In a nutshell, Moore's law says that every two years, computer capacity (memory, speed and so on) increases by a factor 2. How does this apply to big data? It seems like big data is also growing…Continue
Talking about the IT, big data, computer and data science communities, where teams are always a mix of Chinese, Indian, French (like me), British, American, Russian, German, Brazilian and other…Continue
This is a real-time optimization problem based on large data (captured by sensors, cameras, crowd-sourcing etc.) Mathematical models have been developed for this framework. It is typically considered…Continue
Dr. Vincent Granville is a visionary data scientist with 15 years of big data, predictive modeling, digital and business analytics experience. Vincent is widely recognized as the leading expert in scoring technology, fraud detection and web traffic optimization and growth. Over the last ten years, he has worked in real-time credit card fraud detection with Visa, advertising mix optimization with CNET, change point detection with Microsoft, online user experience with Wells Fargo, search intelligence with InfoSpace, automated bidding with eBay, click fraud detection with major search engines, ad networks and large advertising clients.
Most recently, Vincent launched Data Science Central, the leading social network for big data, business analytics and data science practitioners. Vincent is a former post-doctorate of Cambridge University and the National Institute of Statistical Sciences. He was among the finalists at the Wharton School Business Plan Competition and at the Belgian Mathematical Olympiads. Vincent has published 40 papers in statistical journals and is an invited speaker at international conferences. He also developed a new data mining technology known as hidden decision trees, owns multiple patents, published the first data science book, and raised $6MM in start-up funding. Vincent is a top 20 big data influencers according to Forbes, was featured on CNN, and is #1 in Gil Press' A-List of data scientists.
What kind of data is salable? How can data scientists independently make money by selling data that is automatically generated: raw data, research data (presented as customized reports), or predictions. In short, using an automated data generation / gathering or prediction system, working from home with no boss and no employee, and possibly no direct interactions with clients. An alternate career path that many of…Continue