Mar
2016 Apr Opinions, Interviews, Reports
All (108) | Courses, Education (8) | Meetings (13) | News, Features (28) | Opinions, Interviews, Reports (29) | Software (5) | Tutorials, Overviews (19) | Webcasts (6)
- The Development of Classification as a Learning Machine - Apr 29, 2016.
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.
- Positioning a Machine Learning Company - Apr 28, 2016.
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.
- Building effective “Citizens Data Scientist” teams - Apr 28, 2016.
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.
- Eugenics – journey to the dark side at the dawn of statistics - Apr 27, 2016.
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.
- Three Pitfalls to Avoid When Building Data Science Into Your Business - Apr 27, 2016.
An overview of pitfalls to avoid when building data science into your business, how to avoid them, and what to do instead.
- The “Thinking” Part of “Thinking Like A Data Scientist” - Apr 26, 2016.
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.
- Microsoft is Becoming M(ai)crosoft - Apr 25, 2016.
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.
- Turn your company into a data science-driven business in 6 steps - Apr 25, 2016.
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.
- Advantages of a Career in Data Science - Apr 23, 2016.
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.
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When Does Deep Learning Work Better Than SVMs or Random Forests®? - Apr 22, 2016.
Some advice on when a deep neural network may or may not outperform Support Vector Machines or Random Forests. - 3 Signs That BI Will Never Be The Same Again - Apr 22, 2016.
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.
- Metrics Gone Wrong – How Companies Are Optimizing The Wrong Way - Apr 20, 2016.
A critique of the over-abundant and misguided pursuit of metric completeness, and how it can result in incorrect "optimization."
- Does Your Company Need a Data Scientist? - Apr 19, 2016.
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.
- Top 15 Frameworks for Machine Learning Experts - Apr 19, 2016.
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.
- Internet of Things: “Connected” Does Not Equal “Smart” - Apr 18, 2016.
"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.
- Using Big Data Analytics To Prevent Crimes The “Minority Report” Way - Apr 18, 2016.
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.
- What Developers Actually Need to Know About Machine Learning - Apr 14, 2016.
Some guidance on what, exactly, it is that developers need to know to get up to speed with machine learning.
- Advantages and Risks of Self-Service Analytics - Apr 13, 2016.
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.
- Simplifying the Internet of Things Conversation - Apr 11, 2016.
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.
- Stochastic Depth Networks Accelerate Deep Network Training - Apr 7, 2016.
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.
- Link Analysis for Fraud Detection: How Linkurious enabled investigation of the massive Panama Papers leaks - Apr 6, 2016.
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.
- 10 Signs Of A Bad Data Scientist - Apr 6, 2016.
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.
- How IoT is Jeopardizing Your Business Security - Apr 5, 2016.
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.
- Open Data in Elections: Using Visualization and Graphical Discovery Analysis for Voter Education and Civic Engagement - Apr 5, 2016.
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.
- Will Data Science Insure Our Future? - Apr 4, 2016.
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?
- 3 Ways to Build an Analytics Dream Team - Apr 4, 2016.
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 used Deep Learning to change the language of search - Apr 1, 2016.
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.
- If Hollywood Made Movies About Machine Learning Algorithms - Apr 1, 2016.
A lighthearted take on the kind of movie Hollywood would produce if it took on machine learning algorithms.
- The Secret to a Perfect Data Science Interview - Apr 1, 2016.
How to interview a Data Scientist, in 5 steps. The secret to answering every question perfectly :).
When Does Deep Learning Work Better Than SVMs or Random Forests®?