vision and Deep Learning technology that understands their 70 million-plus images and takes away the need for customers to type in descriptions and unreliable keywording. The technology relies on pixel data as its language of choice.
When Does Deep Learning Work Better Than SVMs or Random Forests®?
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